hf_text-generation-inference/Cargo.lock

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2022-10-08 04:30:12 -06:00
# This file is automatically @generated by Cargo.
# It is not intended for manual editing.
version = 3
2023-07-01 11:25:41 -06:00
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2023-07-01 11:25:41 -06:00
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2023-07-01 11:25:41 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2024-03-22 11:44:05 -06:00
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2024-03-22 11:44:05 -06:00
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dependencies = [
2023-07-01 11:25:41 -06:00
"cfg-if",
"getrandom",
"once_cell",
"serde",
"version_check",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"zerocopy",
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2022-10-08 04:30:12 -06:00
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2024-03-22 11:44:05 -06:00
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2022-10-08 04:30:12 -06:00
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2024-03-22 11:44:05 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.6.15"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "64e15c1ab1f89faffbf04a634d5e1962e9074f2741eef6d97f3c4e322426d526"
2022-10-08 04:30:12 -06:00
dependencies = [
"anstyle",
"anstyle-parse",
"anstyle-query",
"anstyle-wincon",
"colorchoice",
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
"is_terminal_polyfill",
"utf8parse",
]
[[package]]
name = "anstyle"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.0.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "1bec1de6f59aedf83baf9ff929c98f2ad654b97c9510f4e70cf6f661d49fd5b1"
[[package]]
name = "anstyle-parse"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.2.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "eb47de1e80c2b463c735db5b217a0ddc39d612e7ac9e2e96a5aed1f57616c1cb"
dependencies = [
"utf8parse",
]
[[package]]
name = "anstyle-query"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.1.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "6d36fc52c7f6c869915e99412912f22093507da8d9e942ceaf66fe4b7c14422a"
dependencies = [
2023-12-11 04:46:30 -07:00
"windows-sys 0.52.0",
]
[[package]]
name = "anstyle-wincon"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "3.0.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "5bf74e1b6e971609db8ca7a9ce79fd5768ab6ae46441c572e46cf596f59e57f8"
dependencies = [
"anstyle",
2023-12-11 04:46:30 -07:00
"windows-sys 0.52.0",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "anyhow"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "1.0.86"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "b3d1d046238990b9cf5bcde22a3fb3584ee5cf65fb2765f454ed428c7a0063da"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2024-03-29 12:17:24 -06:00
version = "1.7.1"
2022-10-08 04:30:12 -06:00
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2024-03-29 12:17:24 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.7.6"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "7c02d123df017efcdfbd739ef81735b36c5ba83ec3c59c80a9d7ecc718f92e50"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"rustls 0.20.9",
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2022-10-08 04:30:12 -06:00
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2023-04-11 12:32:18 -06:00
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2022-10-08 04:30:12 -06:00
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2023-04-11 12:32:18 -06:00
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2022-10-08 04:30:12 -06:00
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2023-02-24 05:27:41 -07:00
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2022-10-08 04:30:12 -06:00
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2023-04-11 12:32:18 -06:00
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2022-10-08 04:30:12 -06:00
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2023-04-11 12:32:18 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
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[[package]]
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.1.81"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "6e0c28dcc82d7c8ead5cb13beb15405b57b8546e93215673ff8ca0349a028107"
2022-10-08 04:30:12 -06:00
dependencies = [
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
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2022-10-08 04:30:12 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "1.3.0"
2022-10-08 04:30:12 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "0c4b4d0bd25bd0b74681c0ad21497610ce1b7c91b1022cd21c80c6fbdd9476b0"
2022-10-08 04:30:12 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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[[package]]
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2024-03-22 11:44:05 -06:00
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2024-03-22 11:44:05 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2024-06-27 00:08:43 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.8.1"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "4ae74d9bd0a7530e8afd1770739ad34b36838829d6ad61818f9230f683f5ad77"
2024-06-27 00:08:43 -06:00
dependencies = [
"aws-lc-sys",
"mirai-annotations",
"paste",
"zeroize",
]
[[package]]
name = "aws-lc-sys"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.20.1"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "0f0e249228c6ad2d240c2dc94b714d711629d52bad946075d8e9b2f5391f0703"
2024-06-27 00:08:43 -06:00
dependencies = [
"bindgen",
"cc",
"cmake",
"dunce",
"fs_extra",
"libc",
"paste",
]
2022-10-11 10:14:39 -06:00
[[package]]
name = "axum"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
version = "0.6.20"
2022-10-11 10:14:39 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
checksum = "3b829e4e32b91e643de6eafe82b1d90675f5874230191a4ffbc1b336dec4d6bf"
2022-10-11 10:14:39 -06:00
dependencies = [
"async-trait",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"axum-core 0.3.4",
2023-07-01 11:25:41 -06:00
"bitflags 1.3.2",
2022-10-11 10:14:39 -06:00
"bytes",
"futures-util",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
"http-body 0.4.6",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"hyper 0.14.30",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"itoa",
"matchit",
"memchr",
"mime",
"percent-encoding",
"pin-project-lite",
"rustversion",
"serde",
"serde_json",
"serde_path_to_error",
"serde_urlencoded",
"sync_wrapper 0.1.2",
"tokio",
"tower",
"tower-layer",
"tower-service",
]
[[package]]
name = "axum"
version = "0.7.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3a6c9af12842a67734c9a2e355436e5d03b22383ed60cf13cd0c18fbfe3dcbcf"
dependencies = [
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"http-body 1.0.1",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http-body-util",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"hyper 1.4.1",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"hyper-util",
2022-10-11 10:14:39 -06:00
"itoa",
"matchit",
"memchr",
"mime",
"percent-encoding",
"pin-project-lite",
"rustversion",
2022-10-11 10:14:39 -06:00
"serde",
"serde_json",
"serde_path_to_error",
2022-10-11 10:14:39 -06:00
"serde_urlencoded",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"sync_wrapper 1.0.1",
2022-10-11 10:14:39 -06:00
"tokio",
"tower",
"tower-layer",
"tower-service",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"tracing",
2022-10-11 10:14:39 -06:00
]
[[package]]
name = "axum-core"
2023-04-11 12:32:18 -06:00
version = "0.3.4"
2022-10-11 10:14:39 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-04-11 12:32:18 -06:00
checksum = "759fa577a247914fd3f7f76d62972792636412fbfd634cd452f6a385a74d2d2c"
2022-10-11 10:14:39 -06:00
dependencies = [
"async-trait",
"bytes",
"futures-util",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
"http-body 0.4.6",
"mime",
"rustversion",
"tower-layer",
"tower-service",
]
[[package]]
name = "axum-core"
version = "0.4.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "a15c63fd72d41492dc4f497196f5da1fb04fb7529e631d73630d1b491e47a2e3"
dependencies = [
"async-trait",
"bytes",
"futures-util",
"http 1.1.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"http-body 1.0.1",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http-body-util",
2022-10-11 10:14:39 -06:00
"mime",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"pin-project-lite",
"rustversion",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"sync_wrapper 0.1.2",
2022-10-11 10:14:39 -06:00
"tower-layer",
"tower-service",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"tracing",
2022-10-11 10:14:39 -06:00
]
2023-02-13 05:02:45 -07:00
[[package]]
name = "axum-tracing-opentelemetry"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.16.0"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "bdad298231394729042d1f155b93f9fdf0b5ee1aea0b62404c4d7341f7d8fe08"
2023-02-13 05:02:45 -07:00
dependencies = [
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"axum 0.7.5",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"futures-core",
"futures-util",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 1.1.0",
"opentelemetry 0.21.0",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"pin-project-lite",
2023-02-13 05:02:45 -07:00
"tower",
"tracing",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"tracing-opentelemetry 0.22.0",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"tracing-opentelemetry-instrumentation-sdk",
2023-07-01 11:25:41 -06:00
]
[[package]]
name = "backtrace"
2024-06-27 00:08:43 -06:00
version = "0.3.73"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
checksum = "5cc23269a4f8976d0a4d2e7109211a419fe30e8d88d677cd60b6bc79c5732e0a"
2023-07-01 11:25:41 -06:00
dependencies = [
"addr2line",
"cc",
"cfg-if",
"libc",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"miniz_oxide 0.7.4",
2023-07-01 11:25:41 -06:00
"object",
"rustc-demangle",
2023-02-13 05:02:45 -07:00
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "base64"
version = "0.13.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9e1b586273c5702936fe7b7d6896644d8be71e6314cfe09d3167c95f712589e8"
2022-10-08 04:30:12 -06:00
2023-02-13 05:02:45 -07:00
[[package]]
name = "base64"
2024-01-26 11:04:57 -07:00
version = "0.21.7"
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-01-26 11:04:57 -07:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "base64"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
version = "0.22.1"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "72b3254f16251a8381aa12e40e3c4d2f0199f8c6508fbecb9d91f575e0fbb8c6"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
2024-06-27 00:08:43 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2024-06-27 00:08:43 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-01 11:25:41 -06:00
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2024-06-27 00:08:43 -06:00
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2023-07-01 11:25:41 -06:00
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2024-06-27 00:08:43 -06:00
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2023-07-01 11:25:41 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "built"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.7.4"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "236e6289eda5a812bc6b53c3b024039382a2895fbbeef2d748b2931546d392c4"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
2022-10-08 04:30:12 -06:00
[[package]]
name = "bumpalo"
2024-04-12 10:38:34 -06:00
version = "3.16.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-04-12 10:38:34 -06:00
checksum = "79296716171880943b8470b5f8d03aa55eb2e645a4874bdbb28adb49162e012c"
2022-10-08 04:30:12 -06:00
[[package]]
name = "bytecount"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
version = "0.6.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "5ce89b21cab1437276d2650d57e971f9d548a2d9037cc231abdc0562b97498ce"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "bytemuck"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.17.1"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "773d90827bc3feecfb67fab12e24de0749aad83c74b9504ecde46237b5cd24e2"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
2022-10-08 04:30:12 -06:00
[[package]]
name = "byteorder"
2023-11-30 07:18:15 -07:00
version = "1.5.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
2022-10-08 04:30:12 -06:00
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
[[package]]
name = "byteorder-lite"
version = "0.1.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "8f1fe948ff07f4bd06c30984e69f5b4899c516a3ef74f34df92a2df2ab535495"
2022-10-08 04:30:12 -06:00
[[package]]
name = "bytes"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.7.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "8318a53db07bb3f8dca91a600466bdb3f2eaadeedfdbcf02e1accbad9271ba50"
2022-10-08 04:30:12 -06:00
2024-01-26 11:04:57 -07:00
[[package]]
name = "camino"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.1.9"
2024-01-26 11:04:57 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "8b96ec4966b5813e2c0507c1f86115c8c5abaadc3980879c3424042a02fd1ad3"
2024-01-26 11:04:57 -07:00
dependencies = [
"serde",
]
[[package]]
name = "cargo-platform"
2024-03-22 11:44:05 -06:00
version = "0.1.8"
2024-01-26 11:04:57 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-22 11:44:05 -06:00
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2024-01-26 11:04:57 -07:00
dependencies = [
"serde",
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[[package]]
name = "cargo_metadata"
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dependencies = [
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"thiserror",
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[[package]]
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source = "registry+https://github.com/rust-lang/crates.io-index"
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[[package]]
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version = "0.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
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2022-10-08 04:30:12 -06:00
[[package]]
name = "cc"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.1.15"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "57b6a275aa2903740dc87da01c62040406b8812552e97129a63ea8850a17c6e6"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
"jobserver",
"libc",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"shlex",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
]
2024-06-27 00:08:43 -06:00
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dependencies = [
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "cfg-expr"
2024-04-12 10:38:34 -06:00
version = "0.15.8"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-04-12 10:38:34 -06:00
checksum = "d067ad48b8650848b989a59a86c6c36a995d02d2bf778d45c3c5d57bc2718f02"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
[[package]]
name = "cfg_aliases"
version = "0.2.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "613afe47fcd5fac7ccf1db93babcb082c5994d996f20b8b159f2ad1658eb5724"
2024-06-27 00:08:43 -06:00
[[package]]
name = "clang-sys"
version = "1.8.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0b023947811758c97c59bf9d1c188fd619ad4718dcaa767947df1cadb14f39f4"
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[[package]]
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version = "2.34.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
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"textwrap",
"unicode-width",
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2022-10-17 10:27:33 -06:00
[[package]]
name = "clap"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "4.5.16"
2022-10-17 10:27:33 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "ed6719fffa43d0d87e5fd8caeab59be1554fb028cd30edc88fc4369b17971019"
2022-10-17 10:27:33 -06:00
dependencies = [
"clap_builder",
2022-10-17 10:27:33 -06:00
"clap_derive",
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[[package]]
name = "clap_builder"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "4.5.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "216aec2b177652e3846684cbfe25c9964d18ec45234f0f5da5157b207ed1aab6"
dependencies = [
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"strsim",
2022-10-17 10:27:33 -06:00
]
[[package]]
name = "clap_derive"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "4.5.13"
2022-10-17 10:27:33 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "501d359d5f3dcaf6ecdeee48833ae73ec6e42723a1e52419c79abf9507eec0a0"
