GitLab

* improve slow class tok usage at xlm rob

* add subword regularization for barthez

* improve barthez tok. test

* fix tokenizer tests

* add subword regularization for camembert

* add subword regularization for deberta v2 tokenizer

* add more doc to deberta v2 tokenizer

* add subword regularization for speech to text tok.

* fix sp_model_kwargs type in speech 2 text tok.

* add subword regularization for M2M100 tok.

* add more concrete type hints

* fix tests for m2m100 and s2t tok.

* add missing Any import

* fix syntax error in m2m100 tok.

* fix unpickle of m2m100 and s2t tok.

* fix test of m2m100 and s2t tok.

* improve unpickle of deberta v2 tok.

* add test for pickle of barthez & camembert

* fix pickle of barthez & camembert

* add test for deberta v2 tok. pickle

* fix m2m100 tok. pickle

* fix s2t tok. pickle

* add subword regularization to albert tok.

* refactor subword reg. test into TokenizerTesterMixin

improve albert tok. test

remove sample argument form albert tok.

check subword reg. using TokenizerTesterMixin

improve tok. tests

improve xlm roberta tok. tests

improve xlm roberta tok. tests

* add subword regularization for big bird t.

* improve xlm roberta tok. test

* add subword regularization for mbart50 tok.

* add subword regularization for pegasus tok.

* add subword regularization for reformer tok.

* add subword regularization for T5 tok.

* fix t5 tok. test formatting

* add subword regularization for xlm_proph. tok.

* add subword regularization for xlnet tok.

* add subword regularization for gert_gen tok.

* add typing to tokenizers

* add typing to xlm rob. tok

* add subword regularization for marian tok.

* add reverse tok. test

* fix marian tok test

* fix marian tok test

* fix casing in tok. tests

* fix style of tok. common test

* fix deberta v2 tok test

* add type annotations to tok. tests

* add type annotations to tok. __init__

* add typing to kokenizer

* add type annotations to tok. __init__

* don't specify the default when it's None

* fix barthez tok. doc

* move sentencepiece tok. tests to TokenizerTesterMixin

* fix unused imports

* fix albert tok. test

* add comment to sentencepiece test options

* fix Any import at big bird tok.

* fix Any import at xlm prophetnet tok.

* empty commit to trigger CI

* Fix tests

* Reorganize

* Update tests/test_modeling_mobilebert.py

* Remove unnecessary addition

* Initial support for upload to hub

* push -> upload

* Fixes + examples

* Fix torchhub test

* Torchhub test I hate you

* push_model_to_hub -> push_to_hub

* Apply mixin to other pretrained models

* Remove ABC inheritance

* Add tests

* Typo

* Run tests

* Install git-lfs

* Change approach

* Add push_to_hub to all

* Staging test suite

* Typo

* Maybe like this?

* More deps

* Cache

* Adapt name

* Quality

* MOAR tests

* Put it in testing_utils

* Docs + torchhub last hope

* Styling

* Wrong method

* Typos

* Update src/transformers/file_utils.py
Co-authored-by: Julien Chaumond <julien@huggingface.co>

* Address review comments

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

* Save fast tokenizers in both formats

* Fix for HerBERT

* Proper fix

* Properly test new behavior

* First third

* Styling and fix mistake

* Quality

* All the rest

* Treat %s and %d

* typo

* Missing )

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* make flax tests pytorch independent

* fix typo

* finish

* improve circle ci

* fix return tensors

* correct flax test

* re-add sentencepiece

* last tokenizer fixes

* finish maybe now

* Make Barthez tokenizer tests a bit faster

* Quality

* change tokenizer requirement

* split line

* Correct typo from list to str

* improve style

* make other function pretty as well

* add comment

* correct typo

* add new test

* pass tests for tok without padding token

* Apply suggestions from code review

* Add target contextmanager and rework prepare_seq2seq_batch

* Fix tests, treat BART and Barthez

* Add last tokenizers

* Fix test

* Set src token before calling the superclass

* Remove special behavior for T5

* Remove needless imports

* Remove needless asserts

* First commit: adding all files from tapas_v3

* Fix multiple bugs including soft dependency and new structure of the library

* Improve testing by adding torch_device to inputs and adding dependency on scatter

