GitLab

* Make forward pass work

* More improvements

* Remove unused imports

* Remove timm dependency

* Improve loss calculation of token classifier

* Fix most tests

* Add docs

* Add model integration test

* Make all tests pass

* Add LayoutLMv3FeatureExtractor

* Improve integration test + make fixup

* Add example script

* Fix style

* Add LayoutLMv3Processor

* Fix style

* Add option to add visual labels

* Make more tokenizer tests pass

* Fix more tests

* Make more tests pass

* Fix bug and improve docs

* Fix import of processors

* Improve docstrings

* Fix toctree and improve docs

* Fix auto tokenizer

* Move tests to model folder

* Move tests to model folder

* change default behavior add_prefix_space

* add prefix space for fast

* add_prefix_spcae set to True for Fast

* no space before `unique_no_split` token

* add test to hightligh special treatment of added tokens

* fix `test_batch_encode_dynamic_overflowing` by building a long enough example

* fix `test_full_tokenizer` with add_prefix_token

* Fix tokenizer integration test

* Make the code more readable

* Add tests for LayoutLMv3Processor

* Fix style

* Add model to README and update init

* Apply suggestions from code review

* Replace asserts by value errors

* Add suggestion by @ducviet00

* Add model to doc tests

* Simplify script

* Improve README

* a step ahead to fix

* Update pair_input_test

* Make all tokenizer tests pass - phew

* Make style

* Add LayoutLMv3 to CI job

* Fix auto mapping

* Fix CI job name

* Make all processor tests pass

* Make tests of LayoutLMv2 and LayoutXLM consistent

* Add copied from statements to fast tokenizer

* Add copied from statements to slow tokenizer

* Remove add_visual_labels attribute

* Fix tests

* Add link to notebooks

* Improve docs of LayoutLMv3Processor

* Fix reference to section
Co-authored-by: SaulLu <lucilesaul.com@gmail.com>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* [WIP] Add FLAVA model

This PR aims to add [FLAVA](ihttps://arxiv.org/abs/2112.04482) model to the transformers repo.

Following checklist delineates the list of things to be done for this PR
to be complete:

[x] Flava init
[x] Flava base models
[x] Flava layers
[x] Flava Configs
[x] Flava encoders
[x] Flava pretraining models
[ ] Flava classification/retrieval models (To be added in a separate PR)
[x] Documentation updates 
[x] Imports updates 
[x] Argstring updates
[x] Flava pretrained checkpoints 
[x] Flava tests
[x] Flava processors 
[x] Sanity check
[x] Lint

* First draft

* Add YolosForObjectDetection

* Make forward pass work

* Add mid position embeddings

* Add interpolation of position encodings

* Add expected values

* Add YOLOS to tests

* Add integration test

* Support tiny model as well

* Support all models in conversion script

* Remove mid_pe_size attribute

* Make more tests pass

* Add model to README and fix config

* Add copied from statements

* Rename base_model_prefix to vit

* Add missing YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP

* Apply suggestions from code review

* Apply more suggestions from code review

* Convert remaining checkpoints

* Improve docstrings

* Add YolosFeatureExtractor

* Add feature extractor to docs

* Add corresponding tests

* Fix style

* Fix docs

* Apply suggestion from code review

* Fix bad rebase

* Fix some more bad rebase

* Fix missing character

* Improve docs and variable names
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* First draft

