Commit Graph

453 Commits

Author SHA1 Message Date
OlivierDehaene
abe521204e fix tests 2024-06-12 18:54:25 +02:00
OlivierDehaene
05eb4dcb17 allocate 16 by 16 2024-06-12 18:53:14 +02:00
OlivierDehaene
9ac7b7bc52 remove slots from grpc 2024-06-12 11:50:31 +02:00
OlivierDehaene
37266e2dbb fix rust and python unit-tests 2024-06-11 17:11:16 +02:00
OlivierDehaene
73c3903214 FlashCausalLM implem 2024-06-11 13:15:06 +02:00
OlivierDehaene
298bf31e69 add terminated_generations 2024-06-11 13:15:06 +02:00
OlivierDehaene
3c596983ba fix python tests 2024-06-11 13:15:06 +02:00
OlivierDehaene
51fa606875 fix 2024-06-11 13:15:05 +02:00
OlivierDehaene
35f27cbcc1 working example 2024-06-11 13:15:05 +02:00
OlivierDehaene
1cc86930a6 wip 2024-06-11 13:15:05 +02:00
OlivierDehaene
18e77a5cc7 wip 2024-06-11 13:15:05 +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
51621439a4 marlin: improve build 2024-06-06 17:19:46 +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
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other checks if that's the case).
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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
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other checks if that's the case).
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2024-06-05 10:45:47 +02:00
Nicolas Patry
824edf28d7
Hotfixing make install. (#2008)
# What does this PR do?

Fixes initial and subsequent installs (protection for folder creation
should only be for git commit, checking out correct commit should be on
both.

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2024-06-04 23:34:03 +02:00
Nicolas Patry
8390e251d9
Making make install work better by default. (#2004)
# What does this PR do?

Making `make install` a much better sane default to start local dev
environments.

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2024-06-04 19:38:46 +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
OlivierDehaene
757223b352
feat: add SchedulerV3 (#1996)
- Refactor code to allow supporting multiple versions of the
generate.proto at the same time
- Add v3/generate.proto (ISO to generate.proto for now but allow for
future changes without impacting v2 backends)
- Add Schedule trait to abstract queuing and batching mechanisms that
will be different in the future
- Add SchedulerV2/V3 impl
2024-06-04 15:56:56 +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
Wang, Yi
d1d724b027
reable xpu, broken by gptq and setuptool upgrade (#1988)
# What does this PR do?

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---------

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
2024-06-03 16:07:50 +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)
# What does this PR do?

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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)
# 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
d32e33bd48
Fix seeded output. (#1949)
# What does this PR do?

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2024-05-24 15:36:13 +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