2022-10-17 10:27:33 -06:00
dependencies = [
2024-03-22 11:44:05 -06:00
"heck 0.5.0",
2022-10-17 10:27:33 -06:00
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-17 10:27:33 -06:00
]
[[package]]
name = "clap_lex"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.7.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "1462739cb27611015575c0c11df5df7601141071f07518d56fcc1be504cbec97"
2024-06-27 00:08:43 -06:00
[[package]]
name = "cmake"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.1.51"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "fb1e43aa7fd152b1f968787f7dbcdeb306d1867ff373c69955211876c053f91a"
2024-06-27 00:08:43 -06:00
dependencies = [
"cc",
]
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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version = "0.11.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3538270d33cc669650c4b093848450d380def10c331d38c768e34cac80576e6e"
dependencies = [
"termcolor",
"unicode-width",
]
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3d7b894f5411737b7867f4827955924d7c254fc9f4d91a6aad6b097804b1018b"
[[package]]
name = "colorchoice"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.0.2"
2022-10-17 10:27:33 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2022-10-17 10:27:33 -06:00
2022-10-08 04:30:12 -06:00
[[package]]
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2024-01-26 11:04:57 -07:00
version = "0.15.8"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-01-26 11:04:57 -07:00
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2022-10-08 04:30:12 -06:00
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2024-01-26 11:04:57 -07:00
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2022-10-08 04:30:12 -06:00
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2023-12-11 04:46:30 -07:00
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2022-10-08 04:30:12 -06:00
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2023-12-11 04:46:30 -07:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.8.7"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "773648b94d0e5d620f64f280777445740e61fe701025087ec8b57f45c791888b"
2022-10-08 04:30:12 -06:00
[[package]]
name = "cpufeatures"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.13"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "51e852e6dc9a5bed1fae92dd2375037bf2b768725bf3be87811edee3249d09ad"
2022-10-08 04:30:12 -06:00
dependencies = [
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]
[[package]]
name = "crc32fast"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "1.4.2"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "a97769d94ddab943e4510d138150169a2758b5ef3eb191a9ee688de3e23ef7b3"
2022-10-08 04:30:12 -06:00
dependencies = [
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]
[[package]]
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source = "registry+https://github.com/rust-lang/crates.io-index"
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"serde",
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dependencies = [
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2022-10-08 04:30:12 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "33480d6946193aa8033910124896ca395333cae7e2d1113d1fef6c3272217df2"
2022-10-08 04:30:12 -06:00
dependencies = [
"crossbeam-utils",
]
[[package]]
name = "crossbeam-deque"
2024-01-26 11:04:57 -07:00
version = "0.8.5"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-01-26 11:04:57 -07:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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]
[[package]]
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2024-01-26 11:04:57 -07:00
version = "0.9.18"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-01-26 11:04:57 -07:00
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2022-10-08 04:30:12 -06:00
dependencies = [
"crossbeam-utils",
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[[package]]
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.8.20"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "22ec99545bb0ed0ea7bb9b8e1e9122ea386ff8a48c0922e43f36d45ab09e0e80"
2022-10-08 04:30:12 -06:00
[[package]]
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.27.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "f476fe445d41c9e991fd07515a6f463074b782242ccf4a5b7b1d1012e70824df"
dependencies = [
2024-06-27 00:08:43 -06:00
"bitflags 2.6.0",
"crossterm_winapi",
"libc",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-18 07:19:03 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-18 07:19:03 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "90eeab0aa92f3f9b4e87f258c72b139c207d251f9cbc1080a0086b86a8870dd3"
2022-10-18 07:19:03 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"nix 0.29.0",
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2022-10-18 07:19:03 -06:00
]
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
name = "cxx"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.126"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "3c4eae4b7fc8dcb0032eb3b1beee46b38d371cdeaf2d0c64b9944f6f69ad7755"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
dependencies = [
"cc",
"cxxbridge-flags",
"cxxbridge-macro",
"link-cplusplus",
]
[[package]]
name = "cxx-build"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.126"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "6c822bf7fb755d97328d6c337120b6f843678178751cba33c9da25cf522272e0"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
dependencies = [
"cc",
"codespan-reporting",
"once_cell",
"proc-macro2",
"quote",
"scratch",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
]
[[package]]
name = "cxxbridge-flags"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.126"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "719d6197dc016c88744aff3c0d0340a01ecce12e8939fc282e7c8f583ee64bc6"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
name = "cxxbridge-macro"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.126"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "35de3b547387863c8f82013c4f79f1c2162edee956383e4089e1d04c18c4f16c"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
dependencies = [
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "darling"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.20.10"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "6f63b86c8a8826a49b8c21f08a2d07338eec8d900540f8630dc76284be802989"
2022-10-08 04:30:12 -06:00
dependencies = [
"darling_core",
"darling_macro",
]
[[package]]
name = "darling_core"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.20.10"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "95133861a8032aaea082871032f5815eb9e98cef03fa916ab4500513994df9e5"
2022-10-08 04:30:12 -06:00
dependencies = [
"fnv",
"ident_case",
"proc-macro2",
"quote",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"strsim",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "darling_macro"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.20.10"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "d336a2a514f6ccccaa3e09b02d41d35330c07ddf03a62165fcec10bb561c7806"
2022-10-08 04:30:12 -06:00
dependencies = [
"darling_core",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
]
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
[[package]]
name = "deranged"
2024-01-26 11:04:57 -07:00
version = "0.3.11"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-01-26 11:04:57 -07:00
checksum = "b42b6fa04a440b495c8b04d0e71b707c585f83cb9cb28cf8cd0d976c315e31b4"
2023-11-30 07:18:15 -07:00
dependencies = [
"powerfmt",
]
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
2022-10-08 04:30:12 -06:00
[[package]]
name = "derive_builder"
2024-04-18 09:17:40 -06:00
version = "0.20.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-04-18 09:17:40 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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2022-10-08 04:30:12 -06:00
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2024-04-18 09:17:40 -06:00
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2022-10-08 04:30:12 -06:00
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2024-04-18 09:17:40 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
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2024-04-18 09:17:40 -06:00
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2022-10-08 04:30:12 -06:00
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2024-04-18 09:17:40 -06:00
checksum = "206868b8242f27cecce124c19fd88157fbd0dd334df2587f36417bafbc85097b"
2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"dirs-sys",
2022-10-08 04:30:12 -06:00
]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2024-06-27 00:08:43 -06:00
[[package]]
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.5"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "92773504d58c093f6de2459af4af33faa518c13451eb8f2b5698ed3d36e7c813"
2024-06-27 00:08:43 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.5.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "10936778145f3bea71fd9bf61332cce28c28e96a380714f7ab34838b80733fd6"
dependencies = [
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2022-10-08 04:30:12 -06:00
[[package]]
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2024-06-27 00:08:43 -06:00
version = "1.13.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
checksum = "60b1af1c220855b6ceac025d3f6ecdd2b7c4894bfe9cd9bda4fbb4bc7c0d4cf0"
2022-10-08 04:30:12 -06:00
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2024-04-12 10:38:34 -06:00
version = "0.8.34"
2022-10-08 04:30:12 -06:00
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2024-04-12 10:38:34 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-14 08:31:48 -06:00
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2023-02-13 05:02:45 -07:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.3.9"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2023-02-13 05:02:45 -07:00
dependencies = [
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2023-11-30 07:18:15 -07:00
"windows-sys 0.52.0",
2023-02-13 05:02:45 -07:00
]
2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
version = "0.1.10"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
"lebe",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"miniz_oxide 0.7.4",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "2.1.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "e8c02a5121d4ea3eb16a80748c74f5549a5665e4c21333c6098f283870fbdea6"
2022-10-08 04:30:12 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
version = "0.3.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
checksum = "eac8f7d7865dcb88bd4373ab671c8cf4508703796caa2b1985a9ca867b3fcb78"
2022-10-08 04:30:12 -06:00
dependencies = [
"futures-core",
"futures-sink",
]
[[package]]
name = "futures-core"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
version = "0.3.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
checksum = "dfc6580bb841c5a68e9ef15c77ccc837b40a7504914d52e47b8b0e9bbda25a1d"
2022-10-08 04:30:12 -06:00
[[package]]
name = "futures-executor"
2024-01-26 11:04:57 -07:00
version = "0.3.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-01-26 11:04:57 -07:00
checksum = "a576fc72ae164fca6b9db127eaa9a9dda0d61316034f33a0a0d4eda41f02b01d"
2022-10-08 04:30:12 -06:00
dependencies = [
"futures-core",
"futures-task",
"futures-util",
]
[[package]]
name = "futures-io"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
version = "0.3.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
checksum = "a44623e20b9681a318efdd71c299b6b222ed6f231972bfe2f224ebad6311f0c1"
2022-10-08 04:30:12 -06:00
[[package]]
name = "futures-macro"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
version = "0.3.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
checksum = "87750cf4b7a4c0625b1529e4c543c2182106e4dedc60a2a6455e00d212c489ac"
2022-10-08 04:30:12 -06:00
dependencies = [
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "futures-sink"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
version = "0.3.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
checksum = "9fb8e00e87438d937621c1c6269e53f536c14d3fbd6a042bb24879e57d474fb5"
2022-10-08 04:30:12 -06:00
[[package]]
name = "futures-task"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
version = "0.3.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
checksum = "38d84fa142264698cdce1a9f9172cf383a0c82de1bddcf3092901442c4097004"
2022-10-08 04:30:12 -06:00
[[package]]
name = "futures-util"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
version = "0.3.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2022-10-08 04:30:12 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-01 11:25:41 -06:00
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2022-10-08 04:30:12 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2023-07-01 11:25:41 -06:00
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2023-02-13 05:02:45 -07:00
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2023-02-13 05:02:45 -07:00
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2023-02-13 05:02:45 -07:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"opentelemetry 0.20.0",
2023-11-30 07:18:15 -07:00
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2023-02-13 05:02:45 -07:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2023-02-13 05:02:45 -07:00
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2022-10-08 04:30:12 -06:00
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2024-04-12 10:38:34 -06:00
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2022-10-08 04:30:12 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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2023-02-13 05:02:45 -07:00
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2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.4.6"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "524e8ac6999421f49a846c2d4411f337e53497d8ec55d67753beffa43c5d9205"
2024-06-27 00:08:43 -06:00
dependencies = [
"atomic-waker",
"bytes",
"fnv",
"futures-core",
"futures-sink",
"http 1.1.0",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"indexmap 2.4.0",
2024-06-27 00:08:43 -06:00
"slab",
"tokio",
"tokio-util",
"tracing",
]
[[package]]
name = "half"
version = "1.8.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "half"
version = "2.4.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "6dd08c532ae367adf81c312a4580bc67f1d0fe8bc9c460520283f4c0ff277888"
dependencies = [
"cfg-if",
"crunchy",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "hashbrown"
version = "0.12.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "8a9ee70c43aaf417c914396645a0fa852624801b24ebb7ae78fe8272889ac888"
2023-07-01 11:25:41 -06:00
[[package]]
name = "hashbrown"
2024-06-27 00:08:43 -06:00
version = "0.14.5"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
checksum = "e5274423e17b7c9fc20b6e7e208532f9b19825d82dfd615708b70edd83df41f1"
dependencies = [
"ahash",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "heck"
2023-02-13 05:02:45 -07:00
version = "0.4.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-02-13 05:02:45 -07:00
checksum = "95505c38b4572b2d910cecb0281560f54b440a19336cbbcb27bf6ce6adc6f5a8"
2022-10-08 04:30:12 -06:00
2024-03-22 11:44:05 -06:00
[[package]]
name = "heck"
version = "0.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "2304e00983f87ffb38b55b444b5e3b60a884b5d30c0fca7d82fe33449bbe55ea"
[[package]]
name = "hermit-abi"
version = "0.1.19"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "62b467343b94ba476dcb2500d242dadbb39557df889310ac77c5d99100aaac33"
dependencies = [
"libc",
]
2023-02-13 05:02:45 -07:00
[[package]]
name = "hermit-abi"
2024-03-22 11:44:05 -06:00
version = "0.3.9"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-22 11:44:05 -06:00
checksum = "d231dfb89cfffdbc30e7fc41579ed6066ad03abda9e567ccafae602b97ec5024"
2023-02-13 05:02:45 -07:00
[[package]]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "hf-hub"
2023-11-30 07:18:15 -07:00
version = "0.3.2"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "2b780635574b3d92f036890d8373433d6f9fc7abb320ee42a5c25897fc8ed732"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
dependencies = [
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"dirs",
"futures",
2023-11-30 07:18:15 -07:00
"indicatif",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"log",
"native-tls",
"num_cpus",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"rand",
"reqwest",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"serde",
"serde_json",
"thiserror",
"tokio",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"ureq",
