GitLab

* Add init barthez

* Add barthez model, tokenizer and docs

BARThez is a pre-trained french seq2seq model that uses BART objective.

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

* Add license

* Change URLs scheme

* Remove barthez model keep tokenizer

* Fix style

* Fix quality

* Update tokenizer

* Add fast tokenizer

* Add fast tokenizer test
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* correct dpr test and bert pos fault

* fix dpr bert config problem

* fix layoutlm

* add config to dpr as well

* try flax fix

* same for roberta

* [FlaxBert] Fix non-broadcastable attention mask for batched forward-passes

* [FlaxRoberta] Fix non-broadcastable attention mask

* Use jax.numpy instead of ordinary numpy (otherwise not jit-able)

* Partially revert "Use jax.numpy ..."

* Add tests for batched forward passes

* Avoid unnecessary OOMs due to preallocation of GPU memory by XLA

* Auto-fix style

* Re-enable GPU memory preallocation but with mem fraction < 1/paralleism

* fix mems in xlnet

* fix use_mems

* fix use_mem_len

* fix use mems

* clean docs

* fix tf typo

* make xlnet tf for generation work

* fix tf test

* refactor use cache

* add use cache for missing models

* correct use_cache in generate

* correct use cache in tf generate

* fix tf

* correct getattr typo

* make sylvain happy

* change in docs as well

* do not apply to cookie cutter statements

* fix tf test

* make pytorch model fully backward compatible

* bart output hidden states upstream

* same w/ decoder

* add tests

* fix prophetnet

* fix gpt2 and ctrl

* fix fstm and skip test for reformer and longformer

* fix all models
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix QA argument handler

* Attempt to get a better fix for QA (#8768)
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Apply on BERT and ALBERT

* Update TF Bart

* Add input processing to TF BART

* Add input processing for TF CTRL

* Add input processing to TF Distilbert

* Add input processing to TF DPR

* Add input processing to TF Electra

* Add input processing for TF Flaubert

* Add deprecated arguments

* Add input processing to TF XLM

* remove unused imports

* Add input processing to TF Funnel

* Add input processing to TF GPT2

* Add input processing to TF Longformer

* Add input processing to TF Lxmert

* Apply style

* Add input processing to TF Mobilebert

* Add input processing to TF GPT

* Add input processing to TF Roberta

* Add input processing to TF T5

* Add input processing to TF TransfoXL

* Apply style

* Rebase on master

* Bug fix

* Retry to bugfix

* Retry bug fix

* Fix wrong model name

* Try another fix

* Fix BART

* Fix input precessing

* Apply style

* Put the deprecated warnings in the input processing function

* Remove the unused imports

* Raise an error when len(kwargs)>0

* test ModelOutput instead of TFBaseModelOutput

* Bug fix

* Address Patrick's comments

* Address Patrick's comments

* Address Sylvain's comments

* Add the new inputs in new Longformer models

* Update the template with the new input processing

* Remove useless assert

* Apply style

* Trigger CI

* implement support for run-time dependency version checking

* try not escaping !

* use findall that works on py36

* small tweaks

* autoformatter worship

* simplify

* shorter names

* add support for non-versioned checks

* add deps

* revert

* tokenizers not required, check version only if installed

* make a proper distutils cmd and add make target

* tqdm must be checked before tokenizers

* workaround the DistributionNotFound peculiar setup

* handle the rest of packages in setup.py

* fully sync setup.py's install_requires - to check them all

* nit

* make install_requires more readable

* typo

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

* restyle

* add types

* simplify

* simplify2
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* MT5 should have an autotokenizer

* Different configurations should be able to point to same tokenizers

* Fix BART test

* Fix MBART tests

* Remove erroneous line from yaml

* Update tests/test_modeling_bart.py

* Quality

* Support BERT relative position embeddings

* Fix typo in README.md

* Address review comment

* Fix failing tests

* [tiny] Fix style_doc.py check by adding an empty line to configuration_bert.py

* make fix copies

* fix configs of electra and albert and fix longformer

* remove copy statement from longformer

* fix albert

* fix electra

* Add bert variants forward tests for various position embeddings

* [tiny] Fix style for test_modeling_bert.py

* improve docstring

* [tiny] improve docstring and remove unnecessary dependency

* [tiny] Remove unused import

* re-add to ALBERT

* make embeddings work for ALBERT

* add test for albert
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add early stopping patience and minimum threshold metric must improve to prevent early stopping to pytorch trainer

* Add early stopping test

* Set patience counter to 0 if best metric not defined yet

* Make early stopping a callback. Add callback event for updating the best metric for early stopping callback to trigger on.

* Run make style

* make funciton name sensible

* Improve new argument docstring wording and hope that flakey CI test passes.

* Use on_evaluation callback instead of custom. Remove some debug printing

* Move early stopping arguments and state into early stopping callback

* Run make style

* Remove old code

* Fix docs formatting. make style went rogue on me.

* Remove copied attributes and fix variable

* Add assertions on training arguments instead of mutating them. Move comment out of public docs.

* Make separate test for early stopping callback. Add test of invalid arguments.

* Run make style... I remembered before CI this time!

* appease flake8

* Add EarlyStoppingCallback to callback docs

* Make docstring EarlyStoppingCallabck match other callbacks.

