Commit Graph

409 Commits

Author SHA1 Message Date
Daniël de Kok 8511669cb2
Move quantized weight handling out of the `Weights` class (#2194)
Quantized weights were loaded in the `Weights` class, but this was
getting quite unwieldy, where every higher level method to load weights
was a long conditional to cover all the different quantizers.

This change moves loading of quantized weights out of the `Weights`
class. This is done by defining a simple `WeightsLoader` interface
that is implemented by `Exl2WeightsLoader`, `GPTQWeightsLoader`,
and `MarlinWeightsLoader`. These implementations are in the quantizers'
respective modules. The `Weights` class provides the low-level load
operations (such as loading tensors or sharded tensors), but delegates
loads that need quantizer-specific weight processing to a loader. The
loaders still use the low-level functionality provided by `Weights`.

I initially tried making a hierarchy where a class like `GPTQWeights`
would inherit from `Weights`. But it is not very flexible (e.g. does
not work well with the new weight storage mock used in tests) and
the implicit indirections made the code harder to follow.
2024-07-09 20:04:03 +02:00
Daniël de Kok 5c7c9f1390
Falcon/DBRX: get correct number of key-value heads (#2205) 2024-07-08 13:22:38 +02:00
Daniël de Kok 153fcf7739
Fix incorrect cache allocation with multi-query (#2203)
We wouldn't allocate any memory in multi-query (1 KV head). Fixes
Starcoder et al.
2024-07-08 11:19:48 +02:00
Daniël de Kok cce475a949
hotfix: Fix number of KV heads (#2202)
Fix number of KV heads
2024-07-08 09:52:12 +02:00
icyboy™ 521d0d990f
fix dbrx & opt model prefix bug (#2201)
* Update idefics_causal_lm.py

Fix syntax issues

* fix dbrx & opt model prefix bug
2024-07-08 09:01:14 +02:00
Daniël de Kok 05c094fcfa
Consistently take `prefix` in model constructors (#2191)
* Consistently take `prefix` in model constructors

* Release test check fix

* Misc refactor-related fixes
2024-07-05 16:07:48 +02:00
Daniël de Kok b67d46336e
Fix Starcoder2 after refactor (#2189) 2024-07-05 12:22:45 +02:00
Nicolas Patry 853d4eb9cf
Hotfixing after refactor. 2024-07-05 09:25:29 +00:00
Nicolas Patry fb2f74e2b9
Refactor dead code - Removing all `flash_xxx.py` files. (#2166)
* Refactor dead code.

* First working step.

* Remove a lot of duplicated code.

* More dead code.

* More cleanup.

* Fix Santacoder test.

* Fixing the simple tests.

* Fixing sharding.

* Fixes for VLM.

* Fixing santacoder (num_kv_heads hardcoded).

* Removing more dead code.

* Fixing `config.n_head`.

* Stopping earlier because of `<end_of_utterance>` in idefics2.

* Addresses comments.

* Removing the dead code.

* Fuse back mistral into FlashCausalLM.

* Finish removal.

* Fixing docs + causal_lm `batch_class`.

* Fixing docs + causal.lm.

* Add default to Gemma Causality.

* Default value for gemma/gemma2.

* Wrong default.
2024-07-05 10:29:56 +02:00
Aaron Mihalik c6bcadf883
Adding "longrope" for Phi-3 (#2172) (#2179)
Adding "longrope" for phi-3
2024-07-05 09:46:41 +02:00
Nicolas Patry 0759ec495e
Hotfixing qwen2 and starcoder2 (which also get clamping). (#2167) 2024-07-02 14:26:47 +02:00
Nicolas Patry dea9c0dc74
Fixing rocm. (#2164) 2024-07-02 12:01:08 +02:00
drbh b966bc0d35
fix: use the base layers weight in mistral rocm (#2155) 2024-07-02 11:56:25 +02:00
Wang, Yi 5d97e0c4a3
fix FlashDecoding change's regression in intel platform (#2161)
install triton because GPTQParams needs it.

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
2024-07-02 11:56:07 +02:00
Nicolas Patry 022f6515a4
Fixing graph capture for flash decoding. (#2163) 2024-07-02 11:43:07 +02:00
Nicolas Patry 4327210e6b
[Major Change][Undecided yet] Move to FlashDecoding instead of PagedAttention kernel. (#1940)
* Using flash decoding

Conditional flashdecoding.