]
2024-06-27 00:08:43 -06:00
[[package]]
name = "home"
version = "0.5.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e3d1354bf6b7235cb4a0576c2619fd4ed18183f689b12b006a0ee7329eeff9a5"
dependencies = [
"windows-sys 0.52.0",
]
[[package]]
name = "hostname"
version = "0.3.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3c731c3e10504cc8ed35cfe2f1db4c9274c3d35fa486e3b31df46f068ef3e867"
dependencies = [
"libc",
"match_cfg",
"winapi",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "http"
2024-03-22 11:44:05 -06:00
version = "0.2.12"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-22 11:44:05 -06:00
checksum = "601cbb57e577e2f5ef5be8e7b83f0f63994f25aa94d673e54a92d5c516d101f1"
2022-10-08 04:30:12 -06:00
dependencies = [
"bytes",
"fnv",
"itoa",
]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
[[package]]
name = "http"
version = "1.1.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "21b9ddb458710bc376481b842f5da65cdf31522de232c1ca8146abce2a358258"
dependencies = [
"bytes",
"fnv",
"itoa",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "http-body"
2023-12-11 06:55:03 -07:00
version = "0.4.6"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-12-11 06:55:03 -07:00
checksum = "7ceab25649e9960c0311ea418d17bee82c0dcec1bd053b5f9a66e265a693bed2"
2022-10-08 04:30:12 -06:00
dependencies = [
"bytes",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
2022-10-08 04:30:12 -06:00
"pin-project-lite",
]
2022-10-11 10:14:39 -06:00
[[package]]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
name = "http-body"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.0.1"
2022-10-11 10:14:39 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "1efedce1fb8e6913f23e0c92de8e62cd5b772a67e7b3946df930a62566c93184"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
dependencies = [
"bytes",
"http 1.1.0",
]
[[package]]
name = "http-body-util"
2024-06-27 00:08:43 -06:00
version = "0.1.2"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
checksum = "793429d76616a256bcb62c2a2ec2bed781c8307e797e2598c50010f2bee2544f"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
dependencies = [
"bytes",
2024-06-27 00:08:43 -06:00
"futures-util",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 1.1.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"http-body 1.0.1",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"pin-project-lite",
]
2022-10-11 10:14:39 -06:00
2022-10-08 04:30:12 -06:00
[[package]]
name = "httparse"
2024-06-27 00:08:43 -06:00
version = "1.9.4"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
checksum = "0fcc0b4a115bf80b728eb8ea024ad5bd707b615bfed49e0665b6e0f86fd082d9"
2022-10-08 04:30:12 -06:00
[[package]]
name = "httpdate"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
version = "1.0.3"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
checksum = "df3b46402a9d5adb4c86a0cf463f42e19994e3ee891101b1841f30a545cb49a9"
2022-10-08 04:30:12 -06:00
[[package]]
name = "hyper"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.14.30"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "a152ddd61dfaec7273fe8419ab357f33aee0d914c5f4efbf0d96fa749eea5ec9"
2022-10-08 04:30:12 -06:00
dependencies = [
"bytes",
"futures-channel",
"futures-core",
"futures-util",
2024-06-27 00:08:43 -06:00
"h2 0.3.26",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
"http-body 0.4.6",
2022-10-08 04:30:12 -06:00
"httparse",
"httpdate",
"itoa",
"pin-project-lite",
2023-12-22 07:46:04 -07:00
"socket2",
2022-10-08 04:30:12 -06:00
"tokio",
"tower-service",
"tracing",
"want",
]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
[[package]]
name = "hyper"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.4.1"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "50dfd22e0e76d0f662d429a5f80fcaf3855009297eab6a0a9f8543834744ba05"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
dependencies = [
"bytes",
"futures-channel",
"futures-util",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"h2 0.4.6",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 1.1.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"http-body 1.0.1",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"httparse",
"httpdate",
"itoa",
"pin-project-lite",
"smallvec",
"tokio",
2024-06-27 00:08:43 -06:00
"want",
]
[[package]]
name = "hyper-rustls"
version = "0.27.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "5ee4be2c948921a1a5320b629c4193916ed787a7f7f293fd3f7f5a6c9de74155"
dependencies = [
"futures-util",
"http 1.1.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"hyper 1.4.1",
2024-06-27 00:08:43 -06:00
"hyper-util",
"log",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"rustls 0.23.12",
2024-06-27 00:08:43 -06:00
"rustls-native-certs",
"rustls-pki-types",
"tokio",
"tokio-rustls",
"tower-service",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "hyper-timeout"
version = "0.4.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "bbb958482e8c7be4bc3cf272a766a2b0bf1a6755e7a6ae777f017a31d11b13b1"
dependencies = [
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"hyper 0.14.30",
2022-10-08 04:30:12 -06:00
"pin-project-lite",
"tokio",
"tokio-io-timeout",
]
[[package]]
name = "hyper-tls"
version = "0.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d6183ddfa99b85da61a140bea0efc93fdf56ceaa041b37d553518030827f9905"
dependencies = [
"bytes",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"hyper 0.14.30",
2022-10-08 04:30:12 -06:00
"native-tls",
"tokio",
"tokio-native-tls",
]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
[[package]]
name = "hyper-util"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.1.7"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "cde7055719c54e36e95e8719f95883f22072a48ede39db7fc17a4e1d5281e9b9"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
dependencies = [
"bytes",
2024-06-27 00:08:43 -06:00
"futures-channel",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"futures-util",
"http 1.1.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"http-body 1.0.1",
"hyper 1.4.1",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"pin-project-lite",
2024-06-27 00:08:43 -06:00
"socket2",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"tokio",
2024-06-27 00:08:43 -06:00
"tower",
"tower-service",
"tracing",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "ident_case"
version = "1.0.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b9e0384b61958566e926dc50660321d12159025e767c18e043daf26b70104c39"
[[package]]
name = "idna"
2023-11-30 07:18:15 -07:00
version = "0.5.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "634d9b1461af396cad843f47fdba5597a4f9e6ddd4bfb6ff5d85028c25cb12f6"
2022-10-08 04:30:12 -06:00
dependencies = [
"unicode-bidi",
"unicode-normalization",
]
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "image"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.25.2"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "99314c8a2152b8ddb211f924cdae532d8c5e4c8bb54728e12fff1b0cd5963a10"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
"bytemuck",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"byteorder-lite",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.1.3"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "f79afb8cbee2ef20f59ccd477a218c12a93943d075b492015ecb1bb81f8ee904"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
"byteorder-lite",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"quick-error",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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2023-07-01 11:25:41 -06:00
"hashbrown 0.12.3",
2023-07-14 08:31:48 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "2.4.0"
2023-07-14 08:31:48 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "93ead53efc7ea8ed3cfb0c79fc8023fbb782a5432b52830b6518941cebe6505c"
2023-07-14 08:31:48 -06:00
dependencies = [
"equivalent",
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
"hashbrown 0.14.5",
"serde",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "indicatif"
2024-02-16 09:50:57 -07:00
version = "0.17.8"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-02-16 09:50:57 -07:00
checksum = "763a5a8f45087d6bcea4222e7b72c291a054edf80e4ef6efd2a4979878c7bea3"
2022-10-08 04:30:12 -06:00
dependencies = [
"console",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"instant",
2023-11-30 07:18:15 -07:00
"number_prefix",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"portable-atomic",
"unicode-width",
2022-10-08 04:30:12 -06:00
]
[[package]]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "indoc"
2024-03-29 12:17:24 -06:00
version = "2.0.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-29 12:17:24 -06:00
checksum = "b248f5224d1d606005e02c97f5aa4e88eeb230488bcc03bc9ca4d7991399f2b5"
2022-10-08 04:30:12 -06:00
[[package]]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "init-tracing-opentelemetry"
version = "0.14.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "94bd26b1b737bc11f183620072e188d1c6ede67e0e78682228d66b49ec510e17"
dependencies = [
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"opentelemetry 0.20.0",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"opentelemetry-otlp",
"thiserror",
"tracing",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"tracing-opentelemetry 0.21.0",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
]
2023-02-13 05:02:45 -07:00
[[package]]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "instant"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.1.13"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "e0242819d153cba4b4b05a5a8f2a7e9bbf97b6055b2a002b395c96b5ff3c0222"
2023-02-13 05:02:45 -07:00
dependencies = [
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"cfg-if",
2023-02-13 05:02:45 -07:00
]
2022-10-08 04:30:12 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
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source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
[[package]]
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2023-11-30 07:18:15 -07:00
version = "2.9.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "8f518f335dce6725a761382244631d86cf0ccb2863413590b31338feb467f9c3"
2022-10-08 04:30:12 -06:00
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
[[package]]
name = "is_terminal_polyfill"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.70.1"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "7943c866cc5cd64cbc25b2e01621d07fa8eb2a1a23160ee81ce38704e97b8ecf"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "itertools"
version = "0.11.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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dependencies = [
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2024-02-16 09:50:57 -07:00
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dependencies = [
"either",
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[[package]]
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source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
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[[package]]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "itoa"
2024-03-29 12:17:24 -06:00
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source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-29 12:17:24 -06:00
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2022-10-08 04:30:12 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
[[package]]
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"clap 4.5.16",
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"fraction",
"getrandom",
"iso8601",
"itoa",
"memchr",
"num-cmp",
"once_cell",
"parking_lot",
"percent-encoding",
"regex",
"reqwest",
"serde",
"serde_json",
"time",
"url",
"uuid",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "lazy_static"
2024-06-27 00:08:43 -06:00
version = "1.5.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
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[[package]]
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2022-10-08 04:30:12 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
[[package]]
name = "libc"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.158"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "d8adc4bb1803a324070e64a98ae98f38934d91957a99cfb3a43dcbc01bc56439"
2023-02-13 05:02:45 -07:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "libfuzzer-sys"
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dependencies = [
"arbitrary",
"cc",
"once_cell",
]
2024-06-27 00:08:43 -06:00
[[package]]
name = "libloading"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.8.5"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "4979f22fdb869068da03c9f7528f8297c6fd2606bc3a4affe42e6a823fdb8da4"
2024-06-27 00:08:43 -06:00
dependencies = [
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"windows-targets 0.52.6",
2024-06-27 00:08:43 -06:00
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2023-11-30 07:18:15 -07:00
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2024-04-12 10:38:34 -06:00
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2024-04-12 10:38:34 -06:00
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2023-11-30 07:18:15 -07:00
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2024-06-27 00:08:43 -06:00
"bitflags 2.6.0",
2023-11-30 07:18:15 -07:00
"libc",
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
name = "link-cplusplus"
version = "1.0.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9d240c6f7e1ba3a28b0249f774e6a9dd0175054b52dfbb61b16eb8505c3785c9"
dependencies = [
"cc",
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2023-02-13 05:02:45 -07:00
[[package]]
name = "linux-raw-sys"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.4.14"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "78b3ae25bc7c8c38cec158d1f2757ee79e9b3740fbc7ccf0e59e4b08d793fa89"
2023-07-01 11:25:41 -06:00
2022-10-08 04:30:12 -06:00
[[package]]
name = "lock_api"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
version = "0.4.12"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "07af8b9cdd281b7915f413fa73f29ebd5d55d0d3f0155584dade1ff18cea1b17"
2022-10-08 04:30:12 -06:00
dependencies = [
"autocfg",
"scopeguard",
]
[[package]]
name = "log"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.4.22"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "a7a70ba024b9dc04c27ea2f0c0548feb474ec5c54bba33a7f72f873a39d07b24"
2022-10-08 04:30:12 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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dependencies = [
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2022-10-08 04:30:12 -06:00
[[package]]
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2023-11-30 07:18:15 -07:00
version = "0.2.0"
2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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[[package]]
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2023-11-30 07:18:15 -07:00
version = "0.2.0"
2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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2023-02-13 05:02:45 -07:00
[[package]]
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2023-07-14 08:31:48 -06:00
"regex-automata 0.1.10",
2023-02-13 05:02:45 -07:00
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2022-10-11 10:14:39 -06:00
[[package]]
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.7.3"
2022-10-11 10:14:39 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "0e7465ac9959cc2b1404e8e2367b43684a6d13790fe23056cc8c6c5a6b7bcb94"
2022-10-11 10:14:39 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
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2024-06-27 00:08:43 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "b4f0c8427b39666bf970460908b213ec09b3b350f20c0c2eabcbba51704a08e6"
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2024-06-27 00:08:43 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2024-06-27 00:08:43 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2024-06-27 00:08:43 -06:00
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2024-06-27 00:08:43 -06:00
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2024-06-27 00:08:43 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "f7c44f8e672c00fe5308fa235f821cb4198414e1c77935c1ab6948d3fd78550e"
dependencies = [
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feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "2.2.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "744a2b84dbd22398e347594ed2aef9d3f1b948934e3e6e94ef69ecd39d597f4b"
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
dependencies = [
