* cleanup torch unittests: part 2
* remove trailing comma added by isort, and which breaks flake
* one more comma
* revert odd balls
* part 3: odd cases
* more ["key"] -> .key refactoring
* .numpy() is not needed
* more unncessary .numpy() removed
* more simplification
* TF outputs and test on BERT
* Albert to DistilBert
* All remaining TF models except T5
* Documentation
* One file forgotten
* TF outputs and test on BERT
* Albert to DistilBert
* All remaining TF models except T5
* Documentation
* One file forgotten
* Add new models and fix issues
* Quality improvements
* Add T5
* A bit of cleanup
* Fix for slow tests
* Style
* improve unit tests
this is a sample of one test according to the request in https://github.com/huggingface/transformers/issues/5973
before I apply it to the rest
* batch 1
* batch 2
* batch 3
* batch 4
* batch 5
* style
* non-tf template
* last deletion of check_loss_output
* Switch from return_tuple to return_dict
* Fix test
* [WIP] Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleC… (#5614)
* Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleChoice} models and tests
* AutoModels
Tiny tweaks
* Style
* Final changes before merge
* Re-order for simpler review
* Final fixes
* Addressing @sgugger's comments
* Test MultipleChoice
* Rework TF trainer (#6038)
* Fully rework training/prediction loops
* fix method name
* Fix variable name
* Fix property name
* Fix scope
* Fix method name
* Fix tuple index
* Fix tuple index
* Fix indentation
* Fix variable name
* fix eval before log
* Add drop remainder for test dataset
* Fix step number + fix logging datetime
* fix eval loss value
* use global step instead of step + fix logging at step 0
* Fix logging datetime
* Fix global_step usage
* Fix breaking loop + logging datetime
* Fix step in prediction loop
* Fix step breaking
* Fix train/test loops
* Force TF at least 2.2 for the trainer
* Use assert_cardinality to facilitate the dataset size computation
* Log steps per epoch
* Make tfds compliant with TPU
* Make tfds compliant with TPU
* Use TF dataset enumerate instead of the Python one
* revert previous commit
* Fix data_dir
* Apply style
* rebase on master
* Address Sylvain's comments
* Address Sylvain's and Lysandre comments
* Trigger CI
* Remove unused import
* Switch from return_tuple to return_dict
* Fix test
* Add recent model
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Julien Plu <plu.julien@gmail.com>
* remove references to old API in docstring - update data processors
* style
* fix tests - better type checking error messages
* better type checking
* include awesome fix by @LysandreJik for #5310
* updated doc and