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fix: fix CohereForAI/c4ai-command-r-plus (#1707) @Narsil @drbh this will update flash attention v2 and vllm. You will need to re-install them.
2024-04-10 09:20:25 -06:00
flash_att_v2_commit_cuda := 23e8fa5a263d1c7122bc46a86ef32030ee7130f9
MI300 compatibility (#1764) Adds support for AMD Instinct MI300 in TGI. Most changes are: * Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable. TunableOp is disabled by default, and can be enabled with `PYTORCH_TUNABLEOP_ENABLED=1`. * Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes from https://github.com/pytorch/pytorch/pull/124362) * Support SILU & Linear custom kernels contributed by AMD * Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/, branching out of a much more recent commit https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308 * Support FA2 Triton kernel as recommended by AMD. Can be used by specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`. * Update dockerfile to ROCm 6.1 By default, TunableOp tuning results are saved in `/data` (e.g. `/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order to avoid to have to rerun the tuning at each `docker run`. Example: ``` Validator,PT_VERSION,2.3.0 Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c Validator,HIPBLASLT_VERSION,0.7.0-1549b021 Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack- Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098 GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431 GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546 GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119 GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645 GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971 GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694 GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522 GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671 GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834 GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622 GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122 GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191 GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514 GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914 GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516 GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953 GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043 GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497 GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895 GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716 GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731 GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816 GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701 GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159 GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524 GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074 GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045 GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582 GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705 GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489 ``` --------- Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
flash_att_v2_commit_rocm := 2554f490101742ccdc56620a938f847f61754be6
feat(server): flash attention v2 (#624)
2023-07-18 08:21:18 -06:00
Add RoCm support (#1243) This PR adds support for AMD Instinct MI210 & MI250 GPUs, with paged attention and FAv2 support. Remaining items to discuss, on top of possible others: * Should we have a `ghcr.io/huggingface/text-generation-inference:1.1.0+rocm` hosted image, or is it too early? * Should we set up a CI on MI210/MI250? I don't have access to the runners of TGI though. * Are we comfortable with those changes being directly in TGI, or do we need a fork? --------- Co-authored-by: Felix Marty <felix@hf.co> Co-authored-by: OlivierDehaene <olivier@huggingface.co> Co-authored-by: Your Name <you@example.com>
2023-11-27 06:08:12 -07:00
`make install-flash-attn-v2-cuda` should work like `make install-flash-attn-v2` used to work. (#1294) # 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 -->
2023-11-28 08:28:40 -07:00
flash-attention-v2-cuda:
# Clone flash attention
pip install -U packaging ninja --no-cache-dir
git clone https://github.com/HazyResearch/flash-attention.git flash-attention-v2
build-flash-attention-v2-cuda: flash-attention-v2-cuda
cd flash-attention-v2 && git fetch && git checkout $(flash_att_v2_commit_cuda)
cd flash-attention-v2 && git submodule update --init --recursive
cd flash-attention-v2 && python setup.py build
install-flash-attention-v2-cuda: build-flash-attention-v2-cuda
cd flash-attention-v2 && git submodule update --init --recursive && python setup.py install