* More improvements

* Add fusion blocks

* Make conversion script work for dpt_large

* Make conversion script work

* Improve implementation

* Improve conversion script

* Add DPTForSemanticSegmentation

* Make conversion work for semantic segmentation

* Add tests

* Remove print statements

* First draft

* Redesign neck

* Improve tests

* Improve implementation some more

* Make neck output list of tensors

* Improve neck and feature extractor

* Fix integration tests

* Make more tests pass

* Make all tests pass

* Add missing config archive map

* Add in_index attribute to make heads accept list of tensors

* Apply suggestions from code review

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply some more suggestions

* Add copied from statements

* Remove assert

* Apply suggestions from code review

* Apply suggestions from code review

* Remove DPTInterpolate in favor of nn.Upsample

* Add comments

* Apply suggestions from code review

* Apply suggestions from code review

* Add proposed design

* Update design

* Add DPTReassembleLayer

* Add DPTFeatureFusionStage

* Apply more suggestions from code review

* Apply suggestions from code review

* Apply suggestions from code review

* Fix rebase

* Update in_index and out_indices

* Fix conversion script

* Fix code quality

* Add model to toctree and use DepthEstimatorOutput

* Fix rebase

* Fix code examples

* Improve code

* Fix copied from statements

* Apply suggestions from code review

* Remove compute_loss method

* Apply suggestions from code review

* Fix documentation tests file

* Remove test.py file

* Improve doc example
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Niels Rogge <nielsrogge@nielss-mbp.home>

* 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

* First draft

* Fix logits calculation

* Improve tests

* Add copied from statements

* Fix base_model_prefix

* Improve implementation, upload new models

* Update design

* Fix integration test

* Add model to README and toctree

* Add document image

* Apply suggestions from code review

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add decoder_hidden_size attribute

* Update design of decoder

* Add DepthEstimatorOutput class

* Rename in_index to head_in_index and add feature extractor tests

* Apply suggestions from code review

* Apply suggestions from code review

* Update pretrained model name and add to doc tests

* Remove test.py script

* Update copied from statements and clean up
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* maskformer

* conflicts

* conflicts

* minor fixes

* feature extractor test fix

refactor MaskFormerLoss following conversation

MaskFormer related types should not trigger a module time import error

missed one

removed all the types that are not used

update config mapping

minor updates in the doc

resolved conversation that doesn't need a discussion

minor changes

resolved conversations

fixed DetrDecoder

* minor changes

minor changes

fixed mdx file

test feature_extractor return types

functional losses -> classes

removed the return type test for the feature extractor

minor changes + style + quality

* conflicts?

* rebase master

* readme

* added missing files

* deleded poolformers test that where in the wrong palce

* CI

* minor changes

* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* resolved conversations

* minor changes

* conversations

[Unispeech] Fix slow tests (#15818)

* remove soundfile old way of loading audio

* Adapt slow test

[Barthez Tokenizer] Fix saving (#15815)

[TFXLNet] Correct tf xlnet generate (#15822)

* [TFXLNet] Correct tf xlnet

* adapt test comment

Fix the push run (#15807)

Fix semantic segmentation pipeline test (#15826)

Fix dummy_inputs() to dummy_inputs in symbolic_trace doc (#15776)

Add model specific output classes to PoolFormer model docs (#15746)

* Added model specific output classes to poolformer docs

* Fixed Segformer typo in Poolformer docs

Adding the option to return_timestamps on pure CTC ASR models. (#15792)

* Adding the option to return_timestamps on pure CTC ASR models.

* Remove `math.prod` which was introduced in Python 3.8

* int are not floats.

* Reworking the PR to support "char" vs "word" output.

* Fixup!

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Quality.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

HFTracer.trace should use/return self.graph to be compatible with torch.fx.Tracer (#15824)

Fix tf.concatenate + test past_key_values for TF models (#15774)

* fix wrong method name tf.concatenate

* add tests related to causal LM / decoder

* make style and quality

* clean-up

* Fix TFBertModel's extended_attention_mask when past_key_values is provided

* Fix tests

* fix copies

* More tf.int8 -> tf.int32 in TF test template

* clean-up

* Update TF test template

* revert the previous commit + update the TF test template

* Fix TF template extended_attention_mask when past_key_values is provided

* Fix some styles manually

* clean-up

* Fix ValueError: too many values to unpack in the test

* Fix more: too many values to unpack in the test

* Add a comment for extended_attention_mask when there is past_key_values

* Fix TFElectra extended_attention_mask when past_key_values is provided

* Add tests to other TF models

* Fix for TF Electra test: add prepare_config_and_inputs_for_decoder

* Fix not passing training arg to lm_head in TFRobertaForCausalLM

* Fix tests (with past) for TF Roberta

* add testing for pask_key_values for TFElectra model
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

