GitLab

* add roc_bert

* update roc_bert readme

* code style

* change name and delete unuse file

* udpate model file

* delete unuse log file

* delete tokenizer fast

* reformat code and change model file path

* add RocBertForPreTraining

* update docs

* delete wrong notes

* fix copies

* fix make repo-consistency error

* fix files are not present in the table of contents error

* change RocBert -> RoCBert

* add doc, add detail test
Co-authored-by: weiweishi <weiweishi@tencent.com>

* Add first draft

* Update conversion script

* Improve conversion script

* Improve conversion script some more

* Add conditional embeddings

* Add initial decoder

* Fix activation function of decoder

* Make decoder outputs match original implementation

* Make decoder outputs match original implementation

* Add more copied from statements

* Improve model outputs

* Fix auto tokenizer file

* Fix more tests

* Add test

* Improve README and docs, improve conditional embeddings

* Fix more tests

* Remove print statements

* Remove initial embeddings

* Improve conversion script

* Add interpolation of position embeddings

* Finish addition of interpolation of position embeddings

* Add support for refined checkpoint

* Fix refined checkpoint

* Remove unused parameter

* Improve conversion script

* Add support for training

* Fix conversion script

* Add CLIPSegFeatureExtractor

* Fix processor

* Fix CLIPSegProcessor

* Fix conversion script

* Fix most tests

* Fix equivalence test

* Fix README

* Add model to doc tests

* Use better variable name

* Convert other checkpoint as well

* Update config, add link to paper

* Add docs

* Update organization

* Replace base_model_prefix with clip

* Fix base_model_prefix

* Fix checkpoint of config

* Fix config checkpoint

* Remove file

* Use logits for output

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

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

* Add contrastive search

* Update defaults and logic to match old FE

* Use docker run rest values

* POC

* For more CLIP-like models
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix esm lm head test

* make fixup

* [Whisper Tokenizer] Make more user-friendly

* use property

* make indexing rigorous

* small clean-up

* tests

* skip seq2seq tests

* remove multilingual arg

* reorder args

* collapse to one function
Co-authored-by: ArthurZucker <arthur@huggingface.co>

* option to override attributes
Co-authored-by: ArthurZucker <arthur@huggingface.co>

* add to docs

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

* make comment more clear
Co-authored-by: sgugger <sylvain@huggingface.co>

* don't add special tokens in get_decoder_prompt_ids

* add test for set_prefix_tokens
Co-authored-by: ArthurZucker <arthur@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: sgugger <sylvain@huggingface.co>

🚨 🚨 🚨 Fix Issue 15003: SentencePiece Tokenizers Not Adding Special Tokens in `convert_tokens_to_string` (#15775)

* Add test for SentencePiece not adding special tokens to strings

* Add SentencePieceStringConversionMixin to fix issue 15003

* Fix conversion from tokens to string for most SentencePiece tokenizers

Tokenizers fixed:
- AlbertTokenizer
- BarthezTokenizer
- CamembertTokenizer
- FNetTokenizer
- M2M100Tokenizer
- MBart50Tokenizer
- PegasusTokenizer
- Speech2TextTokenizer

* Fix MarianTokenizer, adjust SentencePiece test to accomodate vocab

* Fix DebertaV2Tokenizer

* Ignore LayoutXLMTokenizer in SentencePiece string conversion test

* Run 'make style' and 'make quality'

* Clean convert_tokens_to_string test

Instead of explicitly ignoring LayoutXLMTokenizer in the test,
override the test in LayoutLMTokenizationTest and do nothing in it.

* Remove commented out code

* Improve robustness of convert_tokens_to_string test

Instead of comparing lengths of re-tokenized text and input_ids,
check that converting all special tokens to string yields a string
with all special tokens.

* Inline and remove SentencePieceStringConversionMixin

The convert_tokens_to_string method is now implemented
in each relevant SentencePiece tokenizer.

