GitLab

* Use return_dict=True in all tests

* Formatting

* Add MobileBert

* Quality + Conversion script

* style

* Update src/transformers/modeling_mobilebert.py

* Links to S3

* Style

* TFMobileBert

Slight fixes to the pytorch MobileBert
Style

* MobileBertForMaskedLM (PT + TF)

* MobileBertForNextSentencePrediction (PT + TF)

* MobileFor{MultipleChoice, TokenClassification} (PT + TF)


ss

* Tests + Auto

* Doc

* Tests

* Addressing @sgugger's comments

* Adressing @patrickvonplaten's comments

* Style

* Style

* Integration test

* style

* Model card
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* first commit

* add new auto models

* better naming

* fix bert automodel

* fix automodel for pretraining

* add models to init

* fix name typo

* fix typo

* better naming

* future warning instead of depreciation warning

* Split LMBert model in two

* Fix example

* Remove lm_labels

* Adapt tests, refactor prepare_for_generation

* Fix merge

* Hide BeartLMHeadModel

* Deal with multiple choice in common tests

* Kill model archive maps

* Fixup

* Also kill model_archive_map for MaskedBertPreTrainedModel

* Unhook config_archive_map

* Tokenizers: align with model id changes

* make style && make quality

* Fix CI

* Hoist bert model tester for patric

* indent

* make tests work

* Update tests/test_modeling_bert.py
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
Co-authored-by: sshleifer <sshleifer@gmail.com>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

There's an inconsistency right now where:
- we load some models into CACHE_DIR
- and some models in the default cache
- and often, in both for the same models

When running the RUN_SLOW tests, this takes a lot of disk space, time, and bandwidth.

I'd rather always use the default cache

PyTorch < 1.3 requires multiplication operands to be of the same type.
This was violated when using default attention mask (i.e.,
attention_mask=None in arguments) given BERT in the decoder mode.

In particular, this was breaking Model2Model and made tutorial
from the quickstart failing.

I suspect the wrapper classes were created in order to prevent the
abstract base class (TF)CommonModelTester from being included in test
discovery and running, because that would fail.

I solved this by replacing the abstract base class with a mixin.

Code changes are just de-indenting and automatic reformattings
performed by black to use the extra line space.

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.

Caching models across test cases and across runs of the test suite makes
slow tests somewhat more bearable.

Use gettempdir() instead of /tmp in tests. This makes it easier to
change the location of the cache with semi-standard TMPDIR/TEMP/TMP
environment variables.

Fix #2222.

* 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