"minijinja",
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
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2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
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2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
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2022-10-08 04:30:12 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
"simd-adler32",
2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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2024-03-22 11:44:05 -06:00
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2022-10-08 04:30:12 -06:00
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2024-03-22 11:44:05 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-01 11:25:41 -06:00
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2022-10-08 04:30:12 -06:00
]
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
name = "mio"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.2"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "80e04d1dcff3aae0704555fe5fee3bcfaf3d1fdf8a7e521d5b9d2b42acb52cec"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
dependencies = [
"hermit-abi 0.3.9",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"libc",
"wasi",
"windows-sys 0.52.0",
]
2024-06-27 00:08:43 -06:00
[[package]]
name = "mirai-annotations"
version = "1.12.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "c9be0862c1b3f26a88803c4a49de6889c10e608b3ee9344e6ef5b45fb37ad3d1"
[[package]]
name = "monostate"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.1.13"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "0d208407d7552cd041d8cdb69a1bc3303e029c598738177a3d87082004dc0e1e"
dependencies = [
"monostate-impl",
"serde",
]
[[package]]
name = "monostate-impl"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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2024-04-12 10:38:34 -06:00
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2022-10-08 04:30:12 -06:00
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2024-04-12 10:38:34 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-01 11:25:41 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2024-06-27 00:08:43 -06:00
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2024-06-27 00:08:43 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.4.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "35bd024e8b2ff75562e5f34e7f4905839deb4b22955ef5e73d2fea1b9813cb23"
dependencies = [
"num-bigint",
"num-complex",
"num-integer",
"num-iter",
"num-rational",
"num-traits",
]
[[package]]
name = "num-bigint"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.4.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "a5e44f723f1133c9deac646763579fdb3ac745e418f2a7af9cd0c431da1f20b9"
dependencies = [
"num-integer",
"num-traits",
]
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[[package]]
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.4.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "73f88a1307638156682bada9d7604135552957b7818057dcef22705b4d509495"
dependencies = [
"num-traits",
]
2024-02-16 09:50:57 -07:00
[[package]]
name = "num-conv"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "num-derive"
version = "0.4.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ed3955f1a9c7c0c15e092f9c887db08b1fc683305fdf6eb6684f22555355e202"
dependencies = [
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
]
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dependencies = [
"num-traits",
]
[[package]]
name = "num-iter"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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]
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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dependencies = [
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]
[[package]]
name = "num-traits"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-01 11:25:41 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-01 11:25:41 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-14 08:31:48 -06:00
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2024-02-16 09:50:57 -07:00
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2023-07-14 08:31:48 -06:00
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2024-02-16 09:50:57 -07:00
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2023-07-14 08:31:48 -06:00
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2022-10-08 04:30:12 -06:00
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2023-07-01 11:25:41 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2023-07-01 11:25:41 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2023-07-01 11:25:41 -06:00
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2022-10-08 04:30:12 -06:00
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2023-12-11 06:55:03 -07:00
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2023-12-11 06:55:03 -07:00
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2022-10-08 04:30:12 -06:00
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2023-07-01 11:25:41 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2022-10-08 04:30:12 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
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2022-10-08 04:30:12 -06:00
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name = "openssl-macros"
2023-04-11 12:32:18 -06:00
version = "0.1.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-04-11 12:32:18 -06:00
checksum = "a948666b637a0f465e8564c73e89d4dde00d72d4d473cc972f390fc3dcee7d9c"
2022-10-08 04:30:12 -06:00
dependencies = [
"proc-macro2",
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "openssl-probe"
version = "0.1.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ff011a302c396a5197692431fc1948019154afc178baf7d8e37367442a4601cf"
[[package]]
name = "openssl-sys"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.9.103"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "7f9e8deee91df40a943c71b917e5874b951d32a802526c85721ce3b776c929d6"
2022-10-08 04:30:12 -06:00
dependencies = [
"cc",
"libc",
"pkg-config",
"vcpkg",
]
2023-02-13 05:02:45 -07:00
[[package]]
name = "opentelemetry"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.20.0"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "9591d937bc0e6d2feb6f71a559540ab300ea49955229c347a517a28d27784c54"
2023-02-13 05:02:45 -07:00
dependencies = [
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"opentelemetry_api",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"opentelemetry_sdk 0.20.0",
2023-07-01 11:25:41 -06:00
]
[[package]]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
name = "opentelemetry"
version = "0.21.0"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "1e32339a5dc40459130b3bd269e9892439f55b33e772d2a9d402a789baaf4e8a"
2023-07-01 11:25:41 -06:00
dependencies = [
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"futures-core",
"futures-sink",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"indexmap 2.4.0",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"js-sys",
"once_cell",
"pin-project-lite",
"thiserror",
"urlencoding",
2023-02-13 05:02:45 -07:00
]
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
name = "opentelemetry"
version = "0.23.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1b69a91d4893e713e06f724597ad630f1fa76057a5e1026c0ca67054a9032a76"
dependencies = [
"futures-core",
"futures-sink",
"js-sys",
"once_cell",
"pin-project-lite",
"thiserror",
]
2023-02-13 05:02:45 -07:00
[[package]]
name = "opentelemetry-otlp"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.13.0"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "7e5e5a5c4135864099f3faafbe939eb4d7f9b80ebf68a8448da961b32a7c1275"
2023-02-13 05:02:45 -07:00
dependencies = [
"async-trait",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"futures-core",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
2023-02-13 05:02:45 -07:00
"opentelemetry-proto",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"opentelemetry-semantic-conventions",
"opentelemetry_api",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"opentelemetry_sdk 0.20.0",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"prost 0.11.9",
2023-02-13 05:02:45 -07:00
"thiserror",
"tokio",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"tonic 0.9.2",
2023-02-13 05:02:45 -07:00
]
[[package]]
name = "opentelemetry-proto"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.3.0"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "b1e3f814aa9f8c905d0ee4bde026afd3b2577a97c10e1699912e3e44f0c4cbeb"
2023-02-13 05:02:45 -07:00
dependencies = [
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"opentelemetry_api",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"opentelemetry_sdk 0.20.0",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"prost 0.11.9",
"tonic 0.9.2",
2023-02-13 05:02:45 -07:00
]
[[package]]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "opentelemetry-semantic-conventions"
version = "0.12.0"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "73c9f9340ad135068800e7f1b24e9e09ed9e7143f5bf8518ded3d3ec69789269"
2023-02-13 05:02:45 -07:00
dependencies = [
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"opentelemetry 0.20.0",
2023-02-13 05:02:45 -07:00
]
2023-07-01 11:25:41 -06:00
[[package]]
name = "opentelemetry_api"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.20.0"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "8a81f725323db1b1206ca3da8bb19874bbd3f57c3bcd59471bfb04525b265b9b"
2023-07-01 11:25:41 -06:00
dependencies = [
"futures-channel",
"futures-util",
2023-07-14 08:31:48 -06:00
"indexmap 1.9.3",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"js-sys",
2023-07-01 11:25:41 -06:00
"once_cell",
"pin-project-lite",
"thiserror",
"urlencoding",
]
2023-02-13 05:02:45 -07:00
[[package]]
name = "opentelemetry_sdk"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.20.0"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "fa8e705a0612d48139799fcbaba0d4a90f06277153e43dd2bdc16c6f0edd8026"
2023-02-13 05:02:45 -07:00
dependencies = [
"async-trait",
"crossbeam-channel",
"futures-channel",
"futures-executor",
"futures-util",
"once_cell",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"opentelemetry_api",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"ordered-float 3.9.2",
2023-07-01 11:25:41 -06:00
"percent-encoding",
"rand",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"regex",
"serde_json",
2023-07-01 11:25:41 -06:00
"thiserror",
"tokio",
"tokio-stream",
]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
[[package]]
name = "opentelemetry_sdk"
version = "0.21.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "2f16aec8a98a457a52664d69e0091bac3a0abd18ead9b641cb00202ba4e0efe4"
dependencies = [
"async-trait",
"crossbeam-channel",
"futures-channel",
"futures-executor",
"futures-util",
"glob",
"once_cell",
"opentelemetry 0.21.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"ordered-float 4.2.2",
"percent-encoding",
"rand",
"thiserror",
]
[[package]]
name = "opentelemetry_sdk"
version = "0.23.0"
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checksum = "ae312d58eaa90a82d2e627fd86e075cf5230b3f11794e2ed74199ebbe572d4fd"
dependencies = [
"async-trait",
"futures-channel",
"futures-executor",
"futures-util",
"glob",
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"once_cell",
"opentelemetry 0.23.0",
"ordered-float 4.2.2",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"percent-encoding",
"rand",
"thiserror",
]
2023-07-01 11:25:41 -06:00
[[package]]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "option-ext"
version = "0.2.0"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "04744f49eae99ab78e0d5c0b603ab218f515ea8cfe5a456d7629ad883a3b6e7d"
[[package]]
name = "ordered-float"
2023-11-30 07:18:15 -07:00
version = "3.9.2"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "f1e1c390732d15f1d48471625cd92d154e66db2c56645e29a9cd26f4699f72dc"
2023-07-01 11:25:41 -06:00
dependencies = [
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"num-traits",
2023-02-13 05:02:45 -07:00
]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
[[package]]
name = "ordered-float"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "4.2.2"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "4a91171844676f8c7990ce64959210cd2eaef32c2612c50f9fae9f8aaa6065a6"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
dependencies = [
"num-traits",
]
2022-10-18 07:19:03 -06:00
[[package]]
name = "overload"
version = "0.1.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b15813163c1d831bf4a13c3610c05c0d03b39feb07f7e09fa234dac9b15aaf39"
[[package]]
name = "papergrid"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.10.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "a2ccbe15f2b6db62f9a9871642746427e297b0ceb85f9a7f1ee5ff47d184d0c8"
dependencies = [
"bytecount",
"fnv",
"unicode-width",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "parking_lot"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.12.3"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "f1bf18183cf54e8d6059647fc3063646a1801cf30896933ec2311622cc4b9a27"
2022-10-08 04:30:12 -06:00
dependencies = [
"lock_api",
"parking_lot_core",
]
[[package]]
name = "parking_lot_core"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
version = "0.9.10"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "1e401f977ab385c9e4e3ab30627d6f26d00e2c73eef317493c4ec6d468726cf8"
2022-10-08 04:30:12 -06:00
dependencies = [
"cfg-if",
"libc",
2023-11-30 07:18:15 -07:00
"redox_syscall",
2022-10-08 04:30:12 -06:00
"smallvec",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"windows-targets 0.52.6",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "paste"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "1.0.15"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2022-10-08 04:30:12 -06:00
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name = "percent-encoding"
2023-11-30 07:18:15 -07:00
version = "2.3.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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2024-03-22 11:44:05 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "da544ee218f0d287a911e9c99a39a8c9bc8fcad3cb8db5959940044ecfc67265"
2023-11-30 07:18:15 -07:00
[[package]]
name = "powerfmt"
version = "0.2.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "439ee305def115ba05938db6eb1644ff94165c5ab5e9420d1c1bcedbba909391"
2022-10-08 04:30:12 -06:00
[[package]]
name = "ppv-lite86"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.20"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "77957b295656769bb8ad2b6a6b09d897d94f05c41b069aede1fcdaa675eaea04"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
dependencies = [
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"zerocopy",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
]
2022-10-08 04:30:12 -06:00
2023-02-13 05:02:45 -07:00
[[package]]
name = "prettyplease"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.22"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "479cf940fbbb3426c32c5d5176f62ad57549a0bb84773423ba8be9d089f5faba"
2023-02-13 05:02:45 -07:00
dependencies = [
"proc-macro2",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2023-02-13 05:02:45 -07:00
]
2022-10-17 10:27:33 -06:00
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"proc-macro2",
"quote",
"syn 1.0.109",
2022-10-17 10:27:33 -06:00
"version_check",
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dependencies = [
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"quote",
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2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
version = "1.0.86"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
checksum = "5e719e8df665df0d1c8fbfd238015744736151d4445ec0836b8e628aae103b77"
2022-10-08 04:30:12 -06:00
dependencies = [
"unicode-ident",
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "profiling"
version = "1.0.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "43d84d1d7a6ac92673717f9f6d1518374ef257669c24ebc5ac25d5033828be58"
dependencies = [
"profiling-procmacros",
]
[[package]]
name = "profiling-procmacros"
version = "1.0.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "8021cf59c8ec9c432cfc2526ac6b8aa508ecaf29cd415f271b8406c1b851c3fd"
dependencies = [
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "prost"
version = "0.11.9"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0b82eaa1d779e9a4bc1c3217db8ffbeabaae1dca241bf70183242128d48681cd"
2022-10-08 04:30:12 -06:00
dependencies = [
"bytes",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"prost-derive 0.11.9",
