When supplied by Keras deserialization, the config parameter to initializers
will be a dict. So intercept it and convert to PretrainedConfig object (and
store in instance attribute for get_config to get at it) before passing to the
actual initializer. To accomplish this, and repeat as little code as possible,
use a class decorator on TF*MainLayer classes.
* add first copy past test to tf 2 generate
* add tf top_k_top_p_filter fn
* add generate function for TF
* add generate function for TF
* implemented generate for all models expect transfoXL
* implemented generate for all models expect transfoXL
* implemented generate for all models expect transfoXL
* make style
* change permission of test file to correct ones
* delete ipdb
* delete ipdb
* fix bug and finish simple gpt2 integration test
* clean test file
* clean test file
* make style
* make style
* make style
* make style
* change import style
* change import style
* make style
* make style
* add decorators
* add decorators
* fix tf ctrl bug dim => axis in TF
* make style
* make style
* refactored test file
* refactored test file
* take out test_torch_tf_conversion if nothing is defined
* take out test_torch_tf_conversion if nothing is defined
* remove useless files
* remove useless files
* fix conflicts
* fix conflicts
* fix conflicts
* fix conflicts
* fix conflicts
* solve conflicts
* solve conflicts
* fix conflicts
* fix conflicts
* merge conflicts
* delete ipdb
* exposed top_k_top_p_filtering fns
* delete weirdly created w! file
* add comment to test tf common modeling
* fix conflicts
* fix conflicts
* make style
* merge conflicts
* make style
* change tf.tensor.shape to shape_list(tensor)
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.
