Commit Graph

90 Commits

Author SHA1 Message Date
Daniël de Kok 67ef0649cf
GPTQ CI improvements (#2151)
* Add more representative Llama GPTQ test

The Llama GPTQ test is updated to use a model with the commonly-used
quantizer config format and activation sorting. The old test is
kept around (but renamed) since it tests the format produced by
`text-generation-server quantize`.

* Add support for manually triggering a release build
2024-07-05 14:12:16 +02:00
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
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
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 fc9c3153e5
Add pytest release marker (#2114)
* Add pytest release marker

Annotate a test with `@pytest.mark.release` and it only gets run
with `pytest integration-tests --release`.

* Mark many models as `release` to speed up CI
2024-06-25 16:53:20 +02:00
Lucain 3447c722fd
Support `HF_TOKEN` environment variable (#2066)
* Support HF_TOKEN environement variable

* Load test.

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-06-25 09:23:12 +02:00
Nicolas Patry 480d3b3304
New runner. Manual squash. (#2110)
* New runner. Manual squash.

* Network host.

* Put back trufflehog with proper extension.

* No network host ?

* Moving buildx install after tailscale ?

* 1.79
2024-06-24 18:08:34 +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
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
drbh 376a0b7ada
Support chat response format (#2046)
* feat: support response_format in chat

* fix: adjust typos

* fix: add trufflehog lint
2024-06-11 10:44:56 -04:00
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 967ced2ff4 Gemma GPTQ checks: skip logprob checks
This test fails somewhat regularly due to non-determinism and this
test is primarily to verify that we are loading a model which doesn't
have `float16` as the default dtype correctly.
2024-05-30 11:28:05 +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
Daniël de Kok f20463e4e3 Fix (non-container) pytest stdout buffering-related lock-up
Two issues:

1. When one of the stdout/stderr pipe buffers of a process started
   with `subprocess.Popen` is full, the process can get blocked until
   the buffer is drained.
2. Calling `Popen.wait` can deadlock when called before draining
   the pipe buffers (if they are full).

This avoids the issue altogether by giving the child process a
temporary file to write to.
2024-05-28 16:26:11 +02:00
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 d32e33bd48
Fix seeded output. (#1949)
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2024-05-24 15:36:13 +02:00
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
Daniël de Kok b5bc6e5c4e
Add GPT-2 with flash attention (#1889)
# What does this PR do?

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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 bfddfa5955
Idefics2. (#1756)
# What does this PR do?

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2024-04-23 23:04:44 +02:00
OlivierDehaene 2d0a7173d4 v2.0.1 2024-04-18 17:20:36 +02:00
drbh 06c3d4b1ec
feat: accept list as prompt and use first string (#1702)
This PR allows the `CompletionRequest.prompt` to be sent as a string or
array of strings. When an array is sent the first value will be used if
it's a string; otherwise the according error will be thrown

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1690
Similar to: https://github.com/vllm-project/vllm/pull/323/files
2024-04-17 10:41:12 +02:00
drbh 7276d43495
feat: improve tools to include name and add tests (#1693)
This PR makes tool calling aware of the name of the function selected. 

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1657

Thank you @puppetm4st3r for the helpful snippets, large parts of this PR
are simply refactors of the code shared 🙏

**opening draft PR because small tweaks are needed before merging
2024-04-16 09:02:46 -04:00
OlivierDehaene c38a7d7ddd
v2.0.0 (#1736) 2024-04-12 18:38:34 +02:00
Nicolas Patry 1b2670c823
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).

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2024-04-12 14:20:31 +02:00
Nicolas Patry 4634b00c2a
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



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2024-04-09 21:32:00 +02:00
Nicolas Patry 99874eae74
Add cuda graphs sizes and make it default. (#1703)
# What does this PR do?

```
text-generation-launcher --model-id XXX # Uses cuda graphs by default
text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
```
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2024-04-04 23:01:56 +02:00
OlivierDehaene 4ee0a0c401
v1.4.5 (#1686) 2024-03-29 19:17:24 +01:00
OlivierDehaene 6c4496a1a3
v1.4.4 (#1668) 2024-03-22 18:44:05 +01:00
Nicolas Patry f171bdc823
Inline images for multimodal models. (#1666) 2024-03-22 17:14:54 +01:00
Nicolas Patry deb440b3a2
Repair idefics integration tests. (#1663)
# What does this PR do?