Fix max_q.

Working kvcache

Working version with flash decoding.

Make it work for mistral.

Fix after rebase..

Less intrusive.

REvert changes in modeling.

Speedup flashdecoding.

HHachweew
Hack to make other models work.

Fixing non flash decoding llama path.

Router logic knows about page size.

Missing 2 models.

Missing cohere.

Fixing cohere flash decoding.

Revamped all this architecture.

Fix cohere.

Fixing falcon.

Enabling custom block size schedule.

Update router/src/infer.rs

Not sending preallocated output.

* Making it work on non flash decoding.

* Fix Cohere.

* Fix non decoding paths.

* Rebased.

* No need for cache_manager anymore.

* Update?

* "ipex" -> "cpu"

* These do not belong.

* Factoring cu_seqlen_qk for better abstracting over every model.

* Fixing non flash tests/imports.

* Changing return everywhere.

* Update mistral past.

* Fixing Mi{s,x}tral (non functional in Flash Decoding mode though).

* Fixup mistral clamping (had issues with cuda graphs).

* No need to recreate anything actually.
2024-07-01 23:28:00 +02:00
Nicolas Patry 4f55f15840
Fixing baichuan override. (#2158) 2024-07-01 23:25:54 +02:00
Wang, Yi 5da4cfab1c
refine get xpu free memory/enable Qwen2/gemma2/gemma/phi in intel platform (#2132)
* refine get xpu free memory

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* enable qwen2 in xpu

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* enable gemma/gemma2/phi in intel platform

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

---------

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
2024-07-01 14:32:54 +02:00
icyboy™ 9d0ca503a8
fix AttributeError: 'MixtralLayer' object has no attribute 'mlp' (#2123)
https://github.com/huggingface/text-generation-inference/issues/2122
2024-07-01 14:17:22 +02:00
Daniël de Kok 2ce8019480
Use GPTQ-Marlin for supported GPTQ configurations (#2111)
GPTQ-Marlin is currently the best-performing kernel for GPTQ models. So
let's use it by default if the kernels are installed, the GPU supports
it, and the kernels support the configuration.

For models generated by `text-generation-server quantize`, use
`sym=False`. This subcommand symmetric quantization since the beginning
and incorrectly reporting the model to be symmetric will use
GPTQ-Marlin (which does not support asymmetric quantization).
2024-07-01 12:59:12 +02:00
drbh 25f57e2e98
fix: use weights from base_layer (#2141) 2024-07-01 12:58:40 +02:00
Nicolas Patry 3ea8259af1
Fixing gemma2. (#2135)
* Fixing gemma2.

* Adding new model.
2024-06-27 16:04:20 +02:00
Daniël de Kok dd2d91b043
Idefics2: sync added image tokens with transformers (#2080)
Before this change, the number of reserved image tokens was not the
same as the number of images. Fixes #2029.

While at it, also remove all the image token handling duplication
in `prepare_input`.
2024-06-27 15:54:35 +02:00
Daniël de Kok f1f98e369f
Add support for Marlin 2:4 sparsity (#2102)
This change adds support for 2:4 sparsity when using Marlin
quantization. The 2:4 kernel is used when:

* The quantizer is `marlin`;
* the quantizer checkpoint format is `marlin_24`.

Fixes #2098.
2024-06-25 21:09:42 +02:00
Daniël de Kok 14980df2df
Support AWQ quantization with bias (#2117)
When the AWQ quantizer was used with a layer that uses a bias,
the bias tensor was not correctly passed/used. Instead, the
value `true`/`1.0` was added to the linear transformation.

Correctly pass through the bias when it is not `None`.

