GitLab

* add Cambricon MLUs support

* fix mlu device rng state

* up for quality check

* up mlu to support fp16

* fix mlu device dependency error

* fix mlu device dependency error

* enable mlu device for bf16

* fix mlu device memory tracker

* Populate torch_dtype from model to pipeline
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* use property
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* lint
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* Remove default handling
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

---------
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* rm input dtype change in CPU

* add warning when use CPU low-precision

* rm useless logging

* Use logging.warning instead of warnings.warn in pipeline.__call__

* Update src/transformers/pipelines/base.py

* Update base.py

* Fix a typo

add npu device for pipeline
Co-authored-by: unit_test <test@unit.com>

* Abstract out pipeline init args

* Address PR comments

* Reword

* BC PIPELINE_INIT_ARGS

* Remove old arguments

* Small fix

* Add the XPU check for pipeline mode

When setting xpu device for pipeline, It needs to use is_torch_xpu_available to load ipex and determine whether the device is available.
Signed-off-by: yuanwu <yuan.wu@intel.com>

* Don't move model to device when hf_device_map isn't None

1. Don't move model to device when hf_device_map is not None
2. The device string maybe includes the device index, so use 'in'instead of equal
Signed-off-by: yuanwu <yuan.wu@intel.com>

* Raise the error when xpu is not available
Signed-off-by: yuanwu <yuan.wu@intel.com>

* Update src/transformers/pipelines/base.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/pipelines/base.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Modify the error message
Signed-off-by: yuanwu <yuan.wu@intel.com>

* Change message format.
Signed-off-by: yuanwu <yuan.wu@intel.com>

---------
Signed-off-by: yuanwu <yuan.wu@intel.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Safetensors serialization by default

* First pass on the tests

* Second pass on the tests

* Third pass on the tests

* Fix TF weight loading from TF-format safetensors

* Specific encoder-decoder fixes for weight crossloading

* Add VisionEncoderDecoder fixes for TF too

* Change filename test for pt-to-tf

* One missing fix for TFVisionEncoderDecoder

* Fix the other crossload test

* Support for flax + updated tests

* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Sanchit's comments

* Sanchit's comments 2

* Nico's comments

* Fix tests

* cleanup

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

---------
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fix number of minimal calls to the Hub with peft integration

* Alternate design

* And this way?

* Revert

* Nits to fix

* Add util

* Print when changes are made

* Add list to ignore

* Add more rules

* Manual fixes

* deal with kwargs

* deal with enum defaults

* avoid many digits for floats

* Manual fixes

* Fix regex

* Fix regex

* Auto fix

* Style

* Apply script

* Add ignored list

* Add check that templates are filled

* Adding to CI checks

* Add back semi-fix

* Ignore more objects

* More auto-fixes

* Ignore missing objects

* Remove temp semi-fix

* Fixes

* Update src/transformers/models/pvt/configuration_pvt.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update utils/check_docstrings.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/utils/quantization_config.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Deal with float defaults

* Fix small defaults

* Address review comment

* Treat

* Post-rebase cleanup

* Address review comment

* Update src/transformers/models/deprecated/mctct/configuration_mctct.py
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

* Address review comment

---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

* update

* update

* update

* update

---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Save image_processor while saving pipeline (ImageSegmentationPipeline)

* Fix black issues

* revisit device check for pipeline

* let's raise an error.

* added compiled model support for inference

* linter

* Fix tests

* linter

* linter

* remove inference mode from pipelines

* Linter

---------
Co-authored-by: amarkov <alexander@inworld.ai>

* Avoid importing all models when instantiating a pipeline

* Remove sums that don't work

* fix str device issue

* fixup

* adapt from suggestions

* forward contrib credits from suggestions

* better fix

* added backward compatibility for older PT versions

* final fixes

* oops

* Attempting something with less branching.

---------
Co-authored-by: amyeroberts <amyeroberts@users.noreply.github.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Respect framework parameter

* Move check to pipeline()

* Add check inside infer_framework_load_model again

* fix sam test

* update pipeline typehint

expose safe_serialization argument of PreTrainedModel and TFPreTrainedModel in the save_pretrained of the pipeline api
Co-authored-by: Yessen Kanapin <yessen@deepinfra.com>

* Fix some docs what layerdrop does

* Update src/transformers/models/data2vec/configuration_data2vec_audio.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix more docs

---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* New TF version compatibility fixes

* Remove dummy print statement, move expand_1d

* Make a proper framework inference function

* Make a proper framework inference function

* ValueError -> TypeError

* cleanup

* updates

* more refactoring

* make style

* update inits

* support other inputs in base

* update based on review
Co-authored-by: Nicolas Patry <patry.nicolas@gmail.com>

* Update tests/pipelines/test_pipelines_automatic_mask_generation.py
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* update

* fixup

* TODO x and y to refactor, _h _w refactored here

* update docstring

* more nits

* style on these

* more doc fix

* rename variables

* update

* updates

* style

* update

* fix `_mask_to_rle_pytorch`

* styling

* fix ask to rle, wrong outputs

* add device arg

* update

* more updates, fix tets

* udpate

* update docstrings

* styling

* fixup

* add notebook on the docs

* update orginal sizes

* fix docstring

* updat condition on point_per-batch

* updates tests

* fix CI  test

* extend is required, append does not work!