* Use Python 3 inheritance rather than Python 2

* First draft model cards of base sized models

* Remove model cards as they are already on the hub

* Fix multiple bugs with integration tests

* All model integration tests pass

* Remove print statement

* Add test for convert_logits_to_predictions method of TapasTokenizer

* Incorporate suggestions by Google authors

* Fix remaining tests

* Change position embeddings sizes to 512 instead of 1024

* Comment out positional embedding sizes

* Update PRETRAINED_VOCAB_FILES_MAP and PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

* Added more model names

* Fix truncation when no max length is specified

* Disable torchscript test

* Make style & make quality

* Quality

* Address CI needs

* Test the Masked LM model

* Fix the masked LM model

* Truncate when overflowing

* More much needed docs improvements

* Fix some URLs

* Some more docs improvements

* Test PyTorch scatter

* Set to slow + minify

* Calm flake8 down

* First commit: adding all files from tapas_v3

* Fix multiple bugs including soft dependency and new structure of the library

* Improve testing by adding torch_device to inputs and adding dependency on scatter

* Use Python 3 inheritance rather than Python 2

* First draft model cards of base sized models

* Remove model cards as they are already on the hub

* Fix multiple bugs with integration tests

* All model integration tests pass

* Remove print statement

* Add test for convert_logits_to_predictions method of TapasTokenizer

* Incorporate suggestions by Google authors

* Fix remaining tests

* Change position embeddings sizes to 512 instead of 1024

* Comment out positional embedding sizes

* Update PRETRAINED_VOCAB_FILES_MAP and PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

* Added more model names

* Fix truncation when no max length is specified

* Disable torchscript test

* Make style & make quality

* Quality

* Address CI needs

* Test the Masked LM model

* Fix the masked LM model

* Truncate when overflowing

* More much needed docs improvements

* Fix some URLs

* Some more docs improvements

* Add add_pooling_layer argument to TapasModel

Fix comments by @sgugger and @patrickvonplaten

* Fix issue in docs + fix style and quality

* Clean up conversion script and add task parameter to TapasConfig

* Revert the task parameter of TapasConfig

Some minor fixes

* Improve conversion script and add test for absolute position embeddings

* Improve conversion script and add test for absolute position embeddings

* Fix bug with reset_position_index_per_cell arg of the conversion cli

* Add notebooks to the examples directory and fix style and quality

* Apply suggestions from code review

* Move from `nielsr/` to `google/` namespace

* Apply Sylvain's comments
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Rogge Niels <niels.rogge@howest.be>
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: sgugger <sylvain.gugger@gmail.com>

* Warning about too long input for fast tokenizers too

If truncation is not set in tokenizers, but the tokenization is too long
for the model (`model_max_length`), we used to trigger a warning that

The input would probably fail (which it most likely will).

This PR re-enables the warning for fast tokenizers too and uses common
code for the trigger to make sure it's consistent across.

* Checking for pair of inputs too.

* Making the function private and adding it's doc.

* Remove formatting ?? in odd place.

* Missed uppercase.

* Tokenizers should be framework agnostic

* Run the slow tests

* Not testing

* Fix documentation

* 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>

[breaking|pipelines|tokenizers] Adding slow-fast tokenizers equivalence tests pipelines - Removing sentencepiece as a required dependency (#8073)