[examples/summarization and translation] fix readme (#15833)

Add ONNX Runtime quantization for text classification notebook (#15817)

Re-enable doctests for the quicktour (#15828)

* Re-enable doctests for the quicktour

* Re-enable doctests for task_summary (#15830)

* Remove &

Framework split model report (#15825)

Add TFConvNextModel (#15750)

* feat: initial implementation of convnext in tensorflow.

* fix: sample code for the classification model.

* chore: added checked for  from the classification model.

* chore: set bias initializer in the classification head.

* chore: updated license terms.

* chore: removed ununsed imports

* feat: enabled  argument during using drop_path.

* chore: replaced tf.identity with layers.Activation(linear).

* chore: edited default checkpoint.

* fix: minor bugs in the initializations.

* partial-fix: tf model errors for loading pretrained pt weights.

* partial-fix: call method updated

* partial-fix: cross loading of weights (4x3 variables to be matched)

* chore: removed unneeded comment.

* removed playground.py

* rebasing

* rebasing and removing playground.py.

* fix: renaming TFConvNextStage conv and layer norm layers

* chore: added initializers and other minor additions.

* chore: added initializers and other minor additions.

* add: tests for convnext.

* fix: integration tester class.

* fix: issues mentioned in pr feedback (round 1).

* fix: how output_hidden_states arg is propoagated inside the network.

* feat: handling of  arg for pure cnn models.

* chore: added a note on equal contribution in model docs.

* rebasing

* rebasing and removing playground.py.

* feat: encapsulation for the convnext trunk.

* Fix variable naming; Test-related corrections; Run make fixup

* chore: added Joao as a contributor to convnext.

* rebasing

* rebasing and removing playground.py.

* rebasing

* rebasing and removing playground.py.

* chore: corrected copyright year and added comment on NHWC.

* chore: fixed the black version and ran formatting.

* chore: ran make style.

* chore: removed from_pt argument from test, ran make style.

* rebasing

* rebasing and removing playground.py.

* rebasing

* rebasing and removing playground.py.

* fix: tests in the convnext subclass, ran make style.

* rebasing

* rebasing and removing playground.py.

* rebasing

* rebasing and removing playground.py.

* chore: moved convnext test to the correct location

* fix: locations for the test file of convnext.

* fix: convnext tests.

* chore: applied  sgugger's suggestion for dealing w/ output_attentions.

* chore: added comments.

* chore: applied updated quality enviornment style.

* chore: applied formatting with quality enviornment.

* chore: revert to the previous tests/test_modeling_common.py.

* chore: revert to the original test_modeling_common.py

* chore: revert to previous states for test_modeling_tf_common.py and modeling_tf_utils.py

* fix: tests for convnext.

* chore: removed output_attentions argument from convnext config.

* chore: revert to the earlier tf utils.

* fix: output shapes of the hidden states

* chore: removed unnecessary comment

* chore: reverting to the right test_modeling_tf_common.py.