]
[[package]]
name = "prost"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.12.6"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "deb1435c188b76130da55f17a466d252ff7b1418b2ad3e037d127b94e3411f29"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
dependencies = [
"bytes",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"prost-derive 0.12.6",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "prost-build"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.12.6"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "22505a5c94da8e3b7c2996394d1c933236c4d743e81a410bcca4e6989fc066a4"
2022-10-08 04:30:12 -06:00
dependencies = [
"bytes",
2024-04-12 10:38:34 -06:00
"heck 0.5.0",
"itertools 0.12.1",
2022-10-08 04:30:12 -06:00
"log",
"multimap",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"once_cell",
2022-10-08 04:30:12 -06:00
"petgraph",
2023-02-13 05:02:45 -07:00
"prettyplease",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"prost 0.12.6",
2022-10-08 04:30:12 -06:00
"prost-types",
"regex",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
"tempfile",
]
[[package]]
name = "prost-derive"
version = "0.11.9"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e5d2d8d10f3c6ded6da8b05b5fb3b8a5082514344d56c9f871412d29b4e075b4"
2022-10-08 04:30:12 -06:00
dependencies = [
"anyhow",
"itertools 0.10.5",
"proc-macro2",
"quote",
"syn 1.0.109",
2022-10-08 04:30:12 -06:00
]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
[[package]]
name = "prost-derive"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.12.6"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "81bddcdb20abf9501610992b6759a4c888aef7d1a7247ef75e2404275ac24af1"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
dependencies = [
"anyhow",
2024-04-12 10:38:34 -06:00
"itertools 0.12.1",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "prost-types"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.12.6"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "9091c90b0a32608e984ff2fa4091273cbdd755d54935c51d520887f4a1dbd5b0"
2022-10-08 04:30:12 -06:00
dependencies = [
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"prost 0.12.6",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "pyo3"
version = "0.22.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "831e8e819a138c36e212f3af3fd9eeffed6bf1510a805af35b0edee5ffa59433"
dependencies = [
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2024-06-27 00:08:43 -06:00
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2024-06-27 00:08:43 -06:00
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2023-07-01 11:25:41 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2024-06-27 00:08:43 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "a8f0bfd976333248de2078d350bfdf182ff96e168a24d23d2436cef320dd4bdd"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "cb9ee317cfe3fbd54b36a511efc1edd42e216903c9cd575e686dd68a2ba90d8d"
dependencies = [
2024-06-27 00:08:43 -06:00
"bitflags 2.6.0",
]
2022-10-08 04:30:12 -06:00
[[package]]
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2024-03-29 12:17:24 -06:00
version = "1.10.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-29 12:17:24 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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[[package]]
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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[[package]]
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2024-01-26 11:04:57 -07:00
version = "1.12.1"
2022-10-08 04:30:12 -06:00
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2024-01-26 11:04:57 -07:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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[[package]]
name = "redox_syscall"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.5.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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dependencies = [
2024-06-27 00:08:43 -06:00
"bitflags 2.6.0",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "redox_users"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.4.6"
2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
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2022-10-08 04:30:12 -06:00
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2023-02-13 05:02:45 -07:00
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2023-02-13 05:02:45 -07:00
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2023-07-14 08:31:48 -06:00
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2024-06-27 00:08:43 -06:00
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2023-07-14 08:31:48 -06:00
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2024-06-27 00:08:43 -06:00
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2023-07-14 08:31:48 -06:00
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2023-11-30 07:18:15 -07:00
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2023-07-14 08:31:48 -06:00
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2024-06-27 00:08:43 -06:00
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2023-07-14 08:31:48 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
2023-11-30 07:18:15 -07:00
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2024-06-27 00:08:43 -06:00
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2023-11-30 07:18:15 -07:00
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2024-06-27 00:08:43 -06:00
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2024-03-22 11:44:05 -06:00
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2022-10-08 04:30:12 -06:00
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2024-03-22 11:44:05 -06:00
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2022-10-08 04:30:12 -06:00
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2024-01-26 11:04:57 -07:00
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2022-10-08 04:30:12 -06:00
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2024-06-27 00:08:43 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"hyper 0.14.30",
2022-10-08 04:30:12 -06:00
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"pin-project-lite",
2024-06-27 00:08:43 -06:00
"rustls-pemfile 1.0.4",
2022-10-08 04:30:12 -06:00
"serde",
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"sync_wrapper 0.1.2",
2023-11-30 07:18:15 -07:00
"system-configuration",
2022-10-08 04:30:12 -06:00
"tokio",
"tokio-native-tls",
"tower-service",
"url",
"wasm-bindgen",
"wasm-bindgen-futures",
"web-sys",
"winreg",
]
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "rgb"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.8.48"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "0f86ae463694029097b846d8f99fd5536740602ae00022c0c50c5600720b2f71"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2023-11-30 07:18:15 -07:00
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2023-11-30 07:18:15 -07:00
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2024-02-21 06:50:57 -07:00
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2023-11-30 07:18:15 -07:00
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2024-02-21 06:50:57 -07:00
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2023-11-30 07:18:15 -07:00
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2024-02-21 06:50:57 -07:00
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2023-11-30 07:18:15 -07:00
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2024-02-21 06:50:57 -07:00
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2023-11-30 07:18:15 -07:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "fa66af4a4fdd5e7ebc276f115e895611a34739a9c1c01028383d612d550953c0"
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "8.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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dependencies = [
"sha2",
"walkdir",
]
2023-07-01 11:25:41 -06:00
[[package]]
name = "rustc-demangle"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.1.24"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "719b953e2095829ee67db738b3bfa9fa368c94900df327b3f07fe6e794d2fe1f"
2023-07-01 11:25:41 -06:00
2024-06-27 00:08:43 -06:00
[[package]]
name = "rustc-hash"
version = "1.1.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "08d43f7aa6b08d49f382cde6a7982047c3426db949b1424bc4b7ec9ae12c6ce2"
2023-05-02 07:43:19 -06:00
[[package]]
name = "rustc_version"
version = "0.4.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "bfa0f585226d2e68097d4f95d113b15b83a82e819ab25717ec0590d9584ef366"
dependencies = [
"semver",
]
2023-02-13 05:02:45 -07:00
[[package]]
name = "rustix"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
version = "0.38.34"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "70dc5ec042f7a43c4a73241207cecc9873a06d45debb38b329f8541d85c2730f"
2023-07-01 11:25:41 -06:00
dependencies = [
2024-06-27 00:08:43 -06:00
"bitflags 2.6.0",
2023-07-01 11:25:41 -06:00
"errno",
"libc",
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
"linux-raw-sys",
2023-12-11 04:46:30 -07:00
"windows-sys 0.52.0",
2023-02-13 05:02:45 -07:00
]
[[package]]
name = "rustls"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.20.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "1b80e3dec595989ea8510028f30c408a4630db12c9cbb8de34203b89d6577e99"
dependencies = [
"log",
2023-11-30 07:18:15 -07:00
"ring 0.16.20",
"sct",
"webpki",
]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
[[package]]
name = "rustls"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
version = "0.22.4"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "bf4ef73721ac7bcd79b2b315da7779d8fc09718c6b3d2d1b2d94850eb8c18432"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
dependencies = [
"log",
2024-02-21 06:50:57 -07:00
"ring 0.17.8",
2024-02-16 09:50:57 -07:00
"rustls-pki-types",
2023-11-30 07:18:15 -07:00
"rustls-webpki",
2024-02-16 09:50:57 -07:00
"subtle",
"zeroize",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
]
2024-06-27 00:08:43 -06:00
[[package]]
name = "rustls"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.23.12"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "c58f8c84392efc0a126acce10fa59ff7b3d2ac06ab451a33f2741989b806b044"
2024-06-27 00:08:43 -06:00
dependencies = [
"aws-lc-rs",
"log",
"once_cell",
"rustls-pki-types",
"rustls-webpki",
"subtle",
"zeroize",
]
[[package]]
name = "rustls-native-certs"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.7.2"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "04182dffc9091a404e0fc069ea5cd60e5b866c3adf881eff99a32d048242dffa"
2024-06-27 00:08:43 -06:00
dependencies = [
"openssl-probe",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"rustls-pemfile 2.1.3",
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"rustls-pki-types",
"schannel",
"security-framework",
]
[[package]]
name = "rustls-pemfile"
2023-11-30 07:18:15 -07:00
version = "1.0.4"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "1c74cae0a4cf6ccbbf5f359f08efdf8ee7e1dc532573bf0db71968cb56b1448c"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
dependencies = [
2024-01-26 11:04:57 -07:00
"base64 0.21.7",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
]
2024-06-27 00:08:43 -06:00
[[package]]
name = "rustls-pemfile"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "2.1.3"
2024-06-27 00:08:43 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "196fe16b00e106300d3e45ecfcb764fa292a535d7326a29a5875c579c7417425"
2024-06-27 00:08:43 -06:00
dependencies = [
"base64 0.22.1",
"rustls-pki-types",
]
2024-02-16 09:50:57 -07:00
[[package]]
name = "rustls-pki-types"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.8.0"
2024-02-16 09:50:57 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "fc0a2ce646f8655401bb81e7927b812614bd5d91dbc968696be50603510fcaf0"
2024-02-16 09:50:57 -07:00
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
[[package]]
name = "rustls-webpki"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.102.7"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "84678086bd54edf2b415183ed7a94d0efb049f1b646a33e22a36f3794be6ae56"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
dependencies = [
2024-06-27 00:08:43 -06:00
"aws-lc-rs",
2024-02-21 06:50:57 -07:00
"ring 0.17.8",
2024-02-16 09:50:57 -07:00
"rustls-pki-types",
2023-11-30 07:18:15 -07:00
"untrusted 0.9.0",
]
[[package]]
name = "rustversion"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "1.0.17"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "955d28af4278de8121b7ebeb796b6a45735dc01436d898801014aced2773a3d6"
2022-10-08 04:30:12 -06:00
[[package]]
name = "ryu"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "1.0.18"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "f3cb5ba0dc43242ce17de99c180e96db90b235b8a9fdc9543c96d2209116bd9f"
2022-10-08 04:30:12 -06:00
[[package]]
name = "same-file"
version = "1.0.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "93fc1dc3aaa9bfed95e02e6eadabb4baf7e3078b0bd1b4d7b6b0b68378900502"
dependencies = [
"winapi-util",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "schannel"
2024-01-26 11:04:57 -07:00
version = "0.1.23"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-01-26 11:04:57 -07:00
checksum = "fbc91545643bcf3a0bbb6569265615222618bdf33ce4ffbbd13c4bbd4c093534"
2022-10-08 04:30:12 -06:00
dependencies = [
2024-01-26 11:04:57 -07:00
"windows-sys 0.52.0",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "scopeguard"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
version = "1.2.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
checksum = "94143f37725109f92c262ed2cf5e59bce7498c01bcc1502d7b9afe439a4e9f49"
2022-10-08 04:30:12 -06:00
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
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source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "a3cf7c11c38cb994f3d40e8a8cde3bbd1f72a435e4c49e85d6553d8312306152"
[[package]]
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2023-11-30 07:18:15 -07:00
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2023-11-30 07:18:15 -07:00
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dependencies = [
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"ring 0.17.8",
2023-11-30 07:18:15 -07:00
"untrusted 0.9.0",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "security-framework"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "2.11.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "897b2245f0b511c87893af39b033e5ca9cce68824c4d7e7630b5a1d339658d02"
2022-10-08 04:30:12 -06:00
dependencies = [
2024-06-27 00:08:43 -06:00
"bitflags 2.6.0",
2022-10-08 04:30:12 -06:00
"core-foundation",
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"libc",
"security-framework-sys",
]
[[package]]
name = "security-framework-sys"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "2.11.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "75da29fe9b9b08fe9d6b22b5b4bcbc75d8db3aa31e639aa56bb62e9d46bfceaf"
2022-10-08 04:30:12 -06:00
dependencies = [
"core-foundation-sys",
"libc",
]
2023-05-02 07:43:19 -06:00
[[package]]
name = "semver"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "1.0.23"
2023-05-02 07:43:19 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
2024-01-26 11:04:57 -07:00
dependencies = [
"serde",
]
2023-05-02 07:43:19 -06:00
2022-10-08 04:30:12 -06:00
[[package]]
name = "serde"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.209"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "99fce0ffe7310761ca6bf9faf5115afbc19688edd00171d81b1bb1b116c63e09"
2022-10-08 04:30:12 -06:00
dependencies = [
"serde_derive",
]
[[package]]
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source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "2bef2ebfde456fb76bbcf9f59315333decc4fda0b2b44b420243c11e0f5ec1f5"
dependencies = [
"half 1.8.3",
"serde",
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2022-10-08 04:30:12 -06:00
[[package]]
name = "serde_derive"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.209"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "a5831b979fd7b5439637af1752d535ff49f4860c0f341d1baeb6faf0f4242170"
2022-10-08 04:30:12 -06:00
dependencies = [
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "serde_json"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.0.127"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "8043c06d9f82bd7271361ed64f415fe5e12a77fdb52e573e7f06a516dea329ad"
2022-10-08 04:30:12 -06:00
dependencies = [
"itoa",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"memchr",
2022-10-08 04:30:12 -06:00
"ryu",
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[[package]]