Fixes #2106.
2024-06-25 21:09:00 +02:00
drbh 04e1af94d7
Enable multiple LoRa adapters (#2010)
* feat: first draft load multiple lora

* feat: load weights within layer and refactor lora pass

* fix: refactor and reduce lora math

* feat: baseline impl single request multi lora support

* feat: prefer lorax implementation and port loading logic

* fix: prefer adapter_data and refactors

* feat: perfer loraxs custom punica kernels and add mlp loras

* fix: adjust batch for bgmv

* fix: adjust adapter_segments logic when in batch

* fix: refactor and move changes to v3 proto

* fix: pass model_id for all flash causal lms

* fix: pass model_id for all causal and seq2seq lms

* fix: add model_id to model test

* feat: add lora support to mistral and refactors

* feat: prefer model id in request

* fix: include rust code for adapter id

* feat: bump launcher and add new lora docs

* feat: support base model generation and refactors

* fix: rename doc to retry ci build

* feat: support if vlm models

* fix: add adapter_data param and avoid missing layers

* fix: add adapter_data param to phi and neox

* fix: update all models forwards to include adapter_data

* fix: add model_id to IdeficsCausalLM

* Update lora.md

Fixed a typo

* Update lora.md

Fixing spam image

* fix: add lora kernel to dockerfile, support running without kernels and refactors

* fix: avoid dockerfile conflict

* fix: refactors and adjust flash llama lora logic

* fix: skip llama test due to CI issue (temp)

* fix: skip llama test CI (temp) 2

* fix: revert skips and prefer updated ci token for tests

* fix: refactors and helpful comments

* fix: add noop in TensorParallelAdapterRowLinear too

* fix: refactor and move shard_lora_weights logic

* fix: exit early if no adapter_data

---------

Co-authored-by: Derek <datavistics@gmail.com>
2024-06-25 14:46:27 -04:00
Wang, Yi e563983d90
fix cpu and xpu issue (#2116)
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
2024-06-25 16:47:06 +02:00
Nicolas Patry 9e2fdf57c0
Removing IPEX_AVAIL. (#2115)
* Removing IPEX_AVAIL.

Chose to unify CPU and XPU under `ipex`. Most code is exactly similar
except for a very few spots.

The biggest number of spots is the kv-cache layout and the flash_xxx.py
files.
Since those files should be removed soon and factored away, we should
not need them.

* Forgot a few places.

* Unrelated change.

* Fixing HF_TOKEN.

* HF_TOKEN
2024-06-25 13:20:57 +02:00
Wang, Yi b64c70c9e7
Cpu tgi (#1936)
* add CPU tgi support

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* ipex distributed ops support

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

---------

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Funtowicz Morgan <mfuntowicz@users.noreply.github.com>
2024-06-25 12:21:29 +02:00
Wang, Yi 83634dc122
use xpu-smi to dump used memory (#2047)
* use xpu-smi to dump used memory
xpu use "ZE_AFFINITY_MASK" to control card, usage is like CUDA_VISIBLE_DEVICES

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* Update server/text_generation_server/utils/import_utils.py

Co-authored-by: Daniël de Kok <me@github.danieldk.eu>

---------

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
2024-06-25 10:15:46 +02:00
KevinDuffy94 1869ee2f57
Add OTLP Service Name Environment Variable (#2076)
* Adding Service Name Environment variable for https://github.com/huggingface/text-generation-inference/issues/2069

* Update Docs

* Update README.md

* Update Launcher Docs

* Update Launcher Docs
Removing Option
2024-06-25 09:33:01 +02:00
drbh 811a9381b1
feat: sort cuda graphs in descending order (#2104) 2024-06-21 14:28:26 -04:00
Daniël de Kok 197c47a302
Fix `text-generation-server quantize` (#2103)
The subcommand did not work due to some broken imports.
2024-06-21 15:28:51 +02:00
Daniël de Kok bcb3faa1c2
Factor out sharding of packed tensors (#2059)
For Phi-3-Small I need to shard a packed QKV bias tensor, for which
I implemented the `Weights.get_packed_sharded` method. However, this
method can also replace the `Weights._get_qweight` method and the
custom sharding code from `Weights.get_weights_col_packed`.
2024-06-20 09:56:04 +02:00
Daniël de Kok f5a9837592
Support exl2-quantized Qwen2 models (#2085)
Fixes #2081.
2024-06-20 07:56:16 +02:00
Daniël de Kok c8c7ccd31e
Set maximum grpc message receive size to 2GiB (#2075)
* Set maximum grpc message receive size to 2GiB

The previous default was 4MiB, which doesn't really work well for
multi-modal models.