* Styling nits
Co-authored-by: ariG23498 <aritra.born2fly@gmail.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

* minor changes

* doc fix in feature extractor

* doc

* typose

* removed detr logic from config

* removed detr logic from config

* removed num_labels

* small fix in the config

* auxilary -> auxiliary

* make style

* some test is failing

* fix a weird char in config prevending doc-builder

* retry to fix the doc-builder issue

* make style

* new try to fix the doc builder

* CI

* change weights to facebook
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: ariG23498 <aritra.born2fly@gmail.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

* Added all files, PoolFormerFeatureExtractor still failing tests

* Fixed PoolFormerFeatureExtractor not being able to import

* Completed Poolformer doc

* Applied Suggested fixes

* Fixed errors in modeling_auto.py

* Fix feature extractor, convert docs to Markdown, styling of code

* Remove PoolFormer from check_repo and fix integration test

* Remove Poolformer from check_repo

* Fixed configuration_poolformer.py docs and removed inference.py from poolformer

* Ran with black v22

* Added PoolFormer to _toctree.yml

* Updated poolformer doc

* Applied suggested fixes and added on README.md

* Did make fixup and make fix-copies, tests should pass now

* Changed PoolFormer weights conversion script name and fixed README

* Applied fixes in test_modeling_poolformer.py and modeling_poolformer.py

* Added PoolFormerFeatureExtractor to AutoFeatureExtractor API
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>

* First draft

* Add conversion script

* Improve conversion script

* Improve docs and implement tests

* Define model output class

* Fix tests

* Fix more tests

* Add model to README

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply more suggestions from code review

* Apply suggestions from code review

* Rename dims to hidden_sizes

* Fix equivalence test

* Rename gamma to gamma_parameter

* Clean up conversion script

* Add ConvNextFeatureExtractor

* Add corresponding tests

* Implement feature extractor correctly

* Make implementation cleaner

* Add ConvNextStem class

* Improve design

* Update design to also include encoder

* Fix gamma parameter

* Use sample docstrings

* Finish conversion, add center cropping

* Replace nielsr by facebook, make feature extractor tests smaller

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

* First commit

* Add conversion script

* Make conversion script work for base model

* More improvements

* Update conversion script, works for vqa

* Add indexing argument to meshgrid

* Make conversion script work for ViltForPreTraining

* Add ViltForPreTraining to docs

* Fix device issue

* Add processor

* Add MinMaxResize to feature extractor

* Implement call method of ViltProcessor

* Fix tests

* Add integration test

* Add loss calculation for VQA

* Improve tests

* Improve some more tests

* Debug tests

* Small improvements

* Add support for attention_mask

* Remove mask_it

* Add pixel_mask

* Add tests for ViltFeatureExtractor

* Improve tests

* Add ViltForNaturalLanguageVisualReasoning

* Add ViltForNaturalLanguageVisualReasoning to conversion script

* Minor fixes

* Add support for image_embeds, update docstrings to markdown

* Update docs to markdown

* Improve conversion script

* Rename ViltForPreTraining to ViltForMaskedLM

* Improve conversion script

* Convert docstrings to markdown

* Fix code example of retrieval model

* Properly convert masked language model

* Add integration test for nlvr

* Fix code quality

* Apply suggestions from code review

* Add copied from statements

* Fix pretrained_config_archive_map

* Fix docs

* Add model to README

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply more suggestions from code review

* Make code more readable

* Add ViltForNaturalLanguageVisualReasoning to the tests

* Rename ViltForVisualQuestionAnswering to ViltForQuestionAnswering

* Replace pixel_values_2 by single tensor

* Add hidden_states and attentions

* Fix one more test

* Fix all tests

* Update year

* Fix rebase issues

* Fix another rebase issue

* Remove ViltForPreTraining from auto mapping

* Rename ViltForImageRetrievalTextRetrieval to ViltForImageAndTextRetrieval

* Make it possible to use BertTokenizerFast in the processor

* Use BertTokenizerFast by default

* Rename ViltForNaturalLanguageVisualReasoning, define custom model output
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Better dummies

