GitLab

* 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

* [doc] typo fix

@sgugger

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

* Create README.md

* Update model_cards/uer/chinese_roberta_L-2_H-128/README.md
Co-authored-by: Julien Chaumond <chaumond@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>

* 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 load weights

* delete line

* More doc tweaks

* Update model_sharing.rst

* make style

* missing newline

* Add email tip
Co-authored-by: Pierric Cistac <pierric@huggingface.co>

* Model templates

* TensorFlow

* Remove pooler

* CI

* Tokenizer + Refactoring

* Encoder-Decoder

* Let's go testing

* Encoder-Decoder in TF

* Let's go testing in TF

* Documentation

* README

* Fixes

* Better names

* Style

* Update docs

* Choose to skip either TF or PT

* Code quality fixes

* Add to testing suite

* Update file path

* Cookiecutter path

* Update `transformers` path

* Handle rebasing

* Remove seq2seq from model templates

* Remove s2s config

* Apply Sylvain and Patrick comments

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

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

* fix bug

* T5 refactor

* refactor tf

* apply sylvains suggestions

* Update README.md

* Update README.md

* 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

* Model sharing doc

* Style

* fix doc bug
Signed-off-by: mymusise <mymusise1@gmail.com>

* fix example bug
Signed-off-by: mymusise <mymusise1@gmail.com>

cc @Pierrci

* Update deploy-docs dependencies on CI to enable Flax
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Added pair of ""
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

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

* First addition of Flax/Jax documentation
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* make style

* Ensure input order match between Bert & Roberta
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Install dependencies "all" when building doc
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* wraps build_doc deps with ""
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Addressing @sgugger comments.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Use list to highlight JAX features.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

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

* Let's not look to much into the future for now.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

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

* Create modeling_tf_dpr.py

* Add TFDPR

* Add back TFPegasus, TFMarian, TFMBart, TFBlenderBot

last commit accidentally deleted these 4 lines, so I recover them back

* Add TFDPR

* Add TFDPR

* clean up some comments, add TF input-style doc string

* Add TFDPR

* Make return_dict=False as default

* Fix return_dict bug (in .from_pretrained)

* Add get_input_embeddings()

* Create test_modeling_tf_dpr.py

The current version is already passed all 27 tests!
Please see the test run at : 
https://colab.research.google.com/drive/1czS_m9zy5k-iSJbzA_DP1k1xAAC_sdkf?usp=sharing



* fix quality

* delete init weights

* run fix copies

* fix repo consis

* del config_class, load_tf_weights

They shoud be 'pytorch only'

* add config_class back

after removing it, test failed ... so totally only removing "use_tf_weights = None" on Lysandre suggestion

* newline after .. note::

* import tf, np (Necessary for ModelIntegrationTest)

* slow_test from_pretrained with from_pt=True

At the moment we don't have TF weights (since we don't have official official TF model)
Previously, I did not run slow test, so I missed this bug

* Add simple TFDPRModelIntegrationTest

Note that this is just a test that TF and Pytorch gives approx. the same output.
However, I could not test with the official DPR repo's output yet

* upload correct tf model

* remove position_ids as missing keys
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patrickvonplaten <patrick@huggingface.co>

The new run_ner.py script tries to run prediction on the input
test set `datasets["test"]`, but it should be the tokenized set
`tokenized_datasets["test"]`

* Add next sentence prediction loss computation

* Apply style

* Fix tests

* Add forgotten import

* Add forgotten import

* Use a new parameter

* Remove kwargs and use positional arguments