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* Update old existing feature extractor references

* Typo

* Apply suggestions from code review

* Apply suggestions from code review

* Apply suggestions from code review

* Address comments from review - update 'feature extractor'
Co-authored by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

Revert "Fix gradient checkpointing + fp16 autocast for most models (#24247)"

This reverts commit 285a4801.

* fix gc bug

* continue PoC on OPT

* fixes

* :exploding_head:

* fix tests

* remove pytest.mark

* fixup

* forward contrib credits from discussions

* forward contrib credits from discussions

* reverting changes on untouched files.

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Co-authored-by: zhaoqf123 <zhaoqf123@users.noreply.github.com>
Co-authored-by: 7eu7d7 <7eu7d7@users.noreply.github.com>

* Add PipelineTesterMixin

* remove class PipelineTestCaseMeta

* move validate_test_components

* Add for ViT

* Add to SPECIAL_MODULE_TO_TEST_MAP

* style and quality

* Add feature-extraction

* update

* raise instead of skip

* add tiny_model_summary.json

* more explicit

* skip tasks not in mapping

* add availability check

* Add Copyright

* A way to diable irrelevant tests

* update with main

* remove disable_irrelevant_tests

* skip tests

* better skip message

* better skip message

* Add all pipeline task tests

* revert

* Import PipelineTesterMixin

* subclass test classes with PipelineTesterMixin

* Add pipieline_model_mapping

* Fix import after adding pipieline_model_mapping

* Fix style and quality after adding pipieline_model_mapping

* Fix one more import after adding pipieline_model_mapping

* Fix style and quality after adding pipieline_model_mapping

* Fix test issues

* Fix import requirements

* Fix mapping for MobileViTModelTest

* Update

* Better skip message

* pipieline_model_mapping could not be None

* Remove some PipelineTesterMixin

* Fix typo

* revert tests_fetcher.py

* update

* rename

* revert

* Remove PipelineTestCaseMeta from ZeroShotAudioClassificationPipelineTests

* style and quality

* test fetcher for all pipeline/model tests

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

* return post-processed segmentations as list, add test
* use torch to resize logits
* fix assertion error if no target_size is specified

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

* Improve vision models

* Add a lot of improvements

* Remove to_2tuple from swin tests

* Fix TF Swin

* Fix more tests

* Fix copies

* Improve more models

* Fix ViTMAE test

* Add channel check for TF models

* Add proper channel check for TF models

* Apply suggestion from code review

* Apply suggestions from code review

* Add channel check for Flax models, apply suggestion

* Fix bug

* Add tests for greyscale images

* Add test for interpolation of pos encodigns
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* move test model folders (TODO: fix imports and others)

* fix (potentially partially) imports (in model test modules)

* fix (potentially partially) imports (in tokenization test modules)

* fix (potentially partially) imports (in feature extraction test modules)

* fix import utils.test_modeling_tf_core

* fix path ../fixtures/

* fix imports about generation.test_generation_flax_utils

* fix more imports

* fix fixture path

* fix get_test_dir

* update module_to_test_file

* fix get_tests_dir from wrong transformers.utils

* update config.yml (CircleCI)

* fix style

* remove missing imports

* update new model script

* update check_repo

* update SPECIAL_MODULE_TO_TEST_MAP

* fix style

* add __init__

* update self-scheduled

* fix add_new_model scripts

* check one way to get location back

* python setup.py build install

* fix import in test auto

* update self-scheduled.yml

* update slack notification script

* Add comments about artifact names

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

* Clean up tests

* Make fixup
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* Improve code

* Fix bugs

* Fix another bug

* Clean up DTP as well

* Update DPT model outputs
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* update _create_and_check_torchscript

* Enable test_torchscript

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

* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit

* Update expected slices for pillow > 9

* Add expected slices depending on pillow version

* Add different slices depending on pillow version for other models
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* Revert changes in logit size for semantic segmentation models

* Address review comments

* Per-folder tests reorganization
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* Standardize instance segmentation models outputs

* Rename output

* Update src/transformers/modeling_outputs.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add legacy argument to the config and model forward

* Update src/transformers/models/beit/modeling_beit.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Copy fix in Segformer
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add 'with torch.no_grad()' to BEiT integration test forward pass

* Fix inconsistent use of tabs and spaces in indentation

* Improve tests

* Install vision for tf tests

* Fix gradient_checkpointing backward compatibility

* Remove needless line

* make sure mask prob is big enough and length small enough

* Fix tests
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* Add first draft