* See if this fixes the issue

* Fix quality

* Style

* Add doc for DummyObject

* First draft

* Style and remove mlm

* Make forward pass work

* More improvements

* More improvements

* Fix bug

* More improvements

* More improvements

* Add PerceiverTokenizer first draft

* Improve conversion script

* More improvements

* Make conversion script work for the encoder

* Make conversion script work with local pickle files

* Style & quality, fix-copies

* Add dummy input to conversion script

* Add absolute position embeddings to TextPreProcessor

* Make forward pass of encoder work

* More improvements

* Move text preprocessor to separate script

* More improvements

* More improvements

* Add post processor

* Make MLM model work

* Style

* Add PerceiverForMaskedLM

* Add PerceiverImagePreprocessor

* Make style

* Make PerceiverForImageClassification work

* More improvements

* More improvements

* Use tokenizer in conversion script

* Use PerceiverForMaskedLM in conversion script

* Define custom PerceiverModelOutput

* Improve PerceiverAttention to make it work for both MLM and image classification

* More improvements

* More improvements

* More improvements to the conversion script

* Make conversion script work for both MLM and image classification

* Add PerceiverFeatureExtractor

* More improvements

* Style and quality

* Add center cropping

* Fix bug

* Small fix

* Add print statement

* Fix bug in image preprocessor

* Fix bug with conversion script

* Make output position embeddings an nn.Parameter layer instead of nn.Embedding

* Comment out print statements

* Add position encoding classes

* More improvements

* Use position_encoding_kwargs

* Add PerceiverForImageClassificationFourier

* Make style & quality

* Add PerceiverForImageClassificationConvProcessing

* Style & quality

* Add flow model

* Move processors to modeling file

* Make position encodings modular

* Make basic decoder use modular position encodings

* Add PerceiverForOpticalFlow to conversion script

* Add AudioPreprocessor

* Make it possible for the basic decoder to use Fourier position embeddings

* Add PerceiverForMultimodalAutoencoding

* Improve model for optical flow

* Improve _build_network_inputs method

* Add print statement

* Fix device issue

* Fix device of Fourier embeddings

* Add print statements for debugging

* Add another print statement

* Add another print statement

* Add another print statement

* Add another print statement

* Improve PerceiverAudioPreprocessor

* Improve conversion script for multimodal modal

* More improvements

* More improvements

* Improve multimodal model

* Make forward pass multimodal model work

* More improvements

* Improve tests

* Fix some more tests

* Add output dataclasses

* Make more tests pass

* Add print statements for debuggin

* Add tests for image classification

* Add PerceiverClassifierOutput

* More improvements

* Make more tests pass for the optical flow model

* Make style & quality

* Small improvements

* Don't support training for optical flow model for now

* Fix _prepare_for_class for tests

* Make more tests pass, add some docs

* Add multimodal model to tests

* Minor fixes

* Fix tests

* Improve conversion script

* Make fixup

* Remove pos_dim argument

* Fix device issue

* Potential fix for OOM

* Revert previous commit

* Fix test_initialization

* Add print statements for debugging

* Fix print statement

* Add print statement

* Add print statement

* Add print statement

* Add print statement

* Add print statement

* Add print statement

* Remove need for output_shape

* Comment out output_shape

* Remove unnecessary code

* Improve docs

* Fix make fixup

* Remove PerceiverTextProcessor from init

* Improve docs

* Small improvement

* Apply first batch of suggestions from code review

* Apply more suggestions from code review

* Update docstrings

* Define dicts beforehand for readability

* Rename task to architecture in conversion script, include PerceiverModel in tests

