GitLab

* hotfix: fix xpu crash brought by code refine. torch.xpu rely on import ipex
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* reable gemma2 in xpu
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* fix in regression in ipex flashattention
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: Wang, Yi A <yi.a.wang@intel.com>

* fix: attempt forward on flash attn2 to check hardware support

* fix: warn window_size_left when using flash attn 1

* fix: prefer version check over test op and avoid window_size_left if not flash attn2

* fix: improve condtional and error message

* fix: update sliding window conditional

* fix: simplify changes and revert model changes

* fix: avoid changing conditional

* fix: typo tweak

- Always return the hidden states.
- Create the output tensor inside the `attention` and `paged_attention`
  functions.

This removes the difference between how the output is handled between
attention (output parameter) and paged attention (return value). This
also removes the assumption that the attention implementation can
write to an output tensor (in preparation of FlashInfer).

* feat: add ruff and resolve issue

* fix: update client exports and adjust after rebase

* fix: adjust syntax to avoid circular import

* fix: adjust client ruff settings

* fix: lint and refactor import check and avoid model enum as global names

* fix: improve fbgemm_gpu check and lints

* fix: update lints

* fix: prefer comparing model enum over str

* fix: adjust lints and ignore specific rules

* fix: avoid unneeded quantize check

* Softcapping for gemma2.

* Less clutter.

* No access to transformers config, only config_dict here.

* 0.0 is the null value in the C++ API.

* feat(fp8): add support for fbgemm

* allow loading fp8 weights directly

* update outlines

* fix makefile

* build fbgemm

* avoid circular import and fix dockerfile

* add default dtype

* refactored weights loader

* fix auto conversion

* fix quantization config parsing

* force new nccl on install

* missing get_weights implementation

* increase timeout

install triton because GPTQParams needs it.
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* 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.

* 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>

* 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

* 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>

* 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?

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Purely refactors paged/attention into `layers/attention` and make hardware differences more obvious with 1 file per hardware. (#1986)

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guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
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passed. Feel free to tag
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