name = "serde_path_to_error"
2024-03-22 11:44:05 -06:00
version = "0.1.16"
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-22 11:44:05 -06:00
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2023-07-14 08:31:48 -06:00
"itoa",
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]
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.6.7"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.10.8"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "793db75ad2bcafc3ffa7c68b215fee268f537982cd901d132f89c6343f3a3dc8"
2022-10-08 04:30:12 -06:00
dependencies = [
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[[package]]
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2023-11-30 07:18:15 -07:00
version = "0.1.7"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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2024-06-27 00:08:43 -06:00
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[[package]]
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Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
version = "0.3.17"
source = "registry+https://github.com/rust-lang/crates.io-index"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
checksum = "8621587d4798caf8eb44879d42e56b9a93ea5dcd315a6487c357130095b62801"
dependencies = [
"libc",
"signal-hook-registry",
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[[package]]
name = "signal-hook-mio"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"mio 0.8.11",
"signal-hook",
]
2022-10-18 07:19:03 -06:00
[[package]]
name = "signal-hook-registry"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
version = "1.4.2"
2022-10-18 07:19:03 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "a9e9e0b4211b72e7b8b6e85c807d36c212bdb33ea8587f7569562a84df5465b1"
2022-10-18 07:19:03 -06:00
dependencies = [
"libc",
]
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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version = "0.3.7"
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dependencies = [
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[[package]]
name = "sketches-ddsketch"
2024-02-16 09:50:57 -07:00
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source = "registry+https://github.com/rust-lang/crates.io-index"
2024-02-16 09:50:57 -07:00
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2022-10-08 04:30:12 -06:00
[[package]]
name = "slab"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.4.9"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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]
[[package]]
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2023-12-11 04:46:30 -07:00
version = "1.0.7"
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-12-11 04:46:30 -07:00
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dependencies = [
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]
2022-10-08 04:30:12 -06:00
[[package]]
name = "smallvec"
2024-03-22 11:44:05 -06:00
version = "1.13.2"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-22 11:44:05 -06:00
checksum = "3c5e1a9a646d36c3599cd173a41282daf47c44583ad367b8e6837255952e5c67"
2022-10-08 04:30:12 -06:00
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
[[package]]
name = "socket2"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
version = "0.5.7"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "ce305eb0b4296696835b71df73eb912e0f1ffd2556a501fcede6e0c50349191c"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
dependencies = [
"libc",
2024-02-28 08:12:14 -07:00
"windows-sys 0.52.0",
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
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2023-11-30 07:18:15 -07:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2023-11-30 07:18:15 -07:00
2022-10-08 04:30:12 -06:00
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2023-02-13 05:02:45 -07:00
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2022-10-08 04:30:12 -06:00
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2024-02-16 09:50:57 -07:00
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2024-02-16 09:50:57 -07:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2023-11-30 07:18:15 -07:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "23dc1fa9ac9c169a78ba62f0b841814b7abae11bdd047b9c58f893439e309ea0"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
dependencies = [
2024-03-22 11:44:05 -06:00
"heck 0.4.1",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"proc-macro2",
"quote",
"rustversion",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2024-02-16 09:50:57 -07:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "578e081a14e0cefc3279b0472138c513f37b41a08d5a3cca9b6e4e8ceb6cd525"
dependencies = [
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2022-10-11 10:14:39 -06:00
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2023-02-13 05:02:45 -07:00
version = "0.1.2"
2022-10-11 10:14:39 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-02-13 05:02:45 -07:00
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2022-10-11 10:14:39 -06:00
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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2023-05-02 07:43:19 -06:00
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2023-05-02 07:43:19 -06:00
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2023-05-02 07:43:19 -06:00
dependencies = [
"cfg-if",
"core-foundation-sys",
"libc",
"ntapi",
"once_cell",
"rayon",
2024-01-26 11:04:57 -07:00
"windows",
2023-05-02 07:43:19 -06:00
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2023-11-30 07:18:15 -07:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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dependencies = [
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"pkg-config",
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"version-compare",
]
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name = "tabled"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.14.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "dfe9c3632da101aba5131ed63f9eed38665f8b3c68703a6bb18124835c1a5d22"
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2024-03-22 11:44:05 -06:00
"heck 0.4.1",
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "target-lexicon"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
2022-10-08 04:30:12 -06:00
[[package]]
name = "tempfile"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "3.12.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "04cbcdd0c794ebb0d4cf35e88edd2f7d2c4c3e9a5a6dab322839b321c6a87a64"
2022-10-08 04:30:12 -06:00
dependencies = [
"cfg-if",
"fastrand",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"once_cell",
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
"rustix",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"windows-sys 0.59.0",
2022-10-17 10:27:33 -06:00
]
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
name = "termcolor"
version = "1.4.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "06794f8f6c5c898b3275aebefa6b8a1cb24cd2c6c79397ab15774837a0bc5755"
dependencies = [
"winapi-util",
]
[[package]]
name = "text-generation-backends-trtllm"
version = "2.2.1-dev0"
dependencies = [
"async-stream",
"async-trait",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"clap 4.5.16",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"cmake",
"cxx",
"cxx-build",
"log",
"parking_lot",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"pkg-config",
"text-generation-router",
"thiserror",
"tokenizers 0.19.1",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"tokio",
"tokio-stream",
"tracing",
"tracing-opentelemetry 0.24.0",
"tracing-subscriber",
]
[[package]]
name = "text-generation-benchmark"
version = "2.2.1-dev0"
dependencies = [
"average",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"clap 4.5.16",
"crossterm",
"float-ord",
2023-11-30 07:18:15 -07:00
"hf-hub",
"ratatui",
"serde",
"serde_json",
"tabled",
"text-generation-client",
"thiserror",
"tokenizers 0.20.0",
"tokio",
"tracing",
"tracing-subscriber",
]
[[package]]
name = "text-generation-client"
version = "2.2.1-dev0"
dependencies = [
"async-trait",
"base64 0.22.1",
"futures",
2023-02-13 05:02:45 -07:00
"grpc-metadata",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"prost 0.12.6",
2023-02-13 05:02:45 -07:00
"prost-build",
"thiserror",
"tokio",
2023-11-30 07:18:15 -07:00
"tonic 0.10.2",
"tonic-build",
"tower",
"tracing",
]
2022-10-18 07:19:03 -06:00
[[package]]
name = "text-generation-launcher"
version = "2.2.1-dev0"
2022-10-18 07:19:03 -06:00
dependencies = [
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"clap 4.5.16",
2022-10-18 07:19:03 -06:00
"ctrlc",
"float_eq",
Improve the defaults for the launcher (#1727) # What does this PR do? - Renamed `max_input_length` into `max_input_tokens` for consistency (backward compatible change, will yell if both are set.) - Will now use the config for `max_input_tokens` `max_total_token` and `max_batch_total_tokens`. - Capping the values to 16k in order to save VRAM on behalf of users (overriddable by simply setting the values). <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-12 06:20:31 -06:00
"hf-hub",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"nix 0.28.0",
Improve the defaults for the launcher (#1727) # What does this PR do? - Renamed `max_input_length` into `max_input_tokens` for consistency (backward compatible change, will yell if both are set.) - Will now use the config for `max_input_tokens` `max_total_token` and `max_batch_total_tokens`. - Capping the values to 16k in order to save VRAM on behalf of users (overriddable by simply setting the values). <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-12 06:20:31 -06:00
"once_cell",
"reqwest",
"serde",
"serde_json",
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
"thiserror",
2022-10-18 07:19:03 -06:00
"tracing",
"tracing-subscriber",
2023-05-02 07:43:19 -06:00
"vergen",
2022-10-18 07:19:03 -06:00
]
2022-10-17 06:59:00 -06:00
[[package]]
name = "text-generation-router"
version = "2.2.1-dev0"
2022-10-17 06:59:00 -06:00
dependencies = [
"async-stream",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"async-trait",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"axum 0.7.5",
2023-02-13 05:02:45 -07:00
"axum-tracing-opentelemetry",
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
"base64 0.22.1",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"clap 4.5.16",
"csv",
2022-10-17 06:59:00 -06:00
"futures",
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
"futures-util",
2023-11-30 07:18:15 -07:00
"hf-hub",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
"image",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"init-tracing-opentelemetry",
"itertools 0.10.5",
"jsonschema",
"metrics",
"metrics-exporter-prometheus",
feat: supports openai chat completions API (#1427) This PR adds support to make TGI a drop in replacement for OpenAI clients by exposing the same HTTP interface. Notes - TGI inits a single model at startup so the `model` field is unused in HTTP requests. - `max_tokens` and `stream` should work as expected but other params may be (unimplemented or not supported) General approach - fetch the `tokenizer_config` at startup from the hub - pass `tokenizer_config` into `Infer` so we have it at request time - use the `chat_template` on the config to format chat request - parse jinja template and render chat string - pass inputs into existing generate function - wrap generation output in expected structure before returning # How to test ### Streaming curl ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "tgi", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": true, "max_tokens": 20 }' \ -H 'Content-Type: application/json' ``` It is also possible to use the `openai` python library and change the base url ### 🌊 STREAMING REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=True ) # iterate and print stream for message in chat_completion: print(message) # ChatCompletionChunk(id='', choices=[Choice(delta=ChoiceDelta(content=' that', function_call=None, role='assistant', tool_calls=None), finish_reason=None, index=2, logprobs=None)], created=1704486761, model='', object='text_completion', system_fingerprint='') ``` ### 🚗 SYNCHRONOUS REQUEST ```python from openai import OpenAI # init the client but point it to TGI client = OpenAI( base_url="http://localhost:3000/v1", api_key="not needed for a local LLM" ) chat_completion = client.chat.completions.create( model="tgi", messages=[ {"role": "system", "content": "You are a helpful assistant." }, {"role": "user", "content": "What is deep learning?"} ], stream=False ) print(chat_completion) # ChatCompletion(id='', choices=[Choice(finish_reason=None, index=0, logprobs=None, message=ChatCompletionMessage(content='\nDeep learning is a new field of research that has been gaining traction in the last ...', role='assistant', function_call=None, tool_calls=None))], created=1704486762, model='', object='text_completion', system_fingerprint='', usage=CompletionUsage(completion_tokens=100, prompt_tokens=76, total_tokens=176)) ``` ## How to run dev ```bash cd text-generation-inference/server MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 text-generation-server serve --trust-remote-code gpt2 ``` ***note many of the existing `chat_templates` use non standard `jinja` (ie. adding a `raise` to the template) which will throw an error when parsing; hence using `upstage/SOLAR-10.7B-Instruct-v1.0` since it has a valid template ```bash cd text-generation-inference/router cargo run -- --tokenizer-name upstage/SOLAR-10.7B-Instruct-v1.0 ``` trigger ```bash curl localhost:3000/v1/chat/completions \ -X POST \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is the IP address of the Google DNS servers?" } ], "stream": true, "max_tokens": 20, "logprobs": true }' \ -H 'Content-Type: application/json' ``` ^ supports `stream: true` and `stream: false` requests
2024-01-16 03:07:41 -07:00
"minijinja",
"minijinja-contrib",
"ngrok",
"nohash-hasher",
"once_cell",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"opentelemetry 0.20.0",
2023-02-13 05:02:45 -07:00
"opentelemetry-otlp",
"pyo3",
"rand",
"regex",
"reqwest",
2022-10-17 06:59:00 -06:00
"serde",
"serde_json",
"sysinfo",
2022-10-17 06:59:00 -06:00
"thiserror",
"tokenizers 0.20.0",
2022-10-17 06:59:00 -06:00
"tokio",
2023-10-23 07:51:12 -06:00
"tokio-stream",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"tower-http",
2022-10-17 06:59:00 -06:00
"tracing",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"tracing-opentelemetry 0.21.0",
2022-10-17 06:59:00 -06:00
"tracing-subscriber",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"ureq",
"utoipa",
"utoipa-swagger-ui",
"uuid",
"vergen",
2022-10-17 06:59:00 -06:00
]
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
name = "text-generation-router-v3"
version = "2.2.1-dev0"
dependencies = [
"async-stream",
"async-trait",
"axum 0.7.5",
"axum-tracing-opentelemetry",
"base64 0.22.1",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"clap 4.5.16",
"criterion",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"futures",
"futures-util",
"grpc-metadata",
"hf-hub",
"image",
"init-tracing-opentelemetry",
"itertools 0.13.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"jsonschema",
"metrics",
"metrics-exporter-prometheus",
"minijinja",
"minijinja-contrib",
"nohash-hasher",
"once_cell",
"opentelemetry 0.20.0",
"opentelemetry-otlp",
"prost 0.12.6",
"prost-build",
"rand",
"regex",
"reqwest",
"serde",
"serde_json",
"slotmap",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"text-generation-router",
"thiserror",
"tokenizers 0.20.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"tokio",
"tokio-stream",
"tonic 0.10.2",
"tonic-build",
"tower",
"tower-http",
"tracing",
"tracing-opentelemetry 0.21.0",
"tracing-subscriber",
"utoipa",
"utoipa-swagger-ui",
]
[[package]]
name = "textwrap"
version = "0.11.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d326610f408c7a4eb6f51c37c330e496b08506c9457c9d34287ecc38809fb060"
dependencies = [
"unicode-width",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "thiserror"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.0.63"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2022-10-08 04:30:12 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.0.63"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "a4558b58466b9ad7ca0f102865eccc95938dca1a74a856f2b57b6629050da261"
2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-08 04:30:12 -06:00
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2024-02-21 06:50:57 -07:00