* Add print statements for debugging

* Fix tests on GPU

* Remove preprocessors, postprocessors and decoders from main init

* Add integration test

* Fix docs

* Replace einops by torch

* Update for new docs frontend

* Rename PerceiverForImageClassification

* Improve docs

* Improve docs

* Improve docs of PerceiverModel

* Fix some more tests

* Improve center_crop

* Add PerceiverForSequenceClassification

* Small improvements

* Fix tests

* Add integration test for optical flow model

* Clean up

* Add tests for tokenizer

* Fix tokenizer by adding special tokens properly

* Fix CI

* First draft

* More improvements

* Improve conversion script

* Fix init weights for layer norm

* Fix correct model for conversion script

* Don't tie input and output embeddings

* Add print statements for debugging

* Add print statements for debugging

* Fix vocab size of model

* Improve documentation, remove fast tokenizer

* Add ImageGPTForImageClassification, improve docs

* Fix docs issue

* Set verbosity level back to info

* Improve tests

* Fix tests and add figure

* Delete tokenizer file

* Remove ImageGPTTokenizer from init files

* Remove ImageGPTLayer from init files

* Remove ImageGPT tokenizer from docs

* First draft of ImageGPTFeatureExtractor

* Fix typo

* Fix bug

* More improvements

* Apply suggestions from code review, add tests for feature extractor

* Fix layernorm

* Update save_pretrained method

* Fix issue

* Make all tests of ImageGPTFeatureExtractor pass

* Update code examples

* Rename model inputs to pixel_values

* Improve code examples

* Update init_weights to post_init

* Fix post_init

* Add LayoutXLMTokenizer and LayoutXLMTokenizerFast

* Fix styling issues

* Fix more styling issues

* Fix more styling issues

* Fix docstring

* Fix unit tests

* Fix docs

* Fix unit tests

* Fix typos and styling issues

* Fix styling issues

* Fix docstring

* Make all tests of test_tokenization_layoutxlm pass

* Add LayoutXLMProcessor

* Make fixup

* Make all LayoutXLMProcessor tests pass

* Minor fixes

* Leave LayoutLMv2Processor tests unchanged

* Fix code quality

* Move LayoutXLM tokenizers and processor to separate folder

* Fix code quality

* Apply suggestions from code review

* Replace assertions by value errors

* Remove methods from fast tokenizer
Co-authored-by: King Yiu Suen <kingyiusuen@gmail.com>

* First draft

* Make style & quality

* Improve conversion script

* Add print statement to see actual slice

* Make absolute tolerance smaller

* Fix image classification models

* Add post_process_semantic method

* Disable padding

* Improve conversion script

* Rename to ForSemanticSegmentation, add integration test, remove post_process methods

* Improve docs

* Fix code quality

* Fix feature extractor tests

* Fix tests for image classification model

* Delete file

* Add is_torch_available to feature extractor

* Improve documentation of feature extractor methods

* Apply suggestions from @sgugger's code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply some more suggestions of code review

* Rebase with master

* Fix rebase issues

* Make sure model only outputs hidden states when the user wants to

* Apply suggestions from code review

* Add pad method

* Support padding of 2d images

* Add print statement

* Add print statement

* Move padding method to SegformerFeatureExtractor

* Fix issue

* Add casting of segmentation maps

* Add test for padding

* Add small note about padding
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* First commit