* Fixing roberta for slow-fast tests

* WIP getting equivalence on pipelines

* slow-to-fast equivalence - working on question-answering pipeline

* optional FAISS tests

* Pipeline Q&A

* Move pipeline tests to their own test job again

* update tokenizer to add sequence id methods

* update to tokenizers 0.9.4

* set sentencepiecce as optional

* clean up squad

* clean up pipelines to use sequence_ids

* style/quality

* wording

* Switch to use_fast = True by default

* update tests for use_fast at True by default

* fix rag tokenizer test

* removing protobuf from required dependencies

* fix NER test for use_fast = True by default

* fixing example tests (Q&A examples use slow tokenizers for now)

* protobuf in main deps extras["sentencepiece"] and example deps

* fix protobug install test

* try to fix seq2seq by switching to slow tokenizers for now

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

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

* fixing #8001

* make T5 tokenizer serialization more robust - style

[tests|tokenizers] Refactoring pipelines test backbone - Small tokenizers improvements - General tests speedups (#7970)

* WIP refactoring pipeline tests - switching to fast tokenizers

* fix dialog pipeline and fill-mask

* refactoring pipeline tests backbone

* make large tests slow

* fix tests (tf Bart inactive for now)

* fix doc...

* clean up for merge

* fixing tests - remove bart from summarization until there is TF

* fix quality and RAG

* Add new translation pipeline tests - fix JAX tests

* only slow for dialog

* Fixing the missing TF-BART imports in modeling_tf_auto

* spin out pipeline tests in separate CI job

* adding pipeline test to CI YAML

* add slow pipeline tests

* speed up tf and pt join test to avoid redoing all the standalone pt and tf tests

* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

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

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

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

* add require_torch and require_tf in is_pt_tf_cross_test
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* splitting fast and slow tokenizers [WIP]

* [WIP] splitting sentencepiece and tokenizers dependencies

* update dummy objects

* add name_or_path to models and tokenizers

* prefix added to file names

* prefix

* styling + quality

* spliting all the tokenizer files - sorting sentencepiece based ones

* update tokenizer version up to 0.9.0

* remove hard dependency on sentencepiece 🎉

* and removed hard dependency on tokenizers 🎉



* update conversion script

* update missing models

* fixing tests

* move test_tokenization_fast to main tokenization tests - fix bugs

* bump up tokenizers

* fix bert_generation

* update ad fix several tokenizers

* keep sentencepiece in deps for now

* fix funnel and deberta tests

* fix fsmt

* fix marian tests

* fix layoutlm

* fix squeezebert and gpt2

* fix T5 tokenization

* fix xlnet tests

* style

* fix mbart

* bump up tokenizers to 0.9.2

* fix model tests

* fix tf models

* fix seq2seq examples

* fix tests without sentencepiece

* fix slow => fast  conversion without sentencepiece

* update auto and bert generation tests

* fix mbart tests

* fix auto and common test without tokenizers

* fix tests without tokenizers

* clean up tests lighten up when tokenizers + sentencepiece are both off

* style quality and tests fixing

* add sentencepiece to doc/examples reqs

* leave sentencepiece on for now

* style quality split hebert and fix pegasus

* WIP Herbert fast

* add sample_text_no_unicode and fix hebert tokenization

* skip FSMT example test for now

* fix style

* fix fsmt in example tests

* update following Lysandre and Sylvain's comments

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

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

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

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

Adding Fast tokenizers for SentencePiece based tokenizers - Breaking: remove Transfo-XL fast tokenizer (#7141)

* [WIP] SP tokenizers

* fixing tests for T5

* WIP tokenizers

* serialization

* update T5

* WIP T5 tokenization

* slow to fast conversion script

* Refactoring to move tokenzier implementations inside transformers

* Adding gpt - refactoring - quality

* WIP adding several tokenizers to the fast world

* WIP Roberta - moving implementations

* update to dev4 switch file loading to in-memory loading

* Updating and fixing

* advancing on the tokenizers - updating do_lower_case

* style and quality

* moving forward with tokenizers conversion and tests

* MBart, T5

* dumping the fast version of transformer XL

* Adding to autotokenizers + style/quality

* update init and space_between_special_tokens

* style and quality

* bump up tokenizers version

* add protobuf

* fix pickle Bert JP with Mecab

* fix newly added tokenizers

* style and quality

* fix bert japanese

* fix funnel

* limite tokenizer warning to one occurence

* clean up file

* fix new tokenizers

* fast tokenizers deep tests

* WIP adding all the special fast tests on the new fast tokenizers

* quick fix

* adding more fast tokenizers in the fast tests

* all tokenizers in fast version tested

* Adding BertGenerationFast

* bump up setup.py for CI

* remove BertGenerationFast (too early)