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2022-10-08 04:30:12 -06:00
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2024-02-21 06:50:57 -07:00
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2022-10-08 04:30:12 -06:00
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2023-02-13 05:02:45 -07:00
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2022-10-08 04:30:12 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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2024-04-12 10:38:34 -06:00
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2022-10-08 04:30:12 -06:00
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2024-04-12 10:38:34 -06:00
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2022-10-08 04:30:12 -06:00
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Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
"deranged",
"itoa",
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"libc",
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2023-07-14 08:31:48 -06:00
"num_threads",
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"powerfmt",
"serde",
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.1.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2022-10-08 04:30:12 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "1.8.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "445e881f4f6d382d5f27c034e25eb92edd7c784ceab92a0937db7f2e9471b938"
2022-10-08 04:30:12 -06:00
dependencies = [
"tinyvec_macros",
]
[[package]]
name = "tinyvec_macros"
2023-02-13 05:02:45 -07:00
version = "0.1.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-02-13 05:02:45 -07:00
checksum = "1f3ccbac311fea05f86f61904b462b55fb3df8837a366dfc601a0161d0532f20"
2022-10-08 04:30:12 -06:00
[[package]]
name = "tokenizers"
2024-04-18 09:17:40 -06:00
version = "0.19.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-04-18 09:17:40 -06:00
checksum = "e500fad1dd3af3d626327e6a3fe5050e664a6eaa4708b8ca92f1794aaf73e6fd"
2022-10-08 04:30:12 -06:00
dependencies = [
2023-11-30 07:18:15 -07:00
"aho-corasick",
"derive_builder",
"esaxx-rs",
"getrandom",
"hf-hub",
"indicatif",
2024-02-16 09:50:57 -07:00
"itertools 0.12.1",
2022-10-08 04:30:12 -06:00
"lazy_static",
"log",
"macro_rules_attribute",
"monostate",
2022-10-08 04:30:12 -06:00
"onig",
"paste",
"rand",
"rayon",
"rayon-cond",
"regex",
2024-06-27 00:08:43 -06:00
"regex-syntax 0.8.4",
2022-10-08 04:30:12 -06:00
"serde",
"serde_json",
"spm_precompiled",
"thiserror",
"unicode-normalization-alignments",
"unicode-segmentation",
"unicode_categories",
]
[[package]]
name = "tokenizers"
version = "0.20.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "c8a24d7f7d6be5b9d1377418b893ab1808af0074f5d1bb2c64784452ddd2aa70"
dependencies = [
"aho-corasick",
"derive_builder",
"esaxx-rs",
"getrandom",
"hf-hub",
"indicatif",
"itertools 0.12.1",
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"log",
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"monostate",
"onig",
"paste",
"rand",
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"serde",
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"unicode-normalization-alignments",
"unicode-segmentation",
"unicode_categories",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "tokio"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "1.39.3"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "9babc99b9923bfa4804bd74722ff02c0381021eafa4db9949217e3be8e84fff5"
2022-10-08 04:30:12 -06:00
dependencies = [
2023-07-01 11:25:41 -06:00
"backtrace",
2022-10-08 04:30:12 -06:00
"bytes",
"libc",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"mio 1.0.2",
2022-10-08 04:30:12 -06:00
"parking_lot",
"pin-project-lite",
2022-10-18 07:19:03 -06:00
"signal-hook-registry",
2023-12-22 07:46:04 -07:00
"socket2",
2022-10-08 04:30:12 -06:00
"tokio-macros",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"windows-sys 0.52.0",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "tokio-io-timeout"
version = "1.2.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "30b74022ada614a1b4834de765f9bb43877f910cc8ce4be40e89042c9223a8bf"
dependencies = [
"pin-project-lite",
"tokio",
]
[[package]]
name = "tokio-macros"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "2.4.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "693d596312e88961bc67d7f1f97af8a70227d9f90c31bba5806eec004978d752"
2022-10-08 04:30:12 -06:00
dependencies = [
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
]
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2023-02-13 05:02:45 -07:00
version = "0.3.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-02-13 05:02:45 -07:00
checksum = "bbae76ab933c85776efabc971569dd6119c580d8f5d448769dec1764bf796ef2"
2022-10-08 04:30:12 -06:00
dependencies = [
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2024-06-27 00:08:43 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"rustls 0.23.12",
2024-06-27 00:08:43 -06:00
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2022-10-08 04:30:12 -06:00
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2024-03-22 11:44:05 -06:00
version = "0.1.15"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-22 11:44:05 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.7.11"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "9cf6b47b3771c49ac75ad09a6162f53ad4b8088b76ac60e8ec1455b31a189fe1"
2022-10-08 04:30:12 -06:00
dependencies = [
"bytes",
"futures-core",
"futures-io",
2022-10-08 04:30:12 -06:00
"futures-sink",
"pin-project-lite",
"tokio",
]
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "toml"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.8.19"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "a1ed1f98e3fdc28d6d910e6737ae6ab1a93bf1985935a1193e68f93eeb68d24e"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
"serde",
"serde_spanned",
"toml_datetime",
"toml_edit",
]
[[package]]
name = "toml_datetime"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.6.8"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "0dd7358ecb8fc2f8d014bf86f6f638ce72ba252a2c3a2572f2a795f1d23efb41"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
"serde",
]
[[package]]
name = "toml_edit"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.22.20"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "583c44c02ad26b0c3f3066fe629275e50627026c51ac2e595cca4c230ce1ce1d"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"indexmap 2.4.0",
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
"serde",
"serde_spanned",
"toml_datetime",
"winnow",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "tonic"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.9.2"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "3082666a3a6433f7f511c7192923fa1fe07c69332d3c6a2e6bb040b569199d5a"
2022-10-08 04:30:12 -06:00
dependencies = [
"async-trait",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"axum 0.6.20",
2024-01-26 11:04:57 -07:00
"base64 0.21.7",
2022-10-08 04:30:12 -06:00
"bytes",
"futures-core",
"futures-util",
2024-06-27 00:08:43 -06:00
"h2 0.3.26",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
"http-body 0.4.6",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"hyper 0.14.30",
2022-10-08 04:30:12 -06:00
"hyper-timeout",
"percent-encoding",
"pin-project",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"prost 0.11.9",
2022-10-08 04:30:12 -06:00
"tokio",
"tokio-stream",
"tower",
"tower-layer",
"tower-service",
"tracing",
]
2023-07-01 11:25:41 -06:00
[[package]]
name = "tonic"
2023-11-30 07:18:15 -07:00
version = "0.10.2"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "d560933a0de61cf715926b9cac824d4c883c2c43142f787595e48280c40a1d0e"
2023-07-01 11:25:41 -06:00
dependencies = [
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"async-stream",
2023-07-01 11:25:41 -06:00
"async-trait",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"axum 0.6.20",
2024-01-26 11:04:57 -07:00
"base64 0.21.7",
2023-07-01 11:25:41 -06:00
"bytes",
2024-06-27 00:08:43 -06:00
"h2 0.3.26",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 0.2.12",
"http-body 0.4.6",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"hyper 0.14.30",
2023-07-01 11:25:41 -06:00
"hyper-timeout",
"percent-encoding",
"pin-project",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"prost 0.12.6",
2023-07-01 11:25:41 -06:00
"tokio",
"tokio-stream",
"tower",
"tower-layer",
"tower-service",
"tracing",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "tonic-build"
2023-11-30 07:18:15 -07:00
version = "0.10.2"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "9d021fc044c18582b9a2408cd0dd05b1596e3ecdb5c4df822bb0183545683889"
2022-10-08 04:30:12 -06:00
dependencies = [
2023-02-13 05:02:45 -07:00
"prettyplease",
2022-10-08 04:30:12 -06:00
"proc-macro2",
"prost-build",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
]
[[package]]
name = "tower"
version = "0.4.13"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b8fa9be0de6cf49e536ce1851f987bd21a43b771b09473c3549a6c853db37c1c"
dependencies = [
"futures-core",
"futures-util",
2023-07-14 08:31:48 -06:00
"indexmap 1.9.3",
2022-10-08 04:30:12 -06:00
"pin-project",
"pin-project-lite",
"rand",
"slab",
"tokio",
2023-02-13 05:02:45 -07:00
"tokio-util",
2022-10-08 04:30:12 -06:00
"tower-layer",
"tower-service",
"tracing",
]
2022-10-11 10:14:39 -06:00
[[package]]
name = "tower-http"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.5.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "1e9cd434a998747dd2c4276bc96ee2e0c7a2eadf3cae88e52be55a05fa9053f5"
dependencies = [
2024-06-27 00:08:43 -06:00
"bitflags 2.6.0",
"bytes",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 1.1.0",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
"http-body 1.0.1",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http-body-util",
"pin-project-lite",
"tower-layer",
"tower-service",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "tower-layer"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.3.3"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "121c2a6cda46980bb0fcd1647ffaf6cd3fc79a013de288782836f6df9c48780e"
2022-10-08 04:30:12 -06:00
[[package]]
name = "tower-service"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.3.3"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "8df9b6e13f2d32c91b9bd719c00d1958837bc7dec474d94952798cc8e69eeec3"
2022-10-08 04:30:12 -06:00
[[package]]
name = "tracing"
2023-11-30 07:18:15 -07:00
version = "0.1.40"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
checksum = "c3523ab5a71916ccf420eebdf5521fcef02141234bbc0b8a49f2fdc4544364ef"
2022-10-08 04:30:12 -06:00
dependencies = [
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"tracing-core",
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[[package]]
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-08 04:30:12 -06:00
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2023-02-13 05:02:45 -07:00
[[package]]
name = "tracing-opentelemetry"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.21.0"
2023-02-13 05:02:45 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "75327c6b667828ddc28f5e3f169036cb793c3f588d83bf0f262a7f062ffed3c8"
2023-02-13 05:02:45 -07:00
dependencies = [
"once_cell",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"opentelemetry 0.20.0",
"opentelemetry_sdk 0.20.0",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"smallvec",
2023-07-01 11:25:41 -06:00
"tracing",
"tracing-core",
2023-11-30 07:18:15 -07:00
"tracing-log 0.1.4",
2023-07-01 11:25:41 -06:00
"tracing-subscriber",
]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
]
2023-07-01 11:25:41 -06:00
[[package]]
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
name = "tracing-opentelemetry-instrumentation-sdk"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "0.16.0"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "9920abb6a3ee3a2af7d30c9ff02900f8481935d36723c3da95cf807468218e8c"
2023-07-01 11:25:41 -06:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"http 1.1.0",
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"tracing",
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"tracing-opentelemetry 0.22.0",
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
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2024-01-26 11:04:57 -07:00
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2022-10-08 04:30:12 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
[[package]]
name = "ureq"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
checksum = "d11a831e3c0b56e438a28308e7c810799e3c118417f342d30ecec080105395cd"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
dependencies = [
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
"base64 0.22.1",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"flate2",
"log",
"native-tls",
"once_cell",
Upgrading to rust 1.78. (#1851) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-06 05:48:11 -06:00
"rustls 0.22.4",
2024-02-16 09:50:57 -07:00
"rustls-pki-types",
2023-11-30 07:18:15 -07:00
"rustls-webpki",
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"serde",
"serde_json",
"url",
"webpki-roots",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "url"
2024-06-27 00:08:43 -06:00
version = "2.5.2"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
checksum = "22784dbdf76fdde8af1aeda5622b546b422b6fc585325248a2bf9f5e41e94d6c"
2022-10-08 04:30:12 -06:00
dependencies = [
"form_urlencoded",
"idna",
"percent-encoding",
]
2023-07-01 11:25:41 -06:00
[[package]]
name = "urlencoding"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
version = "2.1.3"
2023-07-01 11:25:41 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Fix `tokenizers==0.13.4` . (#838) # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-08-14 11:26:19 -06:00
checksum = "daf8dba3b7eb870caf1ddeed7bc9d2a049f3cfdfae7cb521b087cc33ae4c49da"
2023-07-01 11:25:41 -06:00
[[package]]
name = "utf8parse"
2024-06-27 00:08:43 -06:00
version = "0.2.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-06-27 00:08:43 -06:00
checksum = "06abde3611657adf66d383f00b093d7faecc7fa57071cce2578660c9f1010821"
[[package]]
name = "utoipa"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "4.2.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "c5afb1a60e207dca502682537fefcfd9921e71d0b83e9576060f09abc6efab23"
dependencies = [
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"indexmap 2.4.0",
"serde",
"serde_json",
"utoipa-gen",
]
[[package]]
name = "utoipa-gen"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "4.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "7bf0e16c02bc4bf5322ab65f10ab1149bdbcaa782cba66dc7057370a3f8190be"
dependencies = [
"proc-macro-error",
"proc-macro2",
"quote",
2023-07-14 08:31:48 -06:00
"regex",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "6.0.0"
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "0b39868d43c011961e04b41623e050aedf2cc93652562ff7935ce0f819aaf2da"
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
"axum 0.7.5",
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2024-01-26 11:04:57 -07:00
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2023-05-02 07:43:19 -06:00
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2023-05-02 07:43:19 -06:00
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.9.5"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"
2022-10-08 04:30:12 -06:00
[[package]]
name = "walkdir"
2024-03-22 11:44:05 -06:00
version = "2.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
2024-03-22 11:44:05 -06:00
checksum = "29790946404f91d9c5d06f9874efddea1dc06c5efe94541a7d6863108e3a5e4b"
dependencies = [
"same-file",
"winapi-util",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "want"
version = "0.3.1"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "bfa7760aed19e106de2c7c0b581b509f2f25d3dacaf737cb82ac61bc6d760b0e"
2022-10-08 04:30:12 -06:00
dependencies = [
"try-lock",
]
[[package]]
name = "wasi"
version = "0.11.0+wasi-snapshot-preview1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9c8d87e72b64a3b4db28d11ce29237c246188f4f51057d65a7eab63b7987e423"
[[package]]
name = "wasm-bindgen"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.93"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "a82edfc16a6c469f5f44dc7b571814045d60404b55a0ee849f9bcfa2e63dd9b5"
2022-10-08 04:30:12 -06:00
dependencies = [
"cfg-if",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"once_cell",
2022-10-08 04:30:12 -06:00
"wasm-bindgen-macro",
]
[[package]]
name = "wasm-bindgen-backend"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.93"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "9de396da306523044d3302746f1208fa71d7532227f15e347e2d93e4145dd77b"