* fixup

* fix CI tests

* whit pixels left

* address doc comments

* fix doc

* slow pipeline tests

* update auto init

* add revision

* make fixup

* update p!ipoeline tag when calling tests

* alphabeitcal order in inits

* fix copies

* last style nits

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* reformat docstring

* more reformat

* address most of the comments

* Update src/transformers/pipelines/mask_generation.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* final refactor

* Update src/transformers/models/sam/image_processing_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fixup and fix slow tests

* revert

---------
Co-authored-by: Nicolas Patry <patry.nicolas@gmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fix regression in pipeline when device=-1 is passed

* Add regression test

* add pipeline

* update init

* add zero shot to init

* update inits and correct checkpoints

* update base to support input features

* add tests

* Update src/transformers/pipelines/zero_shot_audio_classification.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/pipelines/zero_shot_audio_classification.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* update pieline code

* use tiny checkpoint

* nits and expected value with tiny model

* style

* last nit on tests values

* fix styling

* fix collate fn that was casting t float

* update

---------
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* v1 fix

* adapt from suggestions

* make style

* fix tests

* add gpu tests

* update docs

* fix other tests

* Apply suggestions from code review
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* better fix

* make fixup

* better example

* revert changes

* proposal

* more elegant solution

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

---------
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fixing the pipeline with image processor.

* Update the slow test.

* Using only the first image processor.

* Include exclusion mecanism for Image processor.

* Do not handle Gitconfig, deemed as a bug.

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove `conversational` changes. They are not supposed to be here.

* Address first row of comments.

* Remove OneFormer modifications.
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fixing #20783

* Update src/transformers/pipelines/base.py

* Fixing some tests.

* Fixup.

* Remove ffmpeg dep + a bit more relaxed for bigbird QA precision.

* Better dataset.

* Prevent failing on TF.

* Better condition. We can't use `can_use_iterator` since we cannot use it
directly.

* add torch_dtype attribute to Pipeline

* Use torch_dtype to cast input tensor type in AutomaticSpeechRecognitionPipeline

* Fix code quality

* Add TextGenerationPipeline fp16 test

* Fix code quality

* Remove useless require in tests
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Remove key word argument X from pipeline predict and transform methods

As __call__ of pipeline clasees require one positional argument, passing
the input as a keyword argument inside predict, transform methods, causing
__call__ to fail. Hence in this commit the keyword argument is modified
into positional argument.

* Implement basic tests for scikitcompat pipeline interface

* Seperate tests instead of running with parameterized based on framework as both frameworks will not be active at the same time

* [WIP] Skeleton of VisualQuestionAnweringPipeline extended to support LayoutLM-like models

* Fixup

* Use the full encoding

* Basic refactoring to DocumentQuestionAnsweringPipeline

* Cleanup

* Improve args, docs, and implement preprocessing

* Integrate OCR

* Refactor question_answering pipeline

* Use refactored QA code in the document qa pipeline

* Fix tests

* Some small cleanups

* Use a string type annotation for Image.Image

* Update encoding with image features

* Wire through the basic docs

* Handle invalid response

* Handle empty word_boxes properly

* Docstring fix

* Integrate Donut model

* Fixup

* Incorporate comments

* Address comments

* Initial incorporation of tests

* Address Comments

* Change assert to ValueError

* Comments

* Wrap `score` in float to make it JSON serializable

* Incorporate AutoModeLForDocumentQuestionAnswering changes

* Fixup

* Rename postprocess function

* Fix auto import

* Applying comments

* Improve docs

* Remove extra assets and add copyright

* Address comments
Co-authored-by: Ankur Goyal <ankur@impira.com>

* `pipeline` support for `device="mps"` (or any other string)

* Simplify `if` nesting

* Update src/transformers/pipelines/base.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix? @sgugger

* passing `attr=None` is not the same as not passing `attr` 🤯
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Adding a better error message when the model is improperly configured

within transformers.

* Update src/transformers/pipelines/__init__.py

* Black version.

* Overriding task aliases so that tokenizer+feature_extractor

values are correct.

* Fixing task aliases by overriding their names early

* X.

* Fixing feature-extraction.

* black again.

* Normalizing `translation` too.

* Fixing last few corner cases.

translation need to use its non normalized name (translation_XX_to_YY,
so that the task_specific_params are correctly overloaded).
This can be removed and cleaned up in a later PR.

`speech-encode-decoder` actually REQUIRES to pass a `tokenizer` manually
so the error needs to be discarded when the `tokenizer` is already
there.

* doc-builder fix.

* Fixing the real issue.

* Removing dead code.

* Do not import the actual config classes.

Comparisons like
version.parse(torch.__version__) > version.parse("1.6")
are True for torch==1.6.0+cu101 or torch==1.6.0+cpu

version.parse(version.parse(torch.__version__).base_version) are preferred (and available in pytorch_utils.py