* Update to Rust 1.79.0

* Fixup formatting to make PR pass
2024-06-17 16:40:44 +02:00
Daniël de Kok e903770897
Support different image sizes in prefill in VLMs (#2065)
When a batch contained images if different sizes during prefill, the
server would fail (see e.g. #2056). Images were processed separately and
then concatenated. However, this can fail for images with different sizes.

Fix this by preprocessing all images in the batch together, so that the
image processor can ensure that all image tensors have compatible sizes.
2024-06-17 10:49:41 +02:00
Tiezhen WANG 96b7b40ca3
Update the link for qwen2 (#2068)
* Update the link for qwen2

* Fix Qwen2 model URL in model table

* Fix too eager staging

---------

Co-authored-by: Daniël de Kok <me@danieldk.eu>
2024-06-14 11:59:33 +02:00
Daniël de Kok 093a27c528
Add support for GPTQ Marlin (#2052)
Add support for GPTQ Marlin kernels

GPTQ Marlin extends the Marlin kernels to support common GPTQ
configurations:

- bits: 4 or 8
- groupsize: -1, 32, 64, or 128
- desc_act: true/false

Using the GPTQ Marlin kernels requires repacking the parameters in the
Marlin quantizer format.

The kernels were contributed by Neural Magic to VLLM. We vendor them
here for convenience.
2024-06-14 09:45:42 +02:00
OlivierDehaene 90184df79c
fix(layers): fix SuRotaryEmbedding (#2060)
* fix(layers): fix SuRotaryEmbedding

* change arange

* remove logs
2024-06-12 18:24:47 +02:00
OlivierDehaene 521de6cacd
fix(server): fix OPT implementation (#2061) 2024-06-12 18:22:20 +02:00
Daniël de Kok 85dfc39222
Add Phi-3 medium support (#2039)
Add support for Phi-3-medium

The main difference between the medium and mini models is that medium
uses grouped query attention with a packed QKV matrix. This change adds
support for GQA with packed matrixes to `Weights.get_weights_col_packed`
and uses it for Phi-3. This also allows us to remove the custom
implementation of GQA from dbrx attention loading.
2024-06-10 09:22:29 +02:00
fxmarty 9b3674d903
ROCm and sliding windows fixes (#2033)
* update vllm commit & fix models using sliding window

* update

* update commit

* fix bug where tunableop is bound to cuda graph even when cuda graph are disabled

* enable tunableop by default

* fix sliding window

* address review

* dead code

* precise comment

* is it flaky?
2024-06-10 15:09:50 +08:00
Daniël de Kok bf3c813782 server: use chunked inputs
The router will now send the input as chunks besides as a single
string. This change modifies the server to process chunked input
rather than strings. This also allows us to remove the image
extraction code from the server.
2024-06-07 08:09:04 +02:00
Daniël de Kok 0d96468ebb marlin: support tp>1 when group_size==-1 2024-06-06 17:19:28 +02:00
Daniël de Kok 4594e6faba Add support for Marlin-quantized models
This change adds support for Marlin-quantized models. Marlin is an
FP16xINT4 matmul kernel, which provides good speedups decoding batches
of 16-32 tokens. It supports quantized models with symmetric
quantization, groupsize -1 or 128, and 4-bit.

Tested with:

- Llama 2
- Llama 3
- Phi 3
2024-06-06 13:16:52 +02:00
Daniël de Kok 3f4bcf978c
Fix GPTQWeight import (#2020)
# What does this PR do?

Fix stray import.

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
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2024-06-05 14:49:15 +02:00
Nicolas Patry 0a94fad79f
Fixing rocm. (#2021)
# What does this PR do?

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2024-06-05 14:41:34 +02:00
OlivierDehaene 8aece3bd68
feat: move allocation logic to rust (#1835)
Close #2007
2024-06-05 12:18:38 +02:00
Daniël de Kok 9ffe1f1e67
Do not initialize scratch space when there are no ExLlamaV2 layers (#2015)
# What does this PR do?

Do not attempt to allocate ExLlamaV2 scratch buffers when there are no
ExLlama2 layers. Avoids a crash in warmup for models that cannot use
exllama when ExLlamaV2 is installed.

