Commit Graph

226 Commits

Author SHA1 Message Date
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
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
OlivierDehaene
8aece3bd68
feat: move allocation logic to rust (#1835)
Close #2007
2024-06-05 12:18:38 +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
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
06edde9491
Purely refactors paged/attention into layers/attention and make hardware differences more obvious with 1 file per hardware. (#1986)
# What does this PR do?

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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
Nicolas Patry
2f243a1a15
Creating doc automatically for supported models. (#1929)
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2024-05-22 16:22:57 +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
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
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
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
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
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
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
OlivierDehaene
c38a7d7ddd
v2.0.0 (#1736) 2024-04-12 18:38:34 +02:00
OlivierDehaene
eefea5ee31
feat: medusa v2 (#1734) 2024-04-12 16:24:45 +02:00
OlivierDehaene
30620a9a44 hotfix: mixtral 2024-04-10 18:38:08 +02:00
OlivierDehaene
ad9d6288c8
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 17:20:25 +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
106d8ee818
Automatic quantization config. (#1719)
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2024-04-09 10:27:57 +02:00
Nicolas Patry
f9958ee191
Fixing cohere tokenizer. (#1697) 2024-04-05 16:44:19 +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
f04255c694
feat: Add dbrx support (#1685)
Close #1679
2024-03-29 18:49:36 +01:00
OlivierDehaene
1e9bcd9dd8
feat: cohere (#1660) 2024-03-22 17:59:25 +01:00
SeongBeomLEE
66914f7b19
fix: LlamaTokenizerFast to AutoTokenizer at flash_mistral.py (#1637)
# What does this PR do?

A few cases where you're using a mistral structure or mixtral structure
but not a llama tokenizer, why not make it to call the AutoTokenizer in
exception handling.

Similar PR #619

@Narsil
2024-03-22 17:13:13 +01:00
Nicolas Patry
ed29d6eeab
Remove unecessary cuda graph. (#1664)
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2024-03-21 20:11:05 +01:00