GitLab

* fix greedy generate test

* delet ipdb

Fixing:

```
src/transformers/tokenization_blenderbot.py:163: DeprecationWarning: invalid escape sequence \s
    token = re.sub("\s{2,}", " ", token)
```

* Bug fix: NER pipeline shouldn't group separate entities of same type

* style fix

* [Bug Fix] Shouldn't group entities that are both 'B' even if they are same type
	(B-type1 B-type1) != (B-type1 I-type1)
[Bug Fix] add an option `ignore_subwords` to ignore subsequent ##wordpieces in predictions. Because some models train on only the first token of a word and not on the subsequent wordpieces (BERT NER default). So it makes sense doing the same thing at inference time.
	The simplest fix is to just group the subwords with the first wordpiece.
	[TODO] how to handle ignored scores? just set them to 0 and calculate zero invariant mean ?
	[TODO] handle different wordpiece_prefix ## ? possible approaches:
		get it from tokenizer? but currently most tokenizers dont have a wordpiece_prefix property?
		have an _is_subword(token)
[Feature add] added option to `skip_special_tokens`. Cause It was harder to remove them after grouping.
[Additional Changes] remove B/I prefix on returned grouped_entities
[Feature Request/TODO] Return indexes?
[Bug TODO]  can't use fast tokenizer with grouped_entities ('BertTokenizerFast' object has no attribute 'convert_tokens_to_string')

* use offset_mapping to fix [UNK] token problem

* ignore score for subwords

* modify ner_pipeline test

* modify ner_pipeline test

* modify ner_pipeline test

* ner_pipeline change ignore_subwords default to true

* add ner_pipeline ignore_subword=False test case

* fix offset_mapping index

* fix style again duh

* change is_subword and convert_tokens_to_string logic

* merge tests with new test structure

* change test names

* remove old tests

* ner tests for fast tokenizer

* fast tokenizers have convert_tokens_to_string

* Fix the incorrect merge
Co-authored-by: Ceyda Cinarel <snu-ceyda@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* make it possible to invoke testconf.py in both test suites without crashing on having the same option added

* perl -pi -e 's|--make_reports|--make-reports|' to be consistent with other opts

* add `pytest --make-reports` to all CIs (and artifacts)

* fix

* Add DataCollatorForTokenClassification and clean tests

* Make quality

* improve documentation of training_args.py

- do_train
- do_eval
- do_predict

* fix line too long

* fix style with black on training_args.py

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

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

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

* fix line length with utils/style_doc

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

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

* Updated ConversationalPipeline to work with encoder-decoder models (e.g. BlenderBot)

* Addition of integration test for EncoderDecoder conversation model
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* [FIX] TextGenerationPipeline is currently broken.

It's most likely due to #8180.
What's missing is a multi vs single string handler at the beginning of
the pipe.
And also there was no testing of this pipeline.

* Fixing Conversational tests too.

* first draft

* show design proposition for new generate method

* up

* make better readable

* make first version

* gpt2 tests pass

* make beam search for gpt2 work

* add first encoder-decoder code

* delete typo

* make t5 work

* save indermediate

* make bart work with beam search

* finish beam search bart / t5

* add default kwargs

* make more tests pass

* fix no bad words sampler

* some fixes and tests for all distribution processors

* fix test

* fix rag slow tests

* merge to master

* add nograd to generate

* make all slow tests pass

* speed up generate

* fix edge case bug

* small fix

* correct typo

* add type hints and docstrings

* fix typos in tests

* add beam search tests

* add tests for beam scorer

* fix test rag

* finish beam search tests

* move generation tests in seperate file

* fix generation tests

* more tests

* add aggressive generation tests

* fix tests

* add gpt2 sample test

* add more docstring

* add more docs

* finish doc strings

* apply some more of sylvains and sams comments

* fix some typos

* make fix copies

* apply lysandres and sylvains comments

* final corrections on examples

* small fix for reformer

* Make line by line optional in run_mlm

* Add option to disable dynamic padding

* Add option to plm too and update README

* Typos

* More typos

* Even more typos

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Some work to fix the behaviour of DefaultArgumentHandler by removing it.

* Fixing specific pipelines argument checking.

* Update README.md

* Update README.md

* Create README.md

* added model cards

* boom boom

* reverse order

* make sure that logging_first_step evaluates

* fix bug with incorrect loss on logging_first_step

* fix style

* logging_first_step only logs, not evals

* Minor style improvements:

1. Use `@nn.compact` rather than `@compact` (as to not make it seem
   like compact is a standard Python decorator.
2. Move attribute docstrings from two `__call__` methods to comments
   on the attributes themselves. (This was probably a remnant from
   the pre-Linen version where the attributes were arguments to
   `call`.)

* Use black on the Flax modeling code