GitLab

torch_xla currently has its own synchronization primitives, so use
xm.rendezvous(tag) instead.

* fix_torch_device_generate_test

* remove @

* fix test

* fix_torch_device_generate_test

* remove @

* upload

* finish doc

* Apply suggestions from code review
Co-authored-by: Omar Sanseviero <osanseviero@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* finish
Co-authored-by: Omar Sanseviero <osanseviero@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* add a test for a WordLevel tokenizer

* adapt common test to new tokenizer

* fix_torch_device_generate_test

* remove @

* start flax wav2vec2

* save intermediate

* forward pass has correct shape

* add weight norm

* add files

* finish ctc

* make style

* finish gumbel quantizer

* correct docstrings

* correct some more files

* fix vit

* finish quality

* correct tests

* correct docstring

* correct tests

* start wav2vec2 pretraining script

* save intermediate

* start pretraining script

* finalize pretraining script

* finish

* finish

* small typo

* finish

* correct

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* make style

* push
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* add philosophy doc

* fix typos

* update doc

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* address Patricks suggestions

* add a training example and fix typos

* jit the training step

* jit train step

* fix example code

* typo

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* First pass

* More progress

* Add support for local attention

* More improvements

* More improvements

* Conversion script working

* Add CanineTokenizer

* Make style & quality

* First draft of integration test

* Remove decoder test

* Improve tests

* Add documentation

* Mostly docs improvements

* Add CanineTokenizer tests

* Fix most tests on GPU, improve upsampling projection

* Address most comments by @dhgarrette

* Remove decoder logic

* Improve Canine tests, improve docs of CanineConfig

* All tokenizer tests passing

* Make fix-copies and fix tokenizer tests

* Fix test_model_outputs_equivalence test

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

* Address some more comments

* Add support for hidden_states and attentions of shallow encoders

* Define custom CanineModelOutputWithPooling, tests pass

* First pass

* More progress

* Add support for local attention

* More improvements

* More improvements

* Conversion script working

* Add CanineTokenizer

* Make style & quality

* First draft of integration test

* Remove decoder test

* Improve tests

* Add documentation

* Mostly docs improvements

* Add CanineTokenizer tests

* Fix most tests on GPU, improve upsampling projection

* Address most comments by @dhgarrette

* Remove decoder logic

* Improve Canine tests, improve docs of CanineConfig

* All tokenizer tests passing

* Make fix-copies and fix tokenizer tests

* Fix test_model_outputs_equivalence test

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

* Address some more comments

* Make conversion script work for Canine-c too

* Fix tokenizer tests

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

* fix ids_to_tokens naming error in tokenizer of deberta v2

* Update tokenization_deberta_v2.py

Add bos_token and eos_token.

* format code
Co-authored-by: Jipeng Huang <jihuan@microsoft.com>

* Fix default bool in argparser

* Add more to test

Added one more confirmed speaker, zoom links and gcal event links

* Add option to save on each training node

* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Address review comments
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

this PR is fixing an incorrect attribute - probably some tests are needed?

* [WIP] Easily train a new fast tokenizer from a given one

* Fix test

* Roll out to other tokenizers and add tests

* Fix bug with unk id and add emoji to test

* Really use something different in test

* Implement special tokens map

* Map special tokens in the Transformers tokenizers

* Fix test

* Make test more robust

* Fix test for BPE

* More robust map and test

Co-authored-by SaulLu

* Test file

* Stronger tests
Co-authored-by: SaulLu <lucilesaul.com@gmail.com>

* Map unk token for Wordpiece and address review comment

* Fix lowercase test and address review comment

* Fix all tests

* Simplify test

* Fix tests for realsies

* Easily train a new fast tokenizer from a given one - tackle the special tokens format (str or AddedToken) (#12420)

* Propose change in tests regarding lower case

* add new test for special tokens types

* put back the test part about decoding

* add feature: the AddedToken is re-build with the different mapped content

* Address review comment: simplify AddedToken building
Co-authored-by: sgugger <sylvain.gugger@gmail.com>

* Update src/transformers/tokenization_utils_fast.py
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: SaulLu <lucilesaul.com@gmail.com>
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

Co-authored-by: Jipeng Huang <jihuan@microsoft.com>

* fix_torch_device_generate_test

* remove @

* finish

* finish

* correct style

* add readme

* update readme and add requirements

* Update examples/flax/summarization/README.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix TFWav2Vec2 SpecAugment

* Invert masks

* Feedback changes

* Add OOV error to ASR models

* Feedback changes

* Rename target to labels in DetrFeatureExtractor

* Update DetrFeatureExtractor tests accordingly

* Improve docs of DetrFeatureExtractor

* Improve docs

* Make style

* [models] respect dtype of the model when instantiating it

* cleanup

* cleanup

* rework to handle non-float dtype

* fix

* switch to fp32 tiny model

* improve

* use dtype.is_floating_point

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

* fix the doc

* recode to use explicit torch_dtype_auto_detect, torch_dtype args

* docs and tweaks

* docs and tweaks

* docs and tweaks

* merge 2 args, add docs

* fix

* fix

* better doc

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

* fix_torch_device_generate_test

* remove @

* add length computatan

* finish masking

* finish

* upload

* fix some bugs

* finish

* fix dependency table

* correct tensorboard

* Apply suggestions from code review

* correct processing

* slight change init

* correct some more mistakes

* apply suggestions

* improve readme

* fix indent

* Apply suggestions from code review
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

* correct tokenizer

* finish

* finish

* finish

* finish
Co-authored-by: Patrick von Platen <patrick@huggingface.co>
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

* Tensorflow MLM example

* Add CLM example

* Style fixes, adding missing checkpoint code from the CLM example

* Fix TPU training, avoid massive dataset warnings

* Fix incorrect training length calculation for multi-GPU training

* Fix incorrect training length calculation for multi-GPU training

* Refactors and nitpicks from the review

* Style pass

* Adding README

* fix_torch_device_generate_test

* remove @

* finish

* correct summary writer

* correct push to hub

* fix indent

* finish

* finish

* finish

* finish

* finish
Co-authored-by: Patrick von Platen <patrick@huggingface.co>

* debug albert einsum

* Fix matmul computation

* Let's use torch linear layer.

* Style.

* fix_torch_device_generate_test

* remove @

* boom boom

* correct typos

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Apply suggestions from code review
Co-authored-by: Suzana Ilić <io.suzanai@gmail.com>

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Suzana Ilić <io.suzanai@gmail.com>

* added cotext manager to datasets map

* fixed style and spaces

* fixed warning of deprecation

* changed desc

* add dependency table sync verification

* improve the message

* improve the message

* revert

* ready to merge

Before the code could not be used for validation only because of this line:
extension = data_args.train_file.split(".")[-1]
was assuming that extension must be extracted from the training dataset. This line would run regardless of the training or validation options of the user. This would lead to an error if the user only wants to run an evaluation only and does not want to do train (because the training file does not exist). I modified it to extract extension from the training file if the user wants to do train and extract it from the validation file if the user wants to run eval. This way the code can be used for both training and validation separately.

[Documentation] Warn that DataCollatorForWholeWordMask is limited to BertTokenizer-like tokenizers (#12371)

* Notify users that DataCollatorForWholeWordMask is limited to BertTokenier-like tokenizers

* Fix code formatting