GitLab

* Fixed train_test_split test_size argument

* `Seq2SeqTrainer` set max_length and num_beams only when non None  (#12899)

* set max_length and num_beams only when non None

* fix instance variables

* fix code style

* [FLAX] Minor fixes in CLM example (#12914)

* readme: fix retrieval of vocab size for flax clm example

* examples: fix flax clm example when using training/evaluation files

* Fix module path for symbolic_trace example
Co-authored-by: cchen-dialpad <47165889+cchen-dialpad@users.noreply.github.com>
Co-authored-by: Stefan Schweter <stefan@schweter.it>
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

* readme: fix retrieval of vocab size for flax clm example

* examples: fix flax clm example when using training/evaluation files

* set max_length and num_beams only when non None

* fix instance variables

* fix code style

* Better heuristic for token-classification pipeline.

Relooking at the problem makes thing actually much simpler,
when we look at ids from a tokenizer, we have no way in **general**
to recover if some substring is part of a word or not.

However, within the pipeline, with offsets we still have access to the
original string, so we can simply look if previous character (if it
exists) of a token, is actually a space. This will obviously be wrong
for tokenizers that contain spaces within tokens, tokenizers where
offsets include spaces too (Don't think there are a lot).

This heuristic hopefully is fully bc and still can handle non-word based
tokenizers.

* Updating test with real values.

* We still need the older "correct" heuristic to prevent fusing
punctuation.

* Adding a real warning when important.

* Add new multiple-choice example, remove old one

* Add possibility to ignore imports in test_fecther

* Style

* add classifier_dropout to Electra

* no type annotations yet
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add classifier_dropout to Electra

* add classifier_dropout to Electra ForTokenClass.

* add classifier_dropout to bert

* add classifier_dropout to roberta

* add classifier_dropout to big_bird

* add classifier_dropout to mobilebert

* empty commit to trigger CI

* add classifier_dropout to reformer

* add classifier_dropout to ConvBERT

* add classifier_dropout to Albert

* add classifier_dropout to Albert
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Faster list concat for trainer_pt_utils.get_length_grouped_indices() (#11825)

get_length_grouped_indices() in LengthGroupedSampler and DistributedLengthGroupedSampler
is prohibitively slow for large number of megabatches (in test case takes hours for ~270k
megabatches with 100 items each) due to slow list concatenation with sum(megabatches, []).

Resolves: #11795
Co-authored-by: ctheodoris <cvtheodo@ds.dfci.harvard.edu>

* Replace double occurrences as the last step (#11367)

* [Flax] Fix PyTorch import error (#11839)

* fix_torch_device_generate_test

* remove @

* change pytorch import to flax import

* Fix reference to XLNet (#11846)

* Switch mem metrics flag (#11851)

* Switch mem metrics flag

* Update src/transformers/training_args.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Fix flos single node (#11844)

* fixing flos bug/typo ...

* fix_torch_device_generate_test

* remove @

* add truncate

* finish

* correct test

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

* clean tests

* correct normalization for truncation

* remove casting

* up

* save intermed

* finish

* finish

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

* fix_torch_device_generate_test

* remove @

* pin git python

* make style

* typo

* Proposal

* Testing pipelines slightly better.

- Overall same design
- Metaclass to get proper different tests instead of subTest (not well
supported by Pytest)
- Added ANY meta object to make output checking more readable.
- Skipping architectures either without tiny_config or without
architecture.

* Small fix.

* Fixing the tests in case of None value.

* Oups.

* Rebased with more architectures.

* Fixing reformer tests (no override anymore).

* Adding more options for model tester config.
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* document Deepspeed-Inference and parallelformers

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

* [Deepspeed] warmup_ratio docs

* Update docs/source/main_classes/deepspeed.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* style

* Update docs/source/main_classes/deepspeed.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

* Add _CHECKPOINT_FOR_DOC

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

* Add versioning system to fast tokenizer files

* Deal with offline mode

* Use staging env in tests

* Style

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

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

* Refer warmup_ratio when setting warmup_num_steps.

* Add a method to get number of warmup steps to TrainerArguments class.

* Fix.

* Fix.

* Expose get_config() on ModelTesters

* Typo

* [trainer] fix % 0

* sanity checks

* fix logging_strategy

* correction

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

* fix_torch_device_generate_test

* remove @

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