GitLab

* add benchmark for all kinds of models

* improved import

* delete bogus files

* make style

* 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

* Configure all models to use output_hidden_states as argument passed to foward()

* Pass all tests

* Remove cast_bool_to_primitive in TF Flaubert model

* correct tf xlnet

* add pytorch test

* add tf test

* Fix broken tests

* Configure all models to use output_hidden_states as argument passed to foward()

* Pass all tests

* Remove cast_bool_to_primitive in TF Flaubert model

* correct tf xlnet

* add pytorch test

* add tf test

* Fix broken tests

* Refactor output_hidden_states for mobilebert

* Reset and remerge to master
Co-authored-by: Joseph Liu <joseph.liu@coinflex.com>
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* Fixed resize_token_embeddings for transfo_xl model

* Fixed resize_token_embeddings for transfo_xl.

Added custom methods to TransfoXLPreTrainedModel for resizing layers of
the AdaptiveEmbedding.

* Updated docstring

* Fixed resizinhg cutoffs; added check for new size of embedding layer.

* Added test for resize_token_embeddings

* Fixed code quality

* Fixed unchanged cutoffs in model.config

* Added feature to move added tokens in tokenizer.

* Fixed code quality

* Added feature to move added tokens in tokenizer.

* Fixed code quality

* Fixed docstring, renamed sym to 	oken.
Co-authored-by: Rafael Weingartner <rweingartner.its-b2015@fh-salzburg.ac.at>

* finish benchmark

* fix isort

* fix setup cfg

* retab

* fix time measuring of tf graph mode

* fix tf cuda

* clean code

* better error message

* Add MobileBert

* Quality + Conversion script

* style

* Update src/transformers/modeling_mobilebert.py

* Links to S3

* Style

* TFMobileBert

Slight fixes to the pytorch MobileBert
Style

* MobileBertForMaskedLM (PT + TF)

* MobileBertForNextSentencePrediction (PT + TF)

* MobileFor{MultipleChoice, TokenClassification} (PT + TF)


ss

* Tests + Auto

* Doc

* Tests

* Addressing @sgugger's comments

* Adressing @patrickvonplaten's comments

* Style

* Style

* Integration test

* style

* Model card
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* resize token embeddings

* add tokens

* add tokens

* add tokens

* add t5 token method

* add t5 token method

* add t5 token method

* typo

* debugging input

* debugging input

* debug

* debug

* debug

* trying to set embedding tokens properly

* set embeddings for generation head too

* set embeddings for generation head too

* debugging

* debugging

* enable generation

* add base method

* add base method

* add base method

* return logits in the main call

* reverting to generation

* revert back

* set embeddings for the bert main layer

* description

* fix conflicts

* logging

* set base model as self

* refactor

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* v0

* v0

* finalize

* final

* black

* add tests

* revert back the emb call

* comments

* comments

* add the second test

* add vocab size condig

* add tf models

* add tf models. add common tests

* remove model specific embedding tests

* stylish

* remove files

* stylez

* Update src/transformers/modeling_tf_transfo_xl.py

change the error.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* adding unchanged weight test
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* add ElectraForMultipleChoice

* add  test_for_multiple_choice

* add ElectraForMultipleChoice in auto model

* add ElectraForMultipleChoice in all_model_classes

* add SequenceSummary related parameters

* get rid pooler, use SequenceSummary instead

* add electra multiple choice test
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Make default_data_collator more flexible

* Accept tensors for all features

* Document code

* Refactor

* Formatting

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Added is_fast property on BatchEncoding to indicate if the object comes from a Fast Tokenizer.

* Added __get_state__() & __set_state__() to be pickable.

* Correct tokens() return type from List[int] to List[str]

* Added unittest for BatchEncoding pickle/unpickle

* Added unittest for BatchEncoding is_fast

* More careful checking on BatchEncoding unpickle tests.

* Formatting.

* is_fast should assertTrue on Rust tokenizers.

* Ensure tensorflow has correct way of checking array_equal

* More formatting.

* Add `DistilBertForMultipleChoice`

[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>

* fix test

* Update tests/test_modeling_common.py

* Update tests/test_modeling_common.py

* Make DataCollator a callable

* Update src/transformers/data/data_collator.py
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Add AlbertForMultipleChoice

* Make up to date and add all models to common tests

* first commit

* add new auto models

* better naming

* fix bert automodel

* fix automodel for pretraining

* add models to init

* fix name typo

* fix typo

* better naming

* future warning instead of depreciation warning

* Support multiple choice in tf common model tests

* Add the input_embeds test

* Fixed resize_token_embeddings for transfo_xl model

* Fixed resize_token_embeddings for transfo_xl.

Added custom methods to TransfoXLPreTrainedModel for resizing layers of
the AdaptiveEmbedding.

* Updated docstring

* Fixed resizinhg cutoffs; added check for new size of embedding layer.

* Added test for resize_token_embeddings

* Fixed code quality

* Fixed unchanged cutoffs in model.config
Co-authored-by: Rafael Weingartner <rweingartner.its-b2015@fh-salzburg.ac.at>

* Split LMBert model in two

* Fix example

* Remove lm_labels

* Adapt tests, refactor prepare_for_generation

* Fix merge

* Hide BeartLMHeadModel

* ElectraForQuestionAnswering

* udate __init__

* add test for electra qa model

* add ElectraForQuestionAnswering in auto models

* add ElectraForQuestionAnswering in all_model_classes

* fix outputs, input_ids defaults to None

* add ElectraForQuestionAnswering in docs

* remove commented line

* Fix CI

* Deal with multiple choice in common tests

* DOC: Replace instances of ``config.output_attentions`` with function argument ``output_attentions``

* DOC: Apply Black Formatting

* Fix errors where output_attentions was undefined

* Remove output_attentions in classes per review

* Fix regressions on tests having `output_attention`

* Fix further regressions in tests relating to `output_attentions`

Ensure proper propagation of `output_attentions` as a function parameter
to all model subclasses

* Fix more regressions in `test_output_attentions`

* Fix issues with BertEncoder

* Rename related variables to `output_attentions`

* fix pytorch tests

* fix bert and gpt2 tf

* Fix most TF tests for `test_output_attentions`

* Fix linter errors and more TF tests

* fix conflicts

* DOC: Apply Black Formatting

* Fix errors where output_attentions was undefined

* Remove output_attentions in classes per review

* Fix regressions on tests having `output_attention`

* fix conflicts

* fix conflicts

* fix conflicts

* fix conflicts

* fix pytorch tests

* fix conflicts

* fix conflicts

* Fix linter errors and more TF tests

* fix tf tests

* make style

* fix isort

* improve output_attentions

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

* add tpu and torchscipt for benchmark

* fix name in tests

* "fix email"

* make style

* better log message for tpu

* add more print and info for tpu

* allow possibility to print tpu metrics

* correct cpu usage

* fix test for non-install

* remove bugus file

* include psutil in testing

* run a couple of times before tracing in torchscript

* do not allow tpu memory tracing for now

* make style

* add torchscript to env

* better name for torch tpu
Co-authored-by: Patrick von Platen <patrick@huggingface.co>