Commit Graph

342 Commits

Author SHA1 Message Date
fxmarty 227f78f3fe Merge branch 'main' into ci_amd3 2024-06-26 12:08:42 +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
fxmarty dc53846456 Merge branch 'main' into ci_amd3 2024-06-25 11:20:00 +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
Felix Marty 5b6b257756
fix gpt2 tests - some weights were not contiguous 2024-06-24 18:51:08 +02:00
fxmarty 1846c1c210
fix tests 2024-06-24 18:50:18 +02:00
fxmarty 5a4b798f98
fix gptq tests, LLMM1 matrix bound 2024-06-24 18:49:45 +02:00
fxmarty 49db30a137
disable marlin tests on rocm/xpu 2024-06-24 18:49:37 +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
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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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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)
# 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
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