Add RoCm support (#1243) This PR adds support for AMD Instinct MI210 & MI250 GPUs, with paged attention and FAv2 support. Remaining items to discuss, on top of possible others: * Should we have a `ghcr.io/huggingface/text-generation-inference:1.1.0+rocm` hosted image, or is it too early? * Should we set up a CI on MI210/MI250? I don't have access to the runners of TGI though. * Are we comfortable with those changes being directly in TGI, or do we need a fork? --------- Co-authored-by: Felix Marty <felix@hf.co> Co-authored-by: OlivierDehaene <olivier@huggingface.co> Co-authored-by: Your Name <you@example.com>
2023-11-27 06:08:12 -07:00
`make install-flash-attn-v2-cuda` should work like `make install-flash-attn-v2` used to work. (#1294) # 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 -->
2023-11-28 08:28:40 -07:00
flash-attention-v2-rocm:
Add RoCm support (#1243) This PR adds support for AMD Instinct MI210 & MI250 GPUs, with paged attention and FAv2 support. Remaining items to discuss, on top of possible others: * Should we have a `ghcr.io/huggingface/text-generation-inference:1.1.0+rocm` hosted image, or is it too early? * Should we set up a CI on MI210/MI250? I don't have access to the runners of TGI though. * Are we comfortable with those changes being directly in TGI, or do we need a fork? --------- Co-authored-by: Felix Marty <felix@hf.co> Co-authored-by: OlivierDehaene <olivier@huggingface.co> Co-authored-by: Your Name <you@example.com>
2023-11-27 06:08:12 -07:00
# Clone flash attention
pip install -U packaging ninja --no-cache-dir
MI300 compatibility (#1764) Adds support for AMD Instinct MI300 in TGI. Most changes are: * Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable. TunableOp is disabled by default, and can be enabled with `PYTORCH_TUNABLEOP_ENABLED=1`. * Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes from https://github.com/pytorch/pytorch/pull/124362) * Support SILU & Linear custom kernels contributed by AMD * Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/, branching out of a much more recent commit https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308 * Support FA2 Triton kernel as recommended by AMD. Can be used by specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`. * Update dockerfile to ROCm 6.1 By default, TunableOp tuning results are saved in `/data` (e.g. `/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order to avoid to have to rerun the tuning at each `docker run`. Example: ``` Validator,PT_VERSION,2.3.0 Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c Validator,HIPBLASLT_VERSION,0.7.0-1549b021 Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack- Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098 GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431 GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546 GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119 GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645 GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971 GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694 GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522 GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671 GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834 GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622 GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122 GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191 GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514 GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914 GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516 GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953 GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043 GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497 GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895 GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716 GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731 GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816 GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701 GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159 GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524 GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074 GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045 GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582 GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705 GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489 ``` --------- Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
git clone https://github.com/ROCm/flash-attention.git flash-attention-v2
feat(server): flash attention v2 (#624)
2023-07-18 08:21:18 -06:00
`make install-flash-attn-v2-cuda` should work like `make install-flash-attn-v2` used to work. (#1294) # 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 -->
