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* [trainer] fix ignored columns logger

This PR fixes a confusing log entry that says:
```
The following columns in the evaluation set don't have a corresponding argument in `T5ForConditionalGeneration.forward` and have been ignored: .
```
when everything is in order.

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

* move old s2s scripts to legacy

* add the tests back

* proper rename

* restore

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas@stason.org>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>

* fix run_seq2seq.py; porting DeepSpeed tests to it

* unrefactor

* defensive programming

* defensive programming 2

* port the rest of the trainer tests

* style

* a cleaner scripts dir finder

* cleanup

* add tokenizer for mBART-50

* update tokenizers

* make src_lang and tgt_lang optional

* update tokenizer test

* add setter

* update docs

* update conversion script

* update docs

* update conversion script

* update tokenizer

* update test

* update docs

* doc

* address Sylvain's suggestions

* fix test

* fix formatting

* nits

* Fix template

* Update Seq2Seq tests

* Add check-ops script

* Finish to implement check_tf_ops and start the test

* Make the test mandatory only for BERT

* Update tf_ops folder

* Remove useless classes

* Add the ONNX test for GPT2 and BART

* Add a onnxruntime slow test + better opset flexibility

* Fix test + apply style

* fix tests

* Switch min opset from 12 to 10

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

* Fix GPT2

* Remove extra shape_list usage

* Fix GPT2

* Address Morgan's comments
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

Fixes #10168

* save fast tokenizer + add info logs

* fix tests

* remove the saving of fast tokenizer

* Conversion from slow to fast for BPE spm vocabs contained an error.

- There is only 1 test currently (tokenizers + slow) that used the modified path
and it's reformer, which does not contain any ids modification so the
bug was silent for now.
- The real issue is that vocab variable was overloaded by
SentencePieceExtractor, leading to Slow specific vocab oddities to be
completely ignored
- The bug was reported here https://github.com/huggingface/transformers/issues/9518
- Ran the complete tokenization test suite with slow without error
(`RUN_SLOW=1 pytest -sv tests/test_tokenization_*`)

* Remove rebase error.

* Adding the fixture.

* [hf_api] delete deprecated methods and tests

cc @lhoestq

* Update test_hf_api.py

* Fix typo

* apply suggestion
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* fix rouge metrics and task specific params

* fix typo

* round metrics

* typo

* remove task_specific_params

* Refactor things out of main train

* Store signature

* Add SageMakerTrainer

* Init + Copyright

* Address review comments

* init devices/setup explicitly

* docs + test

* simplify

* cleanup

* cleanup

* cleanup

* correct the required dist setup

* derive local_rank from env LOCAL_RANK

* save intermediate

* finish batch the same as fairseq

* add normalization

* fix batched input

* add better comment

* Update src/transformers/models/wav2vec2/modeling_wav2vec2.py

* add nice docstring

* add tokenizer tests

* make all slow tests pass

* finish PR

* correct import

* Update:community.md, new nb add

* feat: updated grammar on  nb description

* Update: Train summarizer for BlenderBotSmall

* remove xnli_compute_metrics, add load_dataset, load_metric, set_seed,metric.compute,load_metric

* fix

* fix

* fix

* push

* fix

* everything works

* fix init

* fix

* special treatment for sepconv1d

* style

* 🙏🏽

* add doc and cleanup


* fix doc

* fix doc again

* fix doc again

* Apply suggestions from code review

* make style

* Proposal that should work

* Remove needless code

* Fix test

* Apply suggestions from code review

* remove xnli_compute_metrics, add load_dataset, load_metric, set_seed,metric.compute,load_metric

* amend README

* removed data_args.task_name and replaced with task_name = "xnli"; use split function to load train and validation dataset separately; remove __post_init__; remove flag --task_name from README.

* removed dict task_to_keys, use str "xnli" instead of variable task_name, change preprocess_function to use examples["premise"], examples["hypothesis"] directly, remove sentence1_key and sentence2_key, change compute_metrics function to cater only to accuracy metric, add condition for train_langauge is None when using dataset.load_dataset()

* removed `torch.distributed.barrier()` and `import torch` as `from_pretrained` is able to do the work; amend README

* free up memory at the end of train

* rework tests

* consistent formatting

* correction

* add forced logits processors

* delete adjust_logits method

* add forced_eos_token_id argument in config

* add tests for forced logits processors

* update gen utils tests

* add forced option to tf generate

* remove adjust_logits method from tf models

* update adjust_logits for marian

* delete _force_token_id_to_be_generated method

* style

* import warnings

* pass max_length to _get_logits_processor

* set forced_eos_token_id to None

* set forced attributes in conf utils

* typo

* fix rag generate

* add forced_eos_token_id in rag config

* remove force_bos_token_to_be_generated from BartConfig

* remove _force_token_ids_generation from FSMT

* nit

* fix negative constant

* apply suggestions from code review

* Fix test

* Remove commented test

* Fix name

* Apply style

* Fix check copies

* Remove prints

* Restore boolean

* Fix reshape