* Make style

* Fix dummy objects

* Add Detectron2 config

* Add LayoutLMv2 pooler

* More improvements, add documentation

* More improvements

* Add model tests

* Add clarification regarding image input

* Improve integration test

* Fix bug

* Fix another bug

* Fix another bug

* Fix another bug

* More improvements

* Make more tests pass

* Make more tests pass

* Improve integration test

* Remove gradient checkpointing and add head masking

* Add integration test

* Add LayoutLMv2ForSequenceClassification to the tests

* Add LayoutLMv2ForQuestionAnswering

* More improvements

* More improvements

* Small improvements

* Fix _LazyModule

* Fix fast tokenizer

* Move sync_batch_norm to a separate method

* Replace dummies by requires_backends

* Move calculation of visual bounding boxes to separate method + update README

* Add models to main init

* First draft

* More improvements

* More improvements

* More improvements

* More improvements

* More improvements

* Remove is_split_into_words

* More improvements

* Simply tesseract - no use of pandas anymore

* Add LayoutLMv2Processor

* Update is_pytesseract_available

* Fix bugs

* Improve feature extractor

* Fix bug

* Add print statement

* Add truncation of bounding boxes

* Add tests for LayoutLMv2FeatureExtractor and LayoutLMv2Tokenizer

* Improve tokenizer tests

* Make more tokenizer tests pass

* Make more tests pass, add integration tests

* Finish integration tests

* More improvements

* More improvements - update API of the tokenizer

* More improvements

* Remove support for VQA training

* Remove some files

* Improve feature extractor

* Improve documentation and one more tokenizer test

* Make quality and small docs improvements

* Add batched tests for LayoutLMv2Processor, remove fast tokenizer

* Add truncation of labels

* Apply suggestions from code review

* Improve processor tests

* Fix failing tests and add suggestion from code review

* Fix tokenizer test

* Add detectron2 CI job

* Simplify CI job

* Comment out non-detectron2 jobs and specify number of processes

* Add pip install torchvision

* Add durations to see which tests are slow

* Fix tokenizer test and make model tests smaller

* Frist draft

* Use setattr

* Possible fix

* Proposal with configuration

* First draft of fast tokenizer

* More improvements

* Enable fast tokenizer tests

* Make more tests pass

* Make more tests pass

* More improvements

* Addd padding to fast tokenizer

* Mkae more tests pass

* Make more tests pass

* Make all tests pass for fast tokenizer

* Make fast tokenizer support overflowing boxes and labels

* Add support for overflowing_labels to slow tokenizer

* Add support for fast tokenizer to the processor

* Update processor tests for both slow and fast tokenizers

* Add head models to model mappings

* Make style & quality

* Remove Detectron2 config file

* Add configurable option to label all subwords

* Fix test

* Skip visual segment embeddings in test

* Use ResNet-18 backbone in tests instead of ResNet-101

* Proposal

* Re-enable all jobs on CI

* Fix installation of tesseract

* Fix failing test

* Fix index table

* Add LayoutXLM doc page, first draft of code examples

* Improve documentation a lot

* Update expected boxes for Tesseract 4.0.0 beta

* Use offsets to create labels instead of checking if they start with ##

* Update expected boxes for Tesseract 4.1.1

* Fix conflict

* Make variable names cleaner, add docstring, add link to notebooks

* Revert "Fix conflict"

This reverts commit a9b46ce9afe47ebfcfe7b45e6a121d49e74ef2c5.

* Revert to make integration test pass

* Apply suggestions from @LysandreJik's review

* Address @patrickvonplaten's comments

* Remove fixtures DocVQA in favor of dataset on the hub
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* 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>

* 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>

* begin second draft

* fix import, style

* add loss

* fix embeds, logits_scale, and projection

* fix imports

* add conversion script

* add feature_extractor and processor

* style

* add tests for tokenizer, extractor and processor

* add vision model tests

* add weight init

* add more tests

* fix save_load  test

* model output, dosstrings, causal mask

* config doc

* add clip model tests

* return dict

* bigin integration test

* add integration tests

* fix-copies

* fix init

* Clip => CLIP

* fix module name

* docs

* fix doc

* output_dim => projection_dim

* fix checkpoint names

* remoe fast tokenizer file

* fix conversion script

* fix tests, quality

* put causal mask on device

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix attribute test

* style

* address sylvains comments

* style

* fix docstrings

* add qucik_gelu in activations, docstrings

* clean-up attention test

* fix act fun

* fix config

* fix torchscript tests

* even batch_size

* remove comment

* fix ouput tu_tuple

* fix save load tests

* fix add tokens test

* add fast tokenizer

* update copyright

* new processor API

* fix docs

* docstrings

* docs

* fix doc

* fix doc

* fix tokenizer

* fix import in doc example

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* check types of config

* valhalla => openai

* load image using url

* fix test

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

* 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

* Replaces requires_xxx by one generic method

* Quality and update check_dummies

* Fix inits check

* Post-merge cleanup

* 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>

* Add ImageFeatureExtractionMixin

* Add dummy vision objects

* Add require_vision

* Add tests

* Fix test