* Fix typo in docs

* consistent ignore keys + make private

* style

* - authorized_missing_keys    => _keys_to_ignore_on_load_missing
  - authorized_unexpected_keys => _keys_to_ignore_on_load_unexpected

* move public doc of private attributes to private comment

* gpt2 and t5 parallel modeling

* model_parallel utils update

* adding missing model_parallel_utils

Adds missing model_parallel_utils and reverses the changes to code in modeling_gpt2 and modeling_t5

* training_args reformat

Reformatted training_args

* style formatting

Style formatting doc string length on training_args and model_parallel_utils

* style changes

make style && make quality for training_args and model_parallel_utils.

* adding tests

* minor change in trainer

reverts loss calculation

* Update training_args.py

* Update training_args.py

added back docstring language for adam_beta1 and adam_beta2

* Update trainer.py

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

* Fix style & rebase
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* Make ci fail

* Try to make tests actually run?

* CI finally failing?

* Fix CI

* Revert "Fix CI"

This reverts commit ca7923be7334d4e571b023478ebdd6b33dfd0ebb.

* Ooops wrong one

* one more try

* Ok ok let's move this elsewhere

* Alternative to globals() (#8667)

* Alternative to globals()

* Error is raised later so return None

* Sentencepiece not installed make some tokenizers None

* Apply Lysandre wisdom

* Slightly clearer comment?

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

* Fix the CI and tests

* Fix quality

* Remove that m form nowhere

* don't reconvert when the type is already right

* better name

* adjust logic as suggested

* merge

* `disable_ngram_loss` fix for prophetnet

* add changes documentation

* fix _compute_loss to use mean reduction and -100 to masked tokens & remove unnecessary arguments

* mean label smoothing loss

* small refactor

* fix test
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* Better filtering of the model outputs in Trainer

* Fix examples tests

* Add test for Lysandre

* CI should install `sentencepiece`

* Requiring TF

* Fixing some TFDPR bugs

* remove return_dict=False/True hack
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* working on LongformerForSequenceClassification

* add TFLongformerForMultipleChoice

* add TFLongformerForTokenClassification

* use add_start_docstrings_to_model_forward

* test TFLongformerForSequenceClassification

* test TFLongformerForMultipleChoice

* test TFLongformerForTokenClassification

* remove test from repo

* add test and doc for TFLongformerForSequenceClassification, TFLongformerForTokenClassification, TFLongformerForMultipleChoice

* add requested classes to modeling_tf_auto.py
update dummy_tf_objects
fix tests
fix bugs in requested classes

* pass all tests except test_inputs_embeds

* sync with master

* pass all tests except test_inputs_embeds

* pass all tests

* pass all tests

* work on test_inputs_embeds

* fix style and quality

* make multi choice work

* fix TFLongformerForTokenClassification signature

* fix TFLongformerForMultipleChoice, TFLongformerForSequenceClassification signature

* fix mult choice

* fix mc hint

* fix input embeds

* fix input embeds

* refactor input embeds

* fix copy issue

* apply sylvains changes and clean more
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Adding PrefixConstrainedLogitsProcessor

* fixing RAG and style_doc

* fixing black (v20 instead of v19)

* Improving doc in generation_logits_process.py

* Improving docs and typing in generation_utils.py

* docs improvement

* adding test and fixing doc typo

* fixing doc_len

* isort on test

* fixed test

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

* Remove old deprecated arguments
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* Remove needless imports

* Fix tests
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* 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>

* add mt5 and t5v1_1 model

* fix tests

* correct some imports

* add tf model

* finish tf t5

* improve examples

* fix copies

* clean doc

* Put models in subfolders

* Styling

* Fix imports in tests

* More fixes in test imports

* Sneaky hidden imports

* Fix imports in doc files

* More sneaky imports

* Finish fixing tests

* Fix examples

* Fix path for copies

* More fixes for examples

* Fix dummy files

* More fixes for example

* More model import fixes

* Is this why you're unhappy GitHub?

* Fix imports in conver command

* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Run on the real suite

* Fix slow tests

* Fix passing token_type_ids during GPT2DoubleHeadsModel.generate() if used

and for GPT2LMHeadModel too

* Update tests to check token_type_ids usage in GPT2 models

* Simply insert T5Tokenizer's prepare_seq2seq_batch

* Update/Add some 'import'

* fix RunTimeError caused by '.view'

* Moves .view related error avoidance from seq2seq_trainer to inside prophetnet

* Update test_tokenization_prophetnet.py

* Format the test code with black

* Re-format the test code

* Update test_tokenization_prophetnet.py

* Add importing require_torch in the test code

* Add importing BatchEncoding in the test code

* Re-format the test code on Colab

[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>

* Update some tests

* Small update

* Apply style

* Use max_position_embeddings

* Create a fake attribute

* Create a fake attribute

* Update wrong name

* Wrong TransfoXL model file

* Keep the common tests agnostic

* fix bug

* T5 refactor

* refactor tf

* apply sylvains suggestions

* Add pretraining loss computation for TF Bert pretraining

* Fix labels creation

* Fix T5 model

* restore T5 kwargs

* try a generic fix for pretraining models

* Apply style

* Overide the prepare method for the BERT tests