2022-10-08 04:30:12 -06:00
dependencies = [
"bumpalo",
"log",
"once_cell",
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
"wasm-bindgen-shared",
]
[[package]]
name = "wasm-bindgen-futures"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.4.43"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "61e9300f63a621e96ed275155c108eb6f843b6a26d053f122ab69724559dc8ed"
2022-10-08 04:30:12 -06:00
dependencies = [
"cfg-if",
"js-sys",
"wasm-bindgen",
"web-sys",
]
[[package]]
name = "wasm-bindgen-macro"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.93"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "585c4c91a46b072c92e908d99cb1dcdf95c5218eeb6f3bf1efa991ee7a68cccf"
2022-10-08 04:30:12 -06:00
dependencies = [
"quote",
"wasm-bindgen-macro-support",
]
[[package]]
name = "wasm-bindgen-macro-support"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.93"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "afc340c74d9005395cf9dd098506f7f44e38f2b4a21c6aaacf9a105ea5e1e836"
2022-10-08 04:30:12 -06:00
dependencies = [
"proc-macro2",
"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2022-10-08 04:30:12 -06:00
"wasm-bindgen-backend",
"wasm-bindgen-shared",
]
[[package]]
name = "wasm-bindgen-shared"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.2.93"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "c62a0a307cb4a311d3a07867860911ca130c3494e8c2719593806c08bc5d0484"
2022-10-08 04:30:12 -06:00
[[package]]
name = "web-sys"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.3.70"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "26fdeaafd9bd129f65e7c031593c24d62186301e0c72c8978fa1678be7d532c0"
2022-10-08 04:30:12 -06:00
dependencies = [
"js-sys",
"wasm-bindgen",
]
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
[[package]]
name = "web-time"
version = "0.2.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "aa30049b1c872b72c89866d458eae9f20380ab280ffd1b1e18df2d3e2d98cfe0"
dependencies = [
"js-sys",
"wasm-bindgen",
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2024-02-21 06:50:57 -07:00
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2023-11-30 07:18:15 -07:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2024-06-27 00:08:43 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2024-06-27 00:08:43 -06:00
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2024-02-16 09:50:57 -07:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
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2022-10-08 04:30:12 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-17 10:27:33 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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2022-10-17 10:27:33 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2023-02-13 05:02:45 -07:00
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2022-10-18 07:19:03 -06:00
2023-11-30 07:18:15 -07:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2023-04-11 12:32:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2023-04-11 12:32:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2023-02-13 05:02:45 -07:00
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2022-10-08 04:30:12 -06:00
2023-11-30 07:18:15 -07:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2024-04-18 09:17:40 -06:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
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2022-10-18 07:19:03 -06:00
2023-04-11 12:32:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2023-04-11 12:32:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2023-04-11 12:32:18 -06:00
2023-11-30 07:18:15 -07:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
2023-04-11 12:32:18 -06:00
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Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
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2023-04-11 12:32:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "dc35310971f3b2dbbf3f0690a219f40e2d9afcf64f9ab7cc1be722937c26b4bc"
2023-04-11 12:32:18 -06:00
2023-11-30 07:18:15 -07:00
[[package]]
name = "windows_aarch64_msvc"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.52.6"
2023-11-30 07:18:15 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
2022-10-18 07:19:03 -06:00
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
2023-04-11 12:32:18 -06:00
[[package]]
name = "windows_i686_gnu"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.48.5"
2023-04-11 12:32:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "a75915e7def60c94dcef72200b9a8e58e5091744960da64ec734a6c6e9b3743e"
2023-04-11 12:32:18 -06:00
2023-11-30 07:18:15 -07:00
[[package]]
name = "windows_i686_gnu"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.52.6"
2024-04-18 09:17:40 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "8e9b5ad5ab802e97eb8e295ac6720e509ee4c243f69d781394014ebfe8bbfa0b"
2024-04-18 09:17:40 -06:00
[[package]]
name = "windows_i686_gnullvm"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.52.6"
2023-11-30 07:18:15 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
2022-10-18 07:19:03 -06:00
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2022-10-18 07:19:03 -06:00
2023-04-11 12:32:18 -06:00
[[package]]
name = "windows_i686_msvc"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.48.5"
2023-04-11 12:32:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "8f55c233f70c4b27f66c523580f78f1004e8b5a8b659e05a4eb49d4166cca406"
2023-04-11 12:32:18 -06:00
2023-11-30 07:18:15 -07:00
[[package]]
name = "windows_i686_msvc"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.52.6"
2023-11-30 07:18:15 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
2022-10-08 04:30:12 -06:00
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2022-10-18 07:19:03 -06:00
2023-04-11 12:32:18 -06:00
[[package]]
name = "windows_x86_64_gnu"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.48.5"
2023-04-11 12:32:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "53d40abd2583d23e4718fddf1ebec84dbff8381c07cae67ff7768bbf19c6718e"
2023-04-11 12:32:18 -06:00
2023-11-30 07:18:15 -07:00
[[package]]
name = "windows_x86_64_gnu"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.52.6"
2023-11-30 07:18:15 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
2022-10-18 07:19:03 -06:00
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2022-10-18 07:19:03 -06:00
2023-04-11 12:32:18 -06:00
[[package]]
name = "windows_x86_64_gnullvm"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.48.5"
2023-04-11 12:32:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "0b7b52767868a23d5bab768e390dc5f5c55825b6d30b86c844ff2dc7414044cc"
2023-04-11 12:32:18 -06:00
2023-11-30 07:18:15 -07:00
[[package]]
name = "windows_x86_64_gnullvm"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.52.6"
2023-11-30 07:18:15 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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2023-11-30 07:18:15 -07:00
2022-10-08 04:30:12 -06:00
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2022-10-18 07:19:03 -06:00
2023-04-11 12:32:18 -06:00
[[package]]
name = "windows_x86_64_msvc"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.48.5"
2023-04-11 12:32:18 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "ed94fce61571a4006852b7389a063ab983c02eb1bb37b47f8272ce92d06d9538"
2023-04-11 12:32:18 -06:00
2023-11-30 07:18:15 -07:00
[[package]]
name = "windows_x86_64_msvc"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.52.6"
2023-11-30 07:18:15 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec"
2023-11-30 07:18:15 -07:00
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
name = "winnow"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
version = "0.6.18"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
checksum = "68a9bda4691f099d435ad181000724da8e5899daa10713c2d432552b9ccd3a6f"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
"memchr",
]
2022-10-08 04:30:12 -06:00
[[package]]
name = "winreg"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
version = "0.50.0"
2022-10-08 04:30:12 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
checksum = "524e57b2c537c0f9b1e69f1965311ec12182b4122e45035b1508cd24d2adadb1"
2022-10-08 04:30:12 -06:00
dependencies = [
Preping 1.1.0 (#1066) # What does this PR do? Upgrade all relevant versions and dependencies. <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2023-09-27 02:40:18 -06:00
"cfg-if",
"windows-sys 0.48.0",
2022-10-08 04:30:12 -06:00
]
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
[[package]]
name = "zerocopy"
version = "0.7.35"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1b9b4fd18abc82b8136838da5d50bae7bdea537c574d8dc1a34ed098d6c166f0"
dependencies = [
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"byteorder",
"zerocopy-derive",
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
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Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2023-11-30 07:18:15 -07:00
]
2024-02-16 09:50:57 -07:00
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Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
version = "1.8.1"
2024-02-16 09:50:57 -07:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Upgrade to Axum 0.7 and Hyper 1.0 (Breaking change: disabled ngrok tunneling). (#1959) - Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's our time now - [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files) hasn't yet, and hasn't for several months now, so let's disabled the feature for the time being. # What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-05-28 06:52:17 -06:00
checksum = "ced3678a2879b30306d323f4542626697a464a97c0a07c9aebf7ebca65cd4dde"
2024-06-27 00:08:43 -06:00
dependencies = [
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source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ce36e65b0d2999d2aafac989fb249189a141aee1f53c612c1f37d72631959f69"
dependencies = [
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"quote",
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-08-29 08:29:01 -06:00
"syn 2.0.76",
2024-06-27 00:08:43 -06:00
]
2024-02-16 09:50:57 -07:00
2022-10-08 04:30:12 -06:00
[[package]]
name = "zip"
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2022-10-08 04:30:12 -06:00
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2022-10-08 04:30:12 -06:00
dependencies = [
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2022-10-08 04:30:12 -06:00
"flate2",
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Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
[[package]]
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[[package]]
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Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
version = "0.4.13"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
source = "registry+https://github.com/rust-lang/crates.io-index"
Rebase TRT-llm (#2331) * wip wip refacto refacto Initial setup for CXX binding to TRTLLM Working FFI call for TGI and TRTLLM backend Remove unused parameters annd force tokenizer name to be set Overall build TRTLLM and deps through CMake build system Enable end to end CMake build First version loading engines and making it ready for inference Remembering to check how we can detect support for chunked context Move to latest TensorRT-LLM version Specify which default log level to use depending on CMake build type make leader executor mode working unconditionally call InitializeBackend on the FFI layer bind to CUDA::nvml to retrieve compute capabilities at runtime updated logic and comment to detect cuda compute capabilities implement the Stream method to send new tokens through a callback use spdlog release 1.14.1 moving forward update trtllm to latest version a96cccafcf6365c128f004f779160951f8c0801c correctly tell cmake to build dependent tensorrt-llm required libraries create cmake install target to put everything relevant in installation folder add auth_token CLI argument to provide hf hub authentification token allow converting huggingface::tokenizers error to TensorRtLlmBackendError use correct include for spdlog include guard to build example in cmakelists working setup of the ffi layer remove fmt import use external fmt lib end to end ffi flow working make sure to track include/ffi.h to trigger rebuild from cargo impl the rust backend which currently cannot move the actual computation in background thread expose shutdown function at ffi layer impl RwLock scenario for TensorRtLllmBackend oops missing c++ backend definitions compute the number of maximum new tokens for each request independently make sure the context is not dropped in the middle of the async decoding. remove unnecessary log add all the necessary plumbery to return the generated content update invalid doc in cpp file correctly forward back the log probabilities remove unneeded scope variable for now refactor Stream impl for Generation to factorise code expose the internal missing start/queue timestamp forward tgi parameters rep/freq penalty add some more validation about grammar not supported define a shared struct to hold the result of a decoding step expose information about potential error happening while decoding remove logging add logging in case of decoding error make sure executor_worker is provided add initial Dockerfile for TRTLLM backend add some more information in CMakeLists.txt to correctly install executorWorker add some more information in CMakeLists.txt to correctly find and install nvrtc wrapper simplify prebuilt trtllm libraries name definition do the same name definition stuff for tensorrt_llm_executor_static leverage pkg-config to probe libraries paths and reuse new install structure from cmake fix bad copy/past missing nvinfer linkage direction align all the linker search dependency add missing pkgconfig folder for MPI in Dockerfile correctly setup linking search path for runtime layer fix missing / before tgi lib path adding missing ld_library_path for cuda stubs in Dockerfile update tgi entrypoint commenting out Python part for TensorRT installation refactored docker image move to TensorRT-LLM v0.11.0 make docker linter happy with same capitalization rule fix typo refactor the compute capabilities detection along with num gpus update TensorRT-LLM to latest version update TensorRT install script to latest update build.rs to link to cuda 12.5 add missing dependant libraries for linking clean up a bit install to decoder_attention target add some custom stuff for nccl linkage fix envvar CARGO_CFG_TARGET_ARCH set at runtime vs compile time use std::env::const::ARCH make sure variable live long enough... look for cuda 12.5 add some more basic info in README.md * Rebase. * Fix autodocs. * Let's try to enable trtllm backend. * Ignore backends/v3 by default. * Fixing client. * Fix makefile + autodocs. * Updating the schema thing + redocly. * Fix trtllm lint. * Adding pb files ? * Remove cargo fmt temporarily. * ? * Tmp. * Remove both check + clippy ? * Backporting telemetry. * Backporting 457fb0a1 * Remove PB from git. * Fixing PB with default member backends/client * update TensorRT-LLM to latest version * provided None for api_key * link against libtensorrt_llm and not libtensorrt-llm --------- Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Co-authored-by: Morgan Funtowicz <morgan@huggingface.co>
2024-07-31 02:33:10 -06:00
checksum = "16099418600b4d8f028622f73ff6e3deaabdff330fb9a2a131dea781ee8b0768"
Adding Llava-Next (Llava 1.6) with full support. (#1709) # What does this PR do? - Changed all models to extract `embed_tokens` in order to enable llava to separately call the embeddings and the core model layers. - Added VlmCausalLM to inherit from FlashMistral in order to be maximally supported. The only added logics sits on top and parses images into pixel values, preallocates input_ids space for the image embeddings, and passes them for the model. - Added Clip for the vision tower. - Didn't add flash for the vision tower since there's no padding anyway. - Added heuristic (potentially incomplete) to calculate number of features *before* calculating the clip patches (allows for easier logic reuse of the LLM under the hood). Still needs to be done: - [x] Implement the image parsing in the controller side, to avoid downloading n times per TP shard and also refusing requests too large early and avoid issues where the truncation actually truncates the image. - [ ] Make sure it works with quantization properly. - [x] Make sure it works with TP>1 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
2024-04-09 13:32:00 -06:00
dependencies = [
"zune-core",
]