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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2024-06-05 10:45:47 +02:00
Daniël de Kok d14eaacaca
Support GPTQ models with column-packed up/gate tensor (#2006)
# What does this PR do?

The GPTQ code path for column-packed packed tensors assumed that this is
always a QKV matrix. However, models (e.g. Phi-3) can also have
column-packed MLP up/gate matrices.

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2024-06-04 19:37:49 +02:00
Daniël de Kok 9b52f0e2dc
Fix Phi-2 with `tp>1` (#2003)
# What does this PR do?

We were using the wrong parallelism in the up-projection.

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2024-06-04 14:26:07 +02:00
Nicolas Patry 9a59ebcec3 Hotfix GPTQ. 2024-06-03 09:32:12 +00:00
Nicolas Patry 9add5d0af5
Fixing GPTQ imports. (#1994)
# What does this PR do?

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2024-06-03 10:36:29 +02:00
Nicolas Patry 799a193b10 Fixing Phi3. 2024-06-01 08:47:00 +00:00
Nicolas Patry 5ab4cef67e
Fixing exl2 scratch buffer. (#1990)
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2024-05-31 18:01:43 +02:00
Nicolas Patry 06edde9491
Purely refactors paged/attention into `layers/attention` and make hardware differences more obvious with 1 file per hardware. (#1986)
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2024-05-31 17:57:01 +02:00
Daniël de Kok 36dd16017c Add support for exl2 quantization
Mostly straightforward, changes to existing code:

* Wrap quantizer parameters in a small wrapper to avoid passing
  around untyped tuples and needing to repack them as a dict.
* Move scratch space computation to warmup, because we need the
  maximum input sequence length to avoid allocating huge
  scratch buffers that OOM.
2024-05-30 11:28:05 +02:00
drbh cbced7f0f9
feat: adjust attn weight loading logic (#1975)
This PR updates `load_attention` to prefer loading specific attention
based on the model type. Additionally there were two cases where
`TensorParallelColumnLinear.load_multi` was called and this reduces it
to a single path
2024-05-29 12:42:11 -04:00
Daniël de Kok a401c83c35
Fix GPTQ for models which do not have float16 at the default dtype (simpler) (#1953)
# What does this PR do?

Fix GPTQ for models which do not have float16 at the default dtype

Before this change GPTQ models would not work if the model's default
data type is not `float16`. For example, Gemma GPTQ models would fail
because the default dtype of Gemma is `bfloat16`. There are two issues:

If the default `dtype` is not `float16`, the quantizer's `float16`
parameters get converted to that dtype. The kernels cannot deal
with non-`float16` types. The same applies to inputs of quantized ops.

This is resolved by setting the dtype of gptq/awq-quantized models to
`float16`.

Simpler version of #1951.

**Draft:** just testing...

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2024-05-27 14:41:28 +02:00
Daniël de Kok 9231098f3a Fix (flash) Gemma prefix and enable tests 2024-05-27 09:58:06 +02:00
Nicolas Patry cff472ba2b
Fixing codellama loads by using purely `AutoTokenizer`. (#1947)
- The need for the slow tokenizer default stems from back
  when llama 1 was introduced and all the flags where not
  supported in `tokenizers`.

- Fixes #1891


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2024-05-24 12:40:39 +02:00
Nicolas Patry 954653466d
Improving the logging system. (#1938)
- Added a debug log for speculated ids (helps seeing in logs quality of
  a speculator).
- Remove newlines from child process logs when re-emitting in non JSON
  mode.
- Made standard level be closer to what's expected (only our binaries
  level).
- Propagate that level correctly to the shard (was forced into INFO).


