Support `auto_doctring` in Processors (#42101)
* remove attributes and add all missing sub processors to their auto classes
* remove all mentions of .attributes
* cleanup
* fix processor tests
* fix modular
* remove last attributes
* fixup
* fixes after merge
* fix wrong tokenizer in auto florence2
* fix missing audio_processor + nits
* Override __init__ in NewProcessor and change hf-internal-testing-repo (temporarily)
* fix auto tokenizer test
* add init to markup_lm
* update CustomProcessor in custom_processing
* remove print
* nit
* fix test modeling owlv2
* fix test_processing_layoutxlm
* Fix owlv2, wav2vec2, markuplm, voxtral issues
* add support for loading and saving multiple tokenizer natively
* remove exclude_attributes from save_pretrained
* Run slow v2 (#41914)
* Super
* Super
* Super
* Super
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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Fix `detectron2` installation in docker files (#41975)
* detectron2 - part 1
* detectron2 - part 2
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Fix `autoawq[kernels]` installation in quantization docker file (#41978)
fix autoawq[kernels]
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* add support for saving encoder only so any parakeet model can be loaded for inference (#41969)
* add support for saving encoder only so any decoder model can be loaded
Signed-off-by: nithinraok <nithinrao.koluguri@gmail.com>
* use convolution_bias
* convert modular
* convolution_bias in convertion script
---------
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Co-authored-by: Eustache Le Bihan <eulebihan@gmail.com>
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* Use indices as position_ids in modernebert (#41789)
* Use indices as position_ids in modernebert
* Move position_ids init to the branch
* test tensor parallel: make tests for dense model more robust (#41968)
* make test forward and backward more robust
* refactor compile part of test tensor parallel
* linting
* pass rank around instead of calling it over and over
* Run slow v2 (#41914)
* Super
* Super
* Super
* Super
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Fix `detectron2` installation in docker files (#41975)
* detectron2 - part 1
* detectron2 - part 2
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Fix `autoawq[kernels]` installation in quantization docker file (#41978)
fix autoawq[kernels]
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* add support for saving encoder only so any parakeet model can be loaded for inference (#41969)
* add support for saving encoder only so any decoder model can be loaded
Signed-off-by: nithinraok <nithinrao.koluguri@gmail.com>
* use convolution_bias
* convert modular
* convolution_bias in convertion script
---------
Signed-off-by: nithinraok <nithinrao.koluguri@gmail.com>
Co-authored-by: Eustache Le Bihan <eulebihan@gmail.com>
Co-authored-by: eustlb <94853470+eustlb@users.noreply.github.com>
---------
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Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
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Co-authored-by: Eustache Le Bihan <eulebihan@gmail.com>
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* fix: dict[RopeParameters] to dict[str, RopeParameters] (#41963)
* docs: add continuous batching page (#41847)
* docs: add continuous batching page
* docs(cb): add `generate_batch` example
* docs(cb): add `opentelemtry` and `serving` section
* feat: add `TODO` note about opentelemetry dependency
* docs(cb): add supported features
* docs(cb): add unsupported features
* docs(cb): add `ContinuousBatchingManager` example
* docs(cb): x reference CB in optimizing inference
* Fix `torchcodec` version in quantization docker file (#41988)
check
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* [kernels] Add Tests & CI for kernels (#41765)
* first commit
* add tests
* add kernel config
* add more tests
* add ci
* small fix
* change branch name
* update tests
* nit
* change test name
* revert jobs
* addressing review
* reenable all jobs
* address second review
* Move the Mi355 to regular docker (#41989)
* Move the Mi355 to regular docker
* Disable gfx950 compilation for FA on AMD
* More data in benchmarking (#41848)
* Reduce scope of cross-generate
* Rm generate_sall configs
* Workflow benchmarks more
* Prevent crash when FA is not installed
* fix (CI): Refactor SSH runners (#41991)
* Change ssh runner type
* Add wait step to SSH runner workflow
* Rename wait step to wait2 in ssh-runner.yml
* Remove wait step from ssh-runner.yml
Removed the wait step from the SSH runner workflow.
* Update runner type for single GPU A10 instance
* Update SSH runner version to 1.90.3
* Add sha256sum to ssh-runner workflow
* Update runner type and remove unused steps
* fix 3 failed test cases for video_llama_3 model on Intel XPU (#41931)
* fix 3 failed test cases for video_llama_3 model on Intel XPU
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
* update
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
* adjust format
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
* update code
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
---------
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
* Integrate colqwen2.5 using colqwen2 modelling code (#40600)
* adding option for 2.5
* minor - arg in conversion script
* getting started on modelling.py
* minor - shouldve been using modular
* adressing comments + fixing datatype/device _get method
* minor
* commiting suggestion
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* docs + first test
* ruff fix
* minor fix
* ruff fix
* model fix
* model fix
* fine-grained check, with a hardcoded score from the original Hf implementation.