* Run 'make style' and 'make quality'

* Revert removal of space in convert_tokens_to_string

* Remove redundant import

* Revert test text to original

* Uncomment the lowercasing of the reverse_text variable

* Mimic Rust tokenizer behavior for tokenizers

- Albert
- Barthez
- Camembert
- MBart50
- T5

* Fix accidentally skipping test in wrong tokenizer

* Add test for equivalent Rust and slow tokenizer behavior

* Override _decode in BigBirdTokenizer to mimic Rust behavior

* Override _decode in FNetTokenizer to mimic Rust behavior

* Override _decode in XLNetTokenizer to mimic Rust behavior

* Remove unused 're' import

* Update DebertaV2Tokenizer to mimic Rust tokenizer

* Deberta tokenizer now behaves like Albert and its `convert_tokens_to_string` is not tested.

* Ignore problematic tests in Deberta V2

* Add comment on why the Deberta V2 tests are skipped

* part 1

* part 2

* part 3

* fix

* For CANINE

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

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

* Add CLIP image processor

* Crop size as dict too

* Update warning

* Actually use logger this time

* Normalize doesn't change dtype of input

* Add perceiver image processor

* Tidy up

* Add DPT image processor

* Add Vilt image processor

* Tidy up

* Add poolformer image processor

* Tidy up

* Add LayoutLM v2 and v3 imsge processors

* Tidy up

* Add Flava image processor

* Tidy up

* Add deit image processor

* Tidy up

* Add ConvNext image processor

* Tidy up

* Add levit image processor

* Add segformer image processor

* Add in post processing

* Fix up

* Add ImageGPT image processor

* Fixup

* Add mobilevit image processor

* Tidy up

* Add postprocessing

* Fixup

* Add VideoMAE image processor

* Tidy up

* Add ImageGPT image processor

* Fixup

* Add ViT image processor

* Tidy up

* Add beit image processor

* Add mobilevit image processor

* Tidy up

* Add postprocessing

* Fixup

* Fix up

* Fix flava and remove tree module

* Fix image classification pipeline failing tests

* Update feature extractor in trainer scripts

* Update pad_if_smaller to accept tuple and int size

* Update for image segmentation pipeline

* Update src/transformers/models/perceiver/image_processing_perceiver.py
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>

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

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

* PR comments - docstrings; remove accidentally added resize; var names

* Update docstrings

* Add exception if size is not in the right format

* Fix exception check

* Fix up

* Use shortest_edge in tuple in script
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Use beam search functionality; Add extra outputs and test

* Add full tests for contrastive search

* Add error message on unconventional cache format

* initial commit

* First draft that gets outputs without crashing!

* Add all the ported openfold dependencies

* testing

* Restructure config files for ESMFold

* Debugging to find output discrepancies

* Mainly style

* Make model runnable without extra deps

* Remove utils and merge them to the modeling file

* Use correct gelu and remove some debug prints

* More cleanup

* Update esm docs

* Update conversion script to support ESMFold properly

* Port some top-level changes from ESMFold repo

* Expand EsmFold docstrings

* Make attention_mask optional (default to all 1s)

* Add inference test for ESMFold

* Use config and not n kwargs

* Add modeling output class

* Remove einops

* Remove chunking in ESM FFN

* Update tests for ESMFold

* Quality

* REpo consistency

* Remove tree dependency from ESMFold

* make fixup

* Add an error in case my structure map function breaks later

* Remove needless code

* Stop auto-casting the LM to float16 so CPU tests pass

* Stop auto-casting the LM to float16 so CPU tests pass

* Final test updates

* Split test file

* Copyright and quality

* Unpin PyTorch to see built doc

* Fix config file to_dict() method

* Add some docstrings to the output

* Skip TF checkpoint tests for ESM until we reupload those

* make fixup

* More docstrings

* Unpin to get even with main

* Flag example to write
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

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

* Add postprocessing methods

* Update docs

* Add fix

* Add test

* Add test for deformable detr postprocessing

* Add post processing methods for segmentation

* Update code examples

* Add post_process to make the pipeline work

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

* Support segformer fx

* Add fx_compatible attribute to test_modeling_segformer.py

* Update glpn model (fx support)

glpn model was copied from segformer.