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2024-05-23 15:40:40 +02:00
Nicolas Patry f4a073ae6d
Fixing some legacy behavior (big swapout of serverless on legacy stuff). (#1937)
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---------

Co-authored-by: Daniël de Kok <me@github.danieldk.eu>
2024-05-23 14:39:38 +02:00
Wang, Yi f41d644a90
reenable xpu for tgi (#1939)
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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
2024-05-23 14:11:08 +02:00
drbh efb73fcb59
fix: use path inside of speculator config (#1935)
This PR access the path on the speculator similar to
`MLPSpeculatorHead.load` and `MedusaHeadV1.load`


these changes resolves this error locally when loading a `MedusaHeadV2`
```
TypeError: expected str, bytes or os.PathLike object, not dict
```
2024-05-22 20:46:29 +02:00
Nicolas Patry 2f243a1a15
Creating doc automatically for supported models. (#1929)
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2024-05-22 16:22:57 +02:00
Nicolas Patry f871f114ca
Fixing the download strategy for ibm-fms (#1917)
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2024-05-18 13:31:24 +02:00
fxmarty 5dad0c0b29
Fix TGI issues with ROCm (#1921)
Not all models were tested in
https://github.com/huggingface/text-generation-inference/pull/1764.

Fixing some more issues (notably starcoder2) here, the full CI will come
shortly once we split `build.yml` in two
2024-05-18 01:50:52 +08:00
fxmarty b5f1c9de06
Fix TunableOp bug (#1920)
cc @Narsil
2024-05-17 18:21:51 +02:00
fxmarty 232e8d5227
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
3489ce7936
* 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 15:30:47 +02:00
Nicolas Patry a60fa8406a
Removing some unused code. (#1915)
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2024-05-17 11:35:49 +02:00
Nicolas Patry 3b5d93e68d
Fixing signals. (#1910)
Taking the signal handles later, so during loads,
regular signal handling is done, we only need to handle SIGINT and
SIGTERM during real loads to get more graceful shutdowns when queries
are in flight.

Fixes #1842 


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2024-05-16 15:40:10 -04:00
drbh 40213c957f
Pali gemma modeling (#1895)
This PR adds paligemma modeling code

Blog post: https://huggingface.co/blog/paligemma
Transformers PR: https://github.com/huggingface/transformers/pull/30814

install the latest changes and run with
```bash
# get the weights
# text-generation-server download-weights gv-hf/PaliGemma-base-224px-hf

# run TGI
text-generation-launcher --model-id gv-hf/PaliGemma-base-224px-hf
```


basic example sending various requests
```python
from huggingface_hub import InferenceClient

client = InferenceClient("http://127.0.0.1:3000")


images = [
    "https://huggingface.co/datasets/hf-internal-testing/fixtures-captioning/resolve/main/cow_beach_1.png",
    "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/rabbit.png",
]

prompts = [
    "What animal is in this image?",
    "Name three colors in this image.",
    "What are 10 colors in this image?",
    "Where is the cow standing?",
    "answer en Where is the cow standing?",
    "Is there a bird in the image?",
    "Is ther a cow in the image?",
    "Is there a rabbit in the image?",
    "how many birds are in the image?",
    "how many rabbits are in the image?",
]

for img in images:
    print(f"\nImage: {img.split('/')[-1]}")
    for prompt in prompts:
        inputs = f"![]({img}){prompt}\n"
        json_data = {
            "inputs": inputs,
            "parameters": {
                "max_new_tokens": 30,
                "do_sample": False,
            },
        }
        generated_output = client.text_generation(prompt, max_new_tokens=30, stream=False)
        print([f"{prompt}\n{generated_output}"])

```

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-05-16 06:58:47 +02:00
Dhruv Srikanth 6c715f8183
[Bug Fix] Update torch import reference in bnb quantization (#1902)
# What does this PR do?

Fixes `Import Error` occurring from mismatch of usage between
torch.nn.Module and nn.Module.
2024-05-15 21:08:32 +02:00
Nicolas Patry a70b087e71
Removing accepted ids in the regular info logs, downgrade to debug. (#1898)
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2024-05-15 13:56:07 +02:00
Daniël de Kok b5bc6e5c4e
Add GPT-2 with flash attention (#1889)
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This change adds `FlashGPT2ForCausalLM` and wires it up. The model
itself is pretty straightforward, the main difference from other models
is that it uses trained position embeddings and that all weight matrices
are transposed compared to other models (due to the use of Conv1D in the
upstream model).


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2024-05-15 13:31:22 +02:00
Nicolas Patry e3d765645a
MLPSpeculator. (#1865)
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---------

Co-authored-by: Joshua Rosenkranz <joshua.rosenkranz@gmail.com>
2024-05-14 12:33:18 +02:00
Nilabhra Roy Chowdhury 3136f27f36
Add: Support for the Falcon2 11B architecture (#1886)
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Add's support for the Falcon2 11B model architecture.


