GitLab

* 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>

* fix #5081 and improve backward compatibility (slightly)

* add nlp to setup.cfg - style and quality

* align default to previous default

* remove test that doesn't generalize

[HUGE] Refactoring tokenizers backend - padding - truncation - pre-tokenized pipeline - fast tokenizers - tests (#4510)

* Use tokenizers pre-tokenized pipeline

* failing pretrokenized test

* Fix is_pretokenized in python

* add pretokenized tests

* style and quality

* better tests for batched pretokenized inputs

* tokenizers clean up - new padding_strategy - split the files

* [HUGE] refactoring tokenizers - padding - truncation - tests

* style and quality

* bump up requied tokenizers version to 0.8.0-rc1

* switched padding/truncation API - simpler better backward compat

* updating tests for custom tokenizers

* style and quality - tests on pad

* fix QA pipeline

* fix backward compatibility for max_length only

* style and quality

* Various cleans up - add verbose

* fix tests

* update docstrings

* Fix tests

* Docs reformatted

* __call__ method documented
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Refactor tensor creation in tokenizers.

* Make sure to convert string to TensorType

* Refactor convert_to_tensors_

* Introduce numpy tensor creation

* Format

* Add unittest for TensorType creation from str

* sorting imports

* Added unittests for numpy tensor conversion.

* Do not use in-place version for squeeze as numpy doesn't provide such feature.

* Added extra parameter prepend_batch_axis: bool on prepare_for_model.

* Ensure test_np_encode_plus_sent_to_model is not executed if encoder/decoder model.

* style.

* numpy tests require_torch for now while flax not merged.

* Hopefully will make flake8 happy.

* One more time 🎶

* Fix: unpin flake8 and fix cs errors

* Ok we still need to quote those

cc @julien-c

* Updating modeling tf files; adding tests

* Merge `encode_plus` and `batch_encode_plus`

* Renamed num_added_tokens to num_special_tokens_to_add
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Cherry-Pick: Partially fix space only input without special tokens added to the output #3091
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Added property is_fast on PretrainedTokenizer and PretrainedTokenizerFast
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Make fast tokenizers unittests work on Windows.

* Entirely refactored unittest for tokenizers fast.

* Remove ABC class for CommonFastTokenizerTest

* Added embeded_special_tokens tests from allenai @dirkgr

* Make embeded_special_tokens tests from allenai more generic

* Uniformize vocab_size as a property for both Fast and normal tokenizers

* Move special tokens handling out of PretrainedTokenizer (SpecialTokensMixin)

* Ensure providing None input raise the same ValueError than Python tokenizer + tests.

* Fix invalid input for assert_padding when testing batch_encode_plus

* Move add_special_tokens from constructor to tokenize/encode/[batch_]encode_plus methods parameter.

* Ensure tokenize() correctly forward add_special_tokens to rust.

* Adding None checking on top on encode / encode_batch for TransfoXLTokenizerFast.
Avoid stripping on None values.

* unittests ensure tokenize() also throws a ValueError if provided None

* Added add_special_tokens unittest for all supported models.

* Style

* Make sure TransfoXL test run only if PyTorch is provided.

* Split up tokenizers tests for each model type.

* Fix invalid unittest with new tokenizers API.

* Filter out Roberta openai detector models from unittests.

* Introduce BatchEncoding on fast tokenizers path.

This new structure exposes all the mappings retrieved from Rust.
It also keeps the current behavior with model forward.

* Introduce BatchEncoding on slow tokenizers path.

Backward compatibility.

* Improve error message on BatchEncoding for slow path

* Make add_prefix_space True by default on Roberta fast to match Python in majority of cases.

* Style and format.

* Added typing on all methods for PretrainedTokenizerFast

* Style and format

* Added path for feeding pretokenized (List[str]) input to PretrainedTokenizerFast.

* Style and format

* encode_plus now supports pretokenized inputs.

* Remove user warning about add_special_tokens when working on pretokenized inputs.

* Always go through the post processor.

* Added support for pretokenized input pairs on encode_plus

* Added is_pretokenized flag on encode_plus for clarity and improved error message on input TypeError.

* Added pretokenized inputs support on batch_encode_plus

* Update BatchEncoding methods name to match Encoding.

* Bump setup.py tokenizers dependency to 0.7.0rc1

* Remove unused parameters in BertTokenizerFast

* Make sure Roberta returns token_type_ids for unittests.

* Added missing typings

* Update add_tokens prototype to match tokenizers side and allow AddedToken

* Bumping tokenizers to 0.7.0rc2

* Added documentation for BatchEncoding

* Added (unused) is_pretokenized parameter on PreTrainedTokenizer encode_plus/batch_encode_plus methods.

* Added higher-level typing for tokenize / encode_plus / batch_encode_plus.

* Fix unittests failing because add_special_tokens was defined as a constructor parameter on Rust Tokenizers.

* Fix text-classification pipeline using the wrong tokenizer

* Make pipelines works with BatchEncoding

* Turn off add_special_tokens on tokenize by default.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Remove add_prefix_space from tokenize call in unittest.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Style and quality
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Correct message for batch_encode_plus none input exception.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Fix invalid list comprehension for offset_mapping overriding content every iteration.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* TransfoXL uses Strip normalizer.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Bump tokenizers dependency to 0.7.0rc3
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Support AddedTokens for special_tokens and use left stripping on mask for Roberta.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* SpecilaTokenMixin can use slots to faster access to underlying attributes.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Remove update_special_tokens from fast tokenizers.

* Ensure TransfoXL unittests are run only when torch is available.

* Style.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Style

* Style 🙏🙏



* Remove slots on SpecialTokensMixin, need deep dive into pickle protocol.

* Remove Roberta warning on __init__.

* Move documentation to Google style.
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* Minimal example

* Proposal 2

* Proposal 2 for fast tokenizers

* Typings

* Docs

* Revert "Docs" for easier review

This reverts commit eaf0f97062e809887704a542144c537f769d5223.

* Remove unnecessary assignments

* Tests

* Fix faulty type

* Remove prints

* return_outputs -> model_input_names

* Revert "Revert "Docs" for easier review"

This reverts commit 6fdc69408102bf695797f2dfddbb6350c6b9e722.

* code quality

* force pad_token_id to be set before padding

* fix tests and forbid padding without having a padding_token_id set

* Testing that encode_plus and batch_encode_plus behave the same way

Spoiler alert: they don't

* Testing rest of arguments in batch_encode_plus

* Test tensor return in batch_encode_plus

* Addressing Sam's comments

* flake8

* Simplified with `num_added_tokens`

* Preserve spaces in GPT-2 tokenizers

Preserves spaces after special tokens in GPT-2 and inhereted (RoBERTa)
tokenizers, enabling correct BPE encoding. Automatically inserts a space
in front of first token in encode function when adding special tokens.

* Add tokenization preprocessing method

* Add framework argument to pipeline factory

Also fixes pipeline test issue. Each test input now treated as a
distinct sequence.