GitLab

* Double check for attribute

* Use right name

It was used in shift_right.
After this change TF code is more similar to Pytorch implementations
Also, TF graphs are optimized (one node less)

Adding prepare_decoder_input_ids_from_labels methods to all ConditionalGeneration TF models (#12560)

* Adding support for `pipeline("automatic-speech-recognition")`.

- Ugly `"config"` choice for AutoModel. It would be great to have the
possibility to have something like `AutoModelFor` that would implement
the same logic (Load the config, check Architectures and load the first
one)

* Remove `model_id` was not needed in the end.

* Rebased !

* Remove old code.

* Rename `nlp`.

* fix_torch_device_generate_test

* remove @

* finish

* Validation split percentage to be used for custom data files also

Issue same as https://github.com/huggingface/transformers/issues/12406 fixed for pytorch branch run_mlm.py

* Validation split added in the right place

* Update run_clm.py

* validation split added for custom files

* Validation split added for custom files

* Update run_plm.py

* fixed validation split for custom files as input for pytorch examples in lm

* Update run_clm_no_trainer.py

* args modified

* Copy BART to MBart and rename some stuff

* Add copy statements pointing to FlaxBart

* Update/add some common files

* Update shift_tokens_rigth + fix imports

* Fix shift_tokens_right method according to MBart implementation

* Update shift_tokens_right in tests accordingly

* Fix the import issue and update docs file
* make style quality

* Do some minor changes according to patil-suraj suggestions

* Change the order of normalization layer and attention

* Add some copu statementes

* Update generate method and add integration test for mBart

* Make a few updates after a review

Besides, add `lang_code_to_id` to MBartTokenizeFast

* fix-copies; make style quality

* Apply suggestions from code review

* Apply suggestions from code review

* Apply suggestions from code review

* fix output type, style

* add copied from

* resolve conflicts
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* add adafactor

* Update examples/flax/language-modeling/run_mlm_flax.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix_torch_device_generate_test

* remove @

* up

* up

* correct

* upload
Co-authored-by: Patrick von Platen <patrick@huggingface.co>

* implementing tflxmertmodel integration test

* move import

* revert and fix

* flax gpt neo

* fix query scaling

* update generation test

* use flax model for test

* add RoFormerTokenizerFast into AutoTokenizer

* fix typo in roformer docs

* make onnx export happy

* update RoFormerConfig embedding_size

* use jieba not rjieba

* fix 12244 and make test_alignement passed

* update ARCHIVE_MAP

* make style & quality & fixup

* update

* make style & quality & fixup

* make style quality fixup

* update

* suggestion from LysandreJik
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* make style

* use rjieba
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* fix saving and loading

* update readme

* fix_torch_device_generate_test

* remove @

* adapt flax pretrain script

* fix_torch_device_generate_test

* remove @

* up

* fix_torch_device_generate_test

* remove @

* push

* fix_torch_device_generate_test

* remove @

* add logging steps

* correct training scripts

* correct readme

* correct

* NER example for Tensorflow

* Style pass

* Style pass

* Added metric computation on the evaluation set

* Style pass

* Fixed label masking

* Style pass

* Style pass

* fix_torch_device_generate_test

* remove @

* upload

* finish dataset streaming

* adapt readme

* finish

* up

* up

* up

* up

* Apply suggestions from code review

* finish

* make style

* make style2

* finish
Co-authored-by: Patrick von Platen <patrick@huggingface.co>

* begin script

* clean example, add readme

* update readme

* remove decay mask

* remove masking

* update readme & make flake happy

* create LxmertModelIntegrationTest

* implementation using numpy seeding to fix inputs params.

* fix code quality

* isort check

* clip style example

* fix post init

* add requirements

* update readme, few small fixes

Thanks a lot @BirgerMoell

* fix lm_head.decoder.weight ignore_key handling

* fix the mutable class variable

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

* replicate the comment

* make deterministic
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>