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---------

Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: oOraph <13552058+oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Julien Chaumond <julien@huggingface.co>
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
Co-authored-by: abhishek thakur <1183441+abhishekkrthakur@users.noreply.github.com>
Co-authored-by: Dong Shin <d0104.shin@gmail.com>
Co-authored-by: Christof Weickhardt <christof@weickhardt.ch>
Co-authored-by: Ikko Eltociear Ashimine <eltociear@gmail.com>
Co-authored-by: drbh <david.richard.holtz@gmail.com>
Co-authored-by: Lucain <lucain@huggingface.co>
Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>
Co-authored-by: Moritz Laurer <41862082+MoritzLaurer@users.noreply.github.com>
Co-authored-by: dr3s <dr3s@users.noreply.github.com>
Co-authored-by: Wang, Yi <yi.a.wang@intel.com>
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>
Co-authored-by: Maziyar Panahi <maziyar.panahi@iscpif.fr>
Co-authored-by: Brandon Royal <2762697+brandonroyal@users.noreply.github.com>
Co-authored-by: Mishig <mishig.davaadorj@coloradocollege.edu>
Co-authored-by: Martin Iglesias Goyanes <martinigoyanes@hotmail.com>
Co-authored-by: martini <martin.iglesiasgoyanes@adyen.com>
2024-05-14 10:06:02 +02:00
Nicolas Patry d348d2b28f
Granite support? (#1882)
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2024-05-13 13:46:29 +02:00
Nicolas Patry fd89d9dfae
Refactor layers. (#1866)
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2024-05-13 12:44:30 +02:00
Nicolas Patry a25737139d
Updating Phi3 (long context). (#1849)
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2024-05-02 19:07:10 +02:00
Nicolas Patry de079d607a
Remove misleading warning (not that important nowadays anyway). (#1848)
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2024-05-02 15:09:46 +02:00
Nicolas Patry 27b3a2c9fc
Fix: "Fixing" double BOS for mistral too. (#1843)
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2024-05-01 18:21:17 +02:00
Martin Iglesias Goyanes 9192de57cc
Fixing frequency penalty (#1811)
Thank you so much for the work you are doing, this is my little
contribution to this great thing you have built. I hope it is useful and
helpful, please don't hesitate to discuss any matters that are not
clear!

I am basing my implementation of frequency penalty on OpenAI's
implementation:
https://platform.openai.com/docs/guides/text-generation/parameter-details

The problem I see with TGI's current implementation is that is not
taking into account the frequency of tokens which have already been
sampled in the current generation stream. Also, the scaling is of the
adjusted token logits is done differently for positive and negative
logits. While in OpenAI's implementation token frequency is taking into
account and the scaling is always done with a subtraction (if penalty is
positive) or add operation (if penalty is negative).

This leads to corrupt generations as I mentioned in issue #1810 .
Moreover, after my tests, other issues are also gone like the one about
some request's with ``penalty_frequency = 1.0`` overruling other
requests (with ``frequency_penalty = 0.0``) in the same batch and
therefore corrupting all generations in the batch. Basically, padding
does not affect this implementation so I believe this ``score *=
input_ids.ne(0)`` is not needed anymore.



Frequency penalty | -1.0 | 0.0 | 1.0
-- | -- | -- | --
Before my change | https://paste.mozilla.org/JxqGJkWY |
https://paste.mozilla.org/hrztJ56h | https://paste.mozilla.org/pBSEH2zw
After my change | https://paste.mozilla.org/7gXCi7zo |
https://paste.mozilla.org/ZR9rJ92g | https://paste.mozilla.org/gHaD2YnC

---------

Co-authored-by: martini <martin.iglesiasgoyanes@adyen.com>
2024-04-30 12:13:23 +02:00
OlivierDehaene 8332fc4908
fix: use get_speculate to the number of layers (#1737) 2024-04-30 11:45:26 +02:00
Nicolas Patry 04d4765bad
Small CI cleanup. (#1801)
# What does this PR do?