* bump up tokenizers version

* Clean old docstrings

* Typo

* Update following Lysandre comments
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

* Check decorator order

* Adapt for parametrized decorators

* Fix typos

* is_pretokenized -> is_split_into_words

* Fix tests

* fix deprecation warnings

* remove tests/test_tokenization_common.py's test_padding_to_max_length

* revert test_padding_to_max_length

Batch encore plus and overflowing tokens fails when non existing overflowing tokens for a sequence (#6677)

* Patch and test

* Fix tests

* broken test

* batch parity

* tests pass

* boom boom

* boom boom

* split out bart tokenizer tests

* fix tests

* boom boom

* Fixed dataset bug

* Fix marian

* Undo extra

* Get marian working

* Fix t5 tok tests

* Test passing

* Cleanup

* better assert msg

* require torch

* Fix mbart tests

* undo extra decoder_attn_mask change

* Fix import

* pegasus tokenizer can ignore src_lang kwargs

* unused kwarg test cov

* boom boom

* add todo for pegasus issue

* cover one word translation edge case

* Cleanup

* doc

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

* fix tokenizer saving and loading bugs when adding AddedToken to additional special tokens

* Add tokenizer test

* Style

* Style 2
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

improve unittests for finetuning, especially w.r.t testing frozen parameters
fix freeze_embeds for T5
add streamlit setup.cfg

* BertTokenizerFast - Do not specify strip_accents by default

* Bump tokenizers to new version

* Add test for AddedToken serialization

* Exposing prepare_for_model for both slow & fast tokenizers

* Update method signature

* The traditional style commit

* Hide the warnings behind the verbose flag

* update default truncation strategy and prepare_for_model

* fix tests and prepare_for_models methods
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Add new parameter `pad_to_multiple_of` on tokenizers.

* unittest for pad_to_multiple_of

* Add .name when logging enum.

* Fix missing .items() on dict in tests.

* Add special check + warning if the tokenizer doesn't have proper pad_token.

* Use the correct logger format specifier.

* Ensure tokenizer with no pad_token do not modify the underlying padding strategy.

* Skip test if tokenizer doesn't have pad_token

* Fix RobertaTokenizer on empty input

* Format.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* fix and updating to simpler API
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

[Tokenization] Fix #5181 - make #5155 more explicit - move back the default logging level in tests to WARNING (#5252)

* fix-5181

Padding to max sequence length while truncation to another length was wrong on slow tokenizers

* clean up and fix #5155

* fix XLM test

* Fix tests for Transfo-XL

* logging only above WARNING in tests

* switch slow tokenizers tests in @slow

* fix Marian truncation tokenization test

* style and quality

* make the test a lot faster by limiting the sequence length used in tests

* update tests for fast tokenizers + fix small bug in saving/loading

* better tests on serialization

* fixing serialization

* comment cleanup

* Add return lengths

* make pad a bit more flexible so it can be used as collate_fn

* check all kwargs sent to encoding method are known

* fixing kwargs in encodings

* New AddedToken class in python

This class let you specify specifique tokenization behaviors for some special tokens. Used in particular for GPT2 and Roberta, to control how white spaces are stripped around special tokens.

* style and quality

* switched to hugginface tokenizers library for AddedTokens

* up to tokenizer 0.8.0-rc3 - update API to use AddedToken state

* style and quality

* do not raise an error on additional or unused kwargs for tokenize() but only a warning

* transfo-xl pretrained model requires torch

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