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* [test schedulers] small improvement

* cleanup

* AdaFactor optimizer ported from fairseq. Tested for T5 finetuning and MLM -- reduced memory consumption compared to ADAM.

* update PR fixes, add basic test

* bug -- incorrect params in test

* bugfix -- import Adafactor into test

* bugfix -- removed accidental T5 include

* resetting T5 to master

* bugfix -- include Adafactor in __init__

* longer loop for adafactor test

* remove double error class declare

* lint

* black

* isort

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

* single docstring

* Cleanup docstring
Co-authored-by: Nikolai Y <nikolai.yakovenko@point72.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* [wip] add get_polynomial_decay_schedule_with_warmup

* style

* add assert

* change lr_end to a much smaller default number

* check for exact equality

* [model_cards] electra-base-turkish-cased-ner (#6350)

* for electra-base-turkish-cased-ner

* Add metadata
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Temporarily de-activate TPU CI

* Update modeling_tf_utils.py (#6372)

fix typo: ckeckpoint->checkpoint

* the test now works again (#6371)

* correct pl link in readme (#6364)

* refactor almost identical tests (#6339)

* refactor almost identical tests

* important to add a clear assert error message

* make the assert error even more descriptive than the original bt

* Small docfile fixes (#6328)

* Patch models (#6326)

* TFAlbertFor{TokenClassification, MultipleChoice}

* Patch models

* BERT and TF BERT info


s

* Update check_repo

* Ci GitHub caching (#6382)

* Cache Github Actions CI

* Remove useless file

* Colab button (#6389)

* Add colab button

* Add colab link for tutorials

* Fix links for open in colab (#6391)

* Update src/transformers/optimization.py

consistently use lr_end=1e-7 default
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* [wip] add get_polynomial_decay_schedule_with_warmup

* style

* add assert

* change lr_end to a much smaller default number

* check for exact equality

* Update src/transformers/optimization.py

consistently use lr_end=1e-7 default
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* remove dup (leftover from merge)

* convert the test into the new refactored format

* stick to using the current_step as is, without ++
Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Alexander Measure <ameasure@gmail.com>
Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* refactor almost identical tests

* important to add a clear assert error message

* make the assert error even more descriptive than the original bt

This is the same change as for (TF)CommonTestCases for modeling.

This construct isn't used anymore these days.

Running python tests/test_foo.py puts the tests/ directory on
PYTHONPATH, which isn't representative of how we run tests.

Use python -m unittest tests/test_foo.py instead.

This is the result of:

    $ isort --recursive examples templates transformers utils hubconf.py setup.py

This is the result of:

    $ black --line-length 119 examples templates transformers utils hubconf.py setup.py

There's a lot of fairly long lines in the project. As a consequence, I'm
picking the longest widely accepted line length, 119 characters.

This is also Thomas' preference, because it allows for explicit variable
names, to make the code easier to understand.

* Switch to plain unittest for skipping slow tests.

Add a RUN_SLOW environment variable for running them.

* Switch to plain unittest for PyTorch dependency.

* Switch to plain unittest for TensorFlow dependency.

* Avoid leaking open files in the test suite.

This prevents spurious warnings when running tests.

* Fix unicode warning on Python 2 when running tests.

The warning was:

    UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal

* Support running PyTorch tests on a GPU.

Reverts 27e015bd.

* Tests no longer require pytest.

* Make tests pass on cuda

Custom schedulers are currently initiated by wrapping Pytorch's LambdaLR
class and passing a method of the wrapping class to the __init__
function of LambdaLR. This approach is not appropriate for several
reasons:

1. one does not need to define a class when it only defines a
__init__() method;
2. instantiating the parent class by passing a method of the child class
creates a cyclical reference which leads to memory leaks. See issues #1742 and #1134.

In this commit we replace the wrapper classes with functions that
instantiate `LambdaLR` with a custom learning rate function. We use a
closure to specify the parameter of the latter. We also do a bit of
renaming within the function to explicit the behaviour and removed
docstrings that were subsequently not necessary.

- added some images for illustration
- updated comments in optimization

- removed unused plotting code
- using ABC for LRSchedule
- added some schedule object init tests