Just unifying some branches and making intentions clearer (no cuda graph
when 0 all the way in the launcher)

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2024-04-30 11:39:38 +02:00
Nicolas Patry eade737714
Better graceful shutdown. (#1827)
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2024-04-29 17:23:40 +02:00
Nicolas Patry e9f03f822a
Dummy CI run. (#1817)
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2024-04-26 19:19:55 +02:00
Nicolas Patry 8b8e8f6632
Fixing qwen2. (#1818)
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2024-04-26 19:19:08 +02:00
Nicolas Patry a8fd4236eb
Blunder (#1815)
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2024-04-26 15:51:09 +02:00
Wang, Yi 45ecf9d040
add intel xpu support for TGI (#1475)
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---------

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-26 15:48:58 +02:00
Nicolas Patry ee47973a2f
Use the generation config. (#1808)
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2024-04-25 19:41:50 +02:00
drbh 0acac5cb7a
feat: improve temperature logic in chat (#1749)
This PR adds support for `do_sample` to chat to enable greedy sampling

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-25 15:31:35 +02:00
drbh 23d82b8fb6
fix: avoid frequency and repetition penalty on padding tokens (#1765)
This PR resolves an issue with the penalty processors during batched
generation where extra padding tokens incorrectly impact the penalty
scores.

generation is impacted in the case where at least one item in the batch
includes a `frequency_penalty`

reproduction script below
```python
import requests
from concurrent import futures
import time

headers = {
    "Content-Type": "application/json",
}

json_data = {
    "inputs": "[INST] Whats the capitol of France? [/INST]",
    "parameters": {
        "max_new_tokens": 100,
        "seed": 20,
        "do_sample": False,
    },
}


json_data2 = {
    "inputs": "<s>[INST]Write a mind bending story: I saw a puppy a cat a rat and a raccoon during my bike ride in the park[/INST]",
    "parameters": {
        "max_new_tokens": 100,
        "seed": 2,
        "do_sample": False,
        # OFFENDING LINE
        "frequency_penalty": 1.05,
    },
}

base_url = "http://localhost:3000/generate"


def req():
    response = requests.post(base_url, headers=headers, json=json_data)
    print("[req ]", response.json())


def req2():
    response = requests.post(base_url, headers=headers, json=json_data2)
    print("[req2]", response.json())


n = 1

for i in range(0, 3):
    print(f"- {n} threads -")
    with futures.ThreadPoolExecutor(max_workers=n) as executor:
        executor.submit(req)
        for i in range(3):
            executor.submit(req2)

    n += 1

# - 1 threads -
# [req ] {'generated_text': ' The capital of France is Paris.'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# - 2 threads -
# [req ] {'generated_text': ' The capital city'}
# [req2] {'generated_text': ' As""%\n================'}
# [req2] {'generated_text': ' As""%%$\n================'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}

# output with this PR's changes:
# - 1 threads -
# [req ] {'generated_text': ' The capital of France is Paris.'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# - 2 threads -
# [req ] {'generated_text': ' The capital city'}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}
# [req2] {'generated_text': " As you were riding your bicycle through Central Park, enjoying some fresh air on an otherwise gloomy day. You couldn't help but notice that it was eerily quiet for this time of year - usually there would be hordes"}

```

**divergence from expected generation is easier to reproduce with
batched grammar requests as they are more sensitive to unexpected
outputs.

this PR resolves the issue by setting the penalty score to 0 where input
ids are padding tokens (0).

---------

Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2024-04-23 23:19:16 +02:00
Nicolas Patry bfddfa5955
Idefics2. (#1756)
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2024-04-23 23:04:44 +02:00
Nicolas Patry 986b4044d1
Phi3 support (#1797)
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2024-04-23 18:40:05 +02:00
fxmarty 26b3916612
Make `--cuda-graphs` work as expected (bis) (#1768)
This was ignored up to now, even with `--cuda-graphs 0`.

With this fix, `--cuda-graphs` is obeyed to.
2024-04-22 16:09:19 +02:00
Nicolas Patry f9ee2c41b9
Upgrading all versions. (#1759) 2024-04-18 17:17:40 +02:00
OlivierDehaene c38a7d7ddd
v2.0.0 (#1736) 2024-04-12 18:38:34 +02:00