* Make forward pass work

* Improve conversion script

* Add notebook that checks if it works

* Add BeitForSemanticSegmentation to the tests

* More improvements

* Make BeitForSemanticSegmentation consistent with Segformer

* Small bug fix

* Add BeitForSemanticSegmentation to docs

* Make sure model doesn't output hidden states when the user doesn't want to

* Make it possible to convert the large model

* Fix issue

* Fix conversion script for large model

* Add auxiliary_head option to semantic segmentation model

* Apply suggestions from @sgugger's review

* Apply suggestions from code review

* Fix failing test
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Make gradient_checkpointing a training argument

* Update src/transformers/modeling_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Update src/transformers/configuration_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Fix tests

* Style

* document Gradient Checkpointing as a performance feature

* Small rename

* PoC for not using the config

* Adapt BC to new PoC

* Forgot to save

* Rollout changes to all other models

* Fix typo
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* First pass

* Fix docs of bool_masked_pos

* Add integration script

* Fix docstring

* Add integration test for BeitForMaskedImageModeling

* Remove file

* Fix docs

* First pass

* Make conversion script work

* Improve conversion script

* Fix bug, conversion script working

* Improve conversion script, implement BEiTFeatureExtractor

* Make conversion script work based on URL

* Improve conversion script

* Add tests, add documentation

* Fix bug in conversion script

* Fix another bug

* Add support for converting masked image modeling model

* Add support for converting masked image modeling

* Fix bug

* Add print statement for debugging

* Fix another bug

* Make conversion script finally work for masked image modeling models

* Move id2label for datasets to JSON files on the hub

* Make sure id's are read in as integers

* Add integration tests

* Make style & quality

* Fix test, add BEiT to README

* Apply suggestions from @sgugger's review

* Apply suggestions from code review

* Make quality

* Replace nielsr by microsoft in tests, add docs

* Rename BEiT to Beit

* Minor fix

* Fix docs of BeitForMaskedImageModeling
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Expose get_config() on ModelTesters

* Typo

* consistent nn. and nn.functional: p3 templates

* restore

* Squash all commits of modeling_detr_v7 branch into one

* Improve docs

* Fix tests

* Style

* Improve docs some more and fix most tests

* Fix slow tests of ViT, DeiT and DETR

* Improve replacement of batch norm

* Restructure timm backbone forward

* Make DetrForSegmentation support any timm backbone

* Fix name of output

* Address most comments by @LysandreJik

* Give better names for variables

* Conditional imports + timm in setup.py

* Address additional comments by @sgugger

* Make style, add require_timm and require_vision to testsé

* Remove train_backbone attribute of DetrConfig, add methods to freeze/unfreeze backbone

* Add png files to fixtures

* Fix type hint

* Add timm to workflows

* Add `BatchNorm2d` to the weight initialization

* Fix retain_grad test

* Replace model checkpoints by Facebook namespace

* Fix name of checkpoint in test

* Add user-friendly message when scipy is not available

* Address most comments by @patrickvonplaten

* Remove return_intermediate_layers attribute of DetrConfig and simplify Joiner

* Better initialization

* Scipy is necessary to get sklearn metrics

* Rename TimmBackbone to DetrTimmConvEncoder and rename DetrJoiner to DetrConvModel

* Make style

* Improve docs and add 2 community notebooks
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* First draft of deit

* More improvements

* Remove DeiTTokenizerFast from init

* Conversion script works

* Add DeiT to ViT conversion script

* Add tests, add head model, add support for deit in vit conversion script

* Update model checkpoint names

* Update image_mean and image_std, set resample to bicubic

* Improve docs

* Docs improvements

* Add DeiTForImageClassificationWithTeacher to init

* Address comments by @sgugger

* Improve feature extractors

* Make fix-copies

* Minor fixes

* Address comments by @patil-suraj

* All models uploaded

* Fix tests

* Remove labels argument from DeiTForImageClassificationWithTeacher

* Fix-copies, style and quality

* Fix tests

* Fix typo

* Multiple docs improvements

* More docs fixes

* Squash all commits into one

* Update ViTFeatureExtractor to use image_utils instead of torchvision

* Remove torchvision and add Pillow

* Small docs improvement

* Address most comments by @sgugger

* Fix tests

* Clean up conversion script

* Pooler first draft

* Fix quality

* Improve conversion script

* Make style and quality

* Make fix-copies

* Minor docs improvements

* Should use fix-copies instead of manual handling

* Revert "Should use fix-copies instead of manual handling"

This reverts commit fd4e591bce4496d41406425c82606a8fdaf8a50b.

* Place ViT in alphabetical order
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>