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2024-03-21 22:21:03 +01:00
drbh de6cb15fa5
fix: improve tool type, bump pydantic and outlines (#1650)
This PR resolves a couple 

- [X] adjusts the tool response to align with openai's tools response
type
- [X] bumps pydantic to `2.6.4` in all apps (resolves dependency issue
when running tests)
- [X] bump `outlines` version and fix import for new name
2024-03-21 12:45:56 -04:00
drbh 4f09c80cd8
fix: prefer spaces url over temp url (#1662)
This PR fixes the broken urls in the idefics tests causing CI to fail
2024-03-21 17:34:25 +01:00
drbh 7dbaf9e901
fix: correctly index into mask when applying grammar (#1618)
This PR fixes how the grammar mask is index when generating text and
adds a new test to ensure the grammars work with non flash models
2024-03-01 18:22:01 +01:00
drbh 343aa7a197
fix: Handle concurrent grammar requests (#1610)
This PR fixes parallel grammar requests, currently grammar states are
not concatenated correctly when a new request is added to the batch and
this results in incorrect generation. This PR updates the `concatenate`
function to correctly include the previous states.

fixes: #1601
2024-02-29 11:17:42 +01:00
OlivierDehaene e6bb3ff81f
v1.4.3 (#1609) 2024-02-28 16:12:14 +01:00
OlivierDehaene 26cdea5c0c
feat: Qwen2 (#1608)
See #1584

---------

Co-authored-by: Cheng Kuan Yong Jason <jasoncky96@gmail.com>
2024-02-28 15:50:31 +01:00
OlivierDehaene b40e833493
feat: starcoder2 (#1605) 2024-02-28 12:07:08 +01:00
drbh 9b6db5f793
Support tools (#1587)
This work in progress PR begins to add support for tools. Tools relies
on grammar support and still has some unsolved challenges. Opening the
PR for visibility and feedback
2024-02-28 11:10:27 +01:00
Nicolas Patry bf700e7eef
Revamp medusa implementation so that every model can benefit. (#1588)
# What does this PR do?

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
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2024-02-26 19:49:28 +01:00
OlivierDehaene 9c1cb81cd8
v1.4.2 (#1585) 2024-02-21 14:50:57 +01:00
OlivierDehaene c86f58d37c
feat: add support for Gemma (#1583) 2024-02-21 14:15:22 +01:00
OlivierDehaene fa8a8e05af
fix(router): fix openapi and add jsonschema validation (#1578) 2024-02-21 11:05:32 +01:00
OlivierDehaene 4139054b82
v1.4.1 (#1568) 2024-02-16 17:50:57 +01:00
OlivierDehaene 9946165ee0
chore: add pre-commit (#1569) 2024-02-16 11:58:58 +01:00
drbh cef0553d59
Outlines guided generation (#1539)
This WIP PR starts to add grammar support via outlines, currently this
PR supports very simple regex grammars and does not optimize for
precompiling or caching grammar fsm's.

todo:
- [X] add simple outlines guidance to `NextTokenChooser`
- [X] update protos for grammar
- [X] update generation params API
- [X] constrain simple grammar
- [ ] support parsing more complex grammar into fsm
- [ ] support all outline support grammar types
- [ ] explore optimizations to avoid recompiling grammars

guided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data-raw '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6,
        "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+"
    }
}' | jq
```
response
```json
{
  "generated_text": "david@example.com"
}
```

unguided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6
    }
}' | jq
```
response
```json
{
  "generated_text": "    email = 'david"
}
```
2024-02-15 10:28:10 +01:00
Nicolas Patry d6b0fb9e25
Improving mamba runtime by using updates (#1552)
- Move float16 to bfloat16, which has less imprecisions (load test are
  failing with the update kernels + f16, all working under bf16).

  Another note, is that we are not respecting the layer norm in f32
  defined in the configuration (this is OK in my book, but that could
  impact the f16 precision)

- Moved to update kernels. Triton overhead is super high, removed by
  switching to cuda graphs works great (update cuda graph is available
  in TRT-LLM if needed, seems *exactly* like the regular ssm kernel.

- Moved inference_params struct in order to make only 2 tensors, to
  reduce the overhead of copying back and forth to the cuda graphs.

- Left over overhead seems entirely in the tokenization bit. (Still 4
  copies are paid before launching the graph)


# What does this PR do?

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Fixes # (issue)


## 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?
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2024-02-14 09:54:10 +01:00
OlivierDehaene 0d794af6a5
feat: experimental support for cuda graphs (#1428)
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-02-12 10:09:29 +01:00
Ilyas Moutawwakil a4e5801684
ROCm AWQ support (#1514)
# What does this PR do?

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This PR adds the possibility to run AWQ models with Exllama/GPTQ
kernels, specifically for ROCm devices that support Exllama kernels but
not AWQ's GEMM.

This is done by :
- un-packing, reordering and re-packing AWQ weights when `--quantize
gptq` but the model's `quant_method=awq`.
- avoiding overflows when adding 1 to zeros in exllama and triton.

Ref: https://github.com/casper-hansen/AutoAWQ/pull/313

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
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- [ ] Did you write any new necessary tests?


## Who can review?

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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-02-09 10:45:16 +01:00
OlivierDehaene 09b7c26bbd
feat(server): add frequency penalty (#1541) 2024-02-08 18:41:25 +01:00