* minor ruff
* update tests values with CI hardware
* adding 2.5 to conversion script
* Apply style fixes
---------
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* Fixed wrong padding value in OWLv2 (#41938)
* Update image_processing_owlv2_fast.py
fixed padding value
* fixed padding value
* Change padding constant value from 0.5 to 0.0
* Fixed missed padding value in modular_owlv2.py
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* Fix `run slow v2`: empty report when there is only one model (#42002)
fix
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* [kernels] change import time in KernelConfig (#42004)
* change import time
* style
* DOC Fix typo in argument name: pseudoquant (#41994)
The correct argument name is pseudoquantization. Since there is no error
on passing wrong arguments name (which is arguably an anti-pattern),
this is difficult for users to debug.
* Fix `torch+deepspeed` docker file (#41985)
* fix
* delete
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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Correct syntax error in trainer.md (#42001)
A comma is missing between two parameters in the signature of compute_loss function.
* Reduce the number of benchmark in the CI (#42008)
Changed how benchmark cfgs are chosen
* Fix continuous batching tests (#42012)
* Fix continuous batching tests
* make fixup
* add back `logging_dir` (#42013)
* add back
* Apply style fixes
---------
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* Fix issue with from pretrained and kwargs in image processors (#41997)
* accept kwargs in image proc from_pretrained
* only use kwargs that are in cls.valid_kwargs
* remove specific logic for _from_auto
* add image_seq_length to Images_kwargs for backward compatibility
* fix missing image kwargs in pix2struct
* Fix default image_rows and image_cols initialization in Idefics3 and SmolVLM processors (#41871)
* Fix default image_rows and image_cols initialization in Idefics3 and SmolVLM processors
* Fix default initialization of image_rows and image_cols in Idefics3 and SmolVLM processors
* Add GLPNImageProcessorFast (#41725)
* Add GLPNImageProcessorFast for torch backend
* Address review feedback
- Simplified to_dict() method
- Keep tensors as torch instead of converting to numpy for heterogeneous shapes
- Removed unnecessary shape guards in post_process_depth_estimation
- Improved variable names (tgt -> target_size, d -> resized)
- Removed unnecessary GLPNImageProcessorKwargs class
* Address review feedback
- Simplified to_dict() method
- Keep tensors as torch instead of converting to numpy for heterogeneous shapes
- Removed unnecessary shape guards in post_process_depth_estimation
- Improved variable names (tgt -> target_size, d -> resized)
- Removed unnecessary GLPNImageProcessorKwargs class
* commits after 2nd review
* Address all review feedback and add explicit batched test
- Simplified to_dict() with descriptive variable names (d->output_dict)
- Fixed resize operation: changed from crop to proper resize with interpolation
- Added padding for heterogeneous batch shapes in both slow and fast processors
- Fused rescale and normalize operations for efficiency
- Improved all variable names (tgt->target_size, d->depth_4d->resized)
- Added GLPNImageProcessorKwargs class in slow processor and imported in fast
- Renamed test_equivalence_slow_fast to test_slow_fast_equivalence
- Added explicit test_slow_fast_equivalence_batched test
- All 20 tests passing
* using padding from utils
* simplify glpn image processor fast
* fix docstring
---------
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* add fuyu fast image processors (#41817)
* added fast processor for fuyu (#36978)
* updated docs for fuyu model (#36978)
* updated test_image_processing and image_processing_fuyu_fast
* updated fuyu.md and image_processing_fuyu_fast (#36978)
* updated test_image_processing_fuyu (#36978)
* formatted image_processing_fuyu_fast and test_image_processing_fuyu (#36978)
* updated tests and fuyu fast image processing (#36978)
* Merge branch 'fuyu-fast-image-processors' of https://github.com/DeXtAr47-oss/transformers into fuyu-fast-image-processors
* fixed format (#36978)
* formatted files (#36978)
* formatted files
* revert unnecessary changes
* clean up and process by group
---------
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
* [kernels] Fix XPU layernorm kernel (#41583)
* fix
* add comment
* better fix
* style
* Update src/transformers/modeling_utils.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* [v5] Deprecate Text2Text and related pipelines (#41996)
* Deprecate Text2Text and related pipelines
* Try a restructure
* make fixup
* logging -> logger
* [FPQuant] MXFP8 and MXFP4 backwards support (#41897)
* FP-Quant backwards
* fp-quant v0.3.0 docker
* availability version bump
* fp_quant==0.3.1
* fp_quant v0.3.2
* add working auto_docstring for processors
* add auto_docstring to processors first part
* add auto_docstring to processors part 2
* modifs after review
* fully working auto_docstring and check_docstring with placeholder docstrings
* Working check_docstrings for Typed dicts
* Add recurring processor args to auto_docstring and add support for removing redundant docstring and placeholders
* replace placeholders with real docstrings
* fix copies
* fixup
* remove unwanted changes
* fix unprotected imports
* Fix unprotected imports
* fix unprotected imports
* Add __call__ to all docs of processors
* nits docs
---------
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