2023-11-28 08:28:40 -07:00
build-flash-attention-v2-rocm: flash-attention-v2-rocm
cd flash-attention-v2 && git fetch && git checkout $(flash_att_v2_commit_rocm)
Add RoCm support (#1243) This PR adds support for AMD Instinct MI210 & MI250 GPUs, with paged attention and FAv2 support. Remaining items to discuss, on top of possible others: * Should we have a `ghcr.io/huggingface/text-generation-inference:1.1.0+rocm` hosted image, or is it too early? * Should we set up a CI on MI210/MI250? I don't have access to the runners of TGI though. * Are we comfortable with those changes being directly in TGI, or do we need a fork? --------- Co-authored-by: Felix Marty <felix@hf.co> Co-authored-by: OlivierDehaene <olivier@huggingface.co> Co-authored-by: Your Name <you@example.com>
2023-11-27 06:08:12 -07:00
cd flash-attention-v2 && git submodule update --init --recursive
MI300 compatibility (#1764) Adds support for AMD Instinct MI300 in TGI. Most changes are: * Support PyTorch TunableOp to pick the GEMM/GEMV kernels for decoding https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cuda/tunable. TunableOp is disabled by default, and can be enabled with `PYTORCH_TUNABLEOP_ENABLED=1`. * Update ROCm dockerfile to PyTorch 2.3 (actually patched with changes from https://github.com/pytorch/pytorch/pull/124362) * Support SILU & Linear custom kernels contributed by AMD * Update vLLM paged attention to https://github.com/fxmarty/rocm-vllm/, branching out of a much more recent commit https://github.com/ROCm/vllm/commit/3489ce7936c5de588916ae3047c44c23c0b0c308 * Support FA2 Triton kernel as recommended by AMD. Can be used by specifying `ROCM_USE_FLASH_ATTN_V2_TRITON=1`. * Update dockerfile to ROCm 6.1 By default, TunableOp tuning results are saved in `/data` (e.g. `/data/tunableop_meta-llama-Llama-2-70b-chat-hf_tp1_rank0.csv`) in order to avoid to have to rerun the tuning at each `docker run`. Example: ``` Validator,PT_VERSION,2.3.0 Validator,ROCM_VERSION,6.1.0.0-82-5fabb4c Validator,HIPBLASLT_VERSION,0.7.0-1549b021 Validator,GCN_ARCH_NAME,gfx942:sramecc+:xnack- Validator,ROCBLAS_VERSION,4.1.0-cefa4a9b-dirty GemmTunableOp_Half_TN,tn_8192_7_28672,Gemm_Rocblas_45475,0.132098 GemmTunableOp_Half_TN,tn_10240_4_8192,Gemm_Rocblas_45546,0.0484431 GemmTunableOp_Half_TN,tn_32000_6_8192,Default,0.149546 GemmTunableOp_Half_TN,tn_32000_3_8192,Gemm_Rocblas_45520,0.147119 GemmTunableOp_Half_TN,tn_8192_3_28672,Gemm_Rocblas_45475,0.132645 GemmTunableOp_Half_TN,tn_10240_3_8192,Gemm_Rocblas_45546,0.0482971 GemmTunableOp_Half_TN,tn_57344_5_8192,Gemm_Rocblas_45520,0.255694 GemmTunableOp_Half_TN,tn_10240_7_8192,Gemm_Rocblas_45517,0.0482522 GemmTunableOp_Half_TN,tn_8192_3_8192,Gemm_Rocblas_45546,0.0444671 GemmTunableOp_Half_TN,tn_8192_5_8192,Gemm_Rocblas_45546,0.0445834 GemmTunableOp_Half_TN,tn_57344_7_8192,Gemm_Rocblas_45520,0.25622 GemmTunableOp_Half_TN,tn_8192_2_28672,Gemm_Rocblas_45475,0.132122 GemmTunableOp_Half_TN,tn_8192_4_8192,Gemm_Rocblas_45517,0.0453191 GemmTunableOp_Half_TN,tn_10240_5_8192,Gemm_Rocblas_45517,0.0482514 GemmTunableOp_Half_TN,tn_8192_5_28672,Gemm_Rocblas_45542,0.133914 GemmTunableOp_Half_TN,tn_8192_2_8192,Gemm_Rocblas_45517,0.0446516 GemmTunableOp_Half_TN,tn_8192_1_28672,Gemm_Hipblaslt_TN_10814,0.131953 GemmTunableOp_Half_TN,tn_10240_2_8192,Gemm_Rocblas_45546,0.0481043 GemmTunableOp_Half_TN,tn_32000_4_8192,Gemm_Rocblas_45520,0.147497 GemmTunableOp_Half_TN,tn_8192_6_28672,Gemm_Rocblas_45529,0.134895 GemmTunableOp_Half_TN,tn_57344_2_8192,Gemm_Rocblas_45520,0.254716 GemmTunableOp_Half_TN,tn_57344_4_8192,Gemm_Rocblas_45520,0.255731 GemmTunableOp_Half_TN,tn_10240_6_8192,Gemm_Rocblas_45517,0.0484816 GemmTunableOp_Half_TN,tn_57344_3_8192,Gemm_Rocblas_45520,0.254701 GemmTunableOp_Half_TN,tn_8192_4_28672,Gemm_Rocblas_45475,0.132159 GemmTunableOp_Half_TN,tn_32000_2_8192,Default,0.147524 GemmTunableOp_Half_TN,tn_32000_5_8192,Default,0.147074 GemmTunableOp_Half_TN,tn_8192_6_8192,Gemm_Rocblas_45546,0.0454045 GemmTunableOp_Half_TN,tn_57344_6_8192,Gemm_Rocblas_45520,0.255582 GemmTunableOp_Half_TN,tn_32000_7_8192,Default,0.146705 GemmTunableOp_Half_TN,tn_8192_7_8192,Gemm_Rocblas_45546,0.0445489 ``` --------- Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
2024-05-17 07:30:47 -06:00
cd flash-attention-v2 && GPU_ARCHS="gfx90a;gfx942" PYTORCH_ROCM_ARCH="gfx90a;gfx942" python setup.py build
feat(server): flash attention v2 (#624)
2023-07-18 08:21:18 -06:00
`make install-flash-attn-v2-cuda` should work like `make install-flash-attn-v2` used to work. (#1294) # 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 -->
2023-11-28 08:28:40 -07:00
install-flash-attention-v2-rocm: build-flash-attention-v2-rocm
cd flash-attention-v2 && git submodule update --init --recursive && python setup.py install