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* nlp -> datasets

* More nlp -> datasets

* Woopsie

* More nlp -> datasets

* One last

* feat: allow padding_text for any generative model

* docs(pipelines.py): correct typo

* Update src/transformers/pipelines.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* feat: rename padding_text to prefix

* fix: cannot tokenize empty text

* fix: pass prefix arg to pipeline

* test: add prefix to text-generetation pipeline

* style: fix style

* style: clean code and variable name more explicit

* set arg docstring to optional
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* remove the implied defaults to :obj:`None`

* fix bug in the original

* replace to :obj:`True`, :obj:`False`

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

* Add cache_dir to save features TextDataset

This is in case the dataset is in a RO filesystem, for which is the case
in tests (GKE TPU tests).

* style

* Clarify shuffle

* clarify shuffle
Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>

* broken test

* batch parity

* tests pass

* boom boom

* boom boom

* split out bart tokenizer tests

* fix tests

* boom boom

* Fixed dataset bug

* Fix marian

* Undo extra

* Get marian working

* Fix t5 tok tests

* Test passing

* Cleanup

* better assert msg

* require torch

* Fix mbart tests

* undo extra decoder_attn_mask change

* Fix import

* pegasus tokenizer can ignore src_lang kwargs

* unused kwarg test cov

* boom boom

* add todo for pegasus issue

* cover one word translation edge case

* Cleanup

* doc

* Align TF NER example over the PT one

* Fix Dataset call

* Fix gradient accumulation training

* Apply style

* Address Sylvain's comments

* Address Sylvain's comments

* Apply style

* Allow tests in examples to use cuda or fp16,if they are available

The tests in examples didn't use the cuda or fp16 even if they where available.
- The text classification example (`run_glue.py`) didn't use the fp16 even if it was available but
  the device was take based on the availablity(cuda/cpu).
- The language-modeling example (`run_language_modeling.py`) was having `--no_cuda` argument
  which made the test to work without cuda. This example is having issue when running with fp16
  thus it not enabled (got an assertion error for perplexity due to it higher value).
- The cuda and fp16 is not enabled for question-answering example (`run_squad.py`) as it is having a
  difference in the f1 score.
- The text-generation example (`run_generation.py`) will take the cuda or fp16 whenever it is available.

Resolves some of: #5057

* Unwanted import of is_apex_available was removed

* Made changes to test examples file to have the pass --fp16 only if cuda and apex is avaliable
- run_glue.py: Removed the check for cuda and fp16.
- run_generation.py: Removed the check for cuda and fp16 also removed unwanted flag creation.

* Incorrectly sorted imports fixed

* The model needs to be converted to half precision

* Formatted single line if condition statement to multiline

* The torch_device also needed to be checked before running the test on examples
- The tests in examples which uses cuda should also depend from the USE_CUDA flag,
  similarly to the rest of the test suite. Even if we decide to set USE_CUDA to
  True by default, setting USE_CUDA to False should result in the examples not using CUDA

* Format some of the code in test_examples file

* The improper import of is_apex_available was sorted

* Formatted the code to keep the style standards

* The comma at the end of list giving a flake8 issue was fixed

* Import sort was fixed

* Removed the clean_test_dir function as its not used right now

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

* [testing] switch to a new TestCasePlus + get_auto_remove_tmp_dir() for auto-removal of tmp dirs

* respect after=True for tempfile, simplify code

* comments

* comment fix

* put `before` last in args, so can make debug even faster