* Update utils/fx.py | add semantic-segmentation

for SegformerForSemanticSegmentation model

* Fix minor import order(isort)

* Add random input generation for segformer fx
Co-authored-by: noelbird <lduldu00228@gmail.com>

* Fix tests when running on GPU

* Fix tests that require mp.set_start_method

* Add pegasus_x

* ViTMSN

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

* Support for Vilt in v1.9

* Skip if not higher or equal than 1.10

* Move test :)

* I am bad at python

* Update expected values

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

* Run some TF Whisper tests in subprocesses to avoid GPU OOM
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix panoptic segmentation and pipeline
* Update ImageSegmentationPipeline tests and reenable test_small_model_pt
* Resolve backward compatibility issues

* support sentencepiece for bertjapanesetokenizer

* add test vocab file for sentencepiece, bertjapanesetokenizer

* make BasicTokenizer be identical to transformers.models.bert.tokenization_bert.BasicTokenizer

* fix missing of \n in comment

* fix init argument missing in tests

* make spm_file be optional, exclude spiece.model from tests/fixtures, and add description comments

* make comment length less than 119

* apply doc style check

* First step of PT->TF for composite models

* Update the tests

* For VisionEncoderDecoderModel

* Fix

* Fix

* Add comment

* Fix

* clean up import

* Save memory

* For (TF)EncoderDecoderModel

* For (TF)EncoderDecoderModel
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Clean up deprecation warnings

Notes:
Changed some strings in tests to raw strings, which will change the literal content of the strings as they are fed into whatever machine handles them.
Test cases for past in the past/past_key_values switch changed/removed due to warning of impending removal

* Add PILImageResampling abstraction for PIL.Image.Resampling

* First draft

* Add conversion script

* Make conversion work

* Upload checkpoints

* Add final fixes

* Revert changes of conditional and deformable detr

* Fix toctree, add and remove copied from

* Use model type

* Improve docs

* Improve code example

* Update copies

* Add copied formt

* Don't update conditional detr

* Don't update deformable detr

* [Wav2Vec2] Allow user-managed Pool in Wav2Vec2ProcessorWithLM.batch_decode

* [Wav2Vec2] Add user-managed LM's pool tests and usage examples

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

* [Wav2Vec2] Fix hyperlink references
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Improve DETR models

* Fix Deformable DETR loss and matcher

* Fixup

* Fix integration tests

* Improve variable names

* Apply suggestion

* Fix copies

* Fix DeformableDetrLoss

* Make Conditional DETR copy from Deformable DETR

* Copy from deformable detr's hungarian matcher

* Fix bug

* Partial TF port for ESM model

* Add ESM-TF tests

* Add the various imports for TF-ESM

* TF weight conversion almost ready

* Stop ignoring the decoder weights in PT

* Add tests and lots of fixes

* fix-copies

* Fix imports, add model docs

* Add get_vocab() to tokenizer

* Fix vocab links for pretrained files

* Allow multiple inputs with a sep

* Use EOS as SEP token because ESM vocab lacks SEP

* Correctly return special tokens mask from ESM tokenizer

* make fixup

* Stop testing unsupported embedding resizing

* Handle TF bias correctly

* Skip all models with slow tokenizers in the token classification test

* Fixing the batch/unbatcher of pipelines to accomodate the `None` being

passed around.

* Fixing pipeline bug caused by slow tokenizer  being different.

* Update src/transformers/models/esm/modeling_tf_esm.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/esm/modeling_tf_esm.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/esm/modeling_tf_esm.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update set_input_embeddings and the copyright notices
Co-authored-by: Your Name <you@example.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* add suport for non fast tf bert tokenizer

* add tests for non fast tf bert tokenizer

* fix fast bert tf tokenizer flag

* double tokenizers list on tf tokenizers test to aovid breaking zip on test output equivalence

* reformat code with black to comply with code quality checks

* trigger ci

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

* [Whisper] Don't return attention mask in feat extractor

* remove attention mask from test

* fix failing tests

* quality

* [Whisper] Freeze params of encoder

* add tests

* return None to avoid recursive call

* Give error

* Give error

* Add test

* More tests

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

* Add a decorator for flaky tests

* Quality

* Don't break the rest

* Address review comments

* Fix test name

* Fix typo and print to stderr

* Fix XCLIP doc tests

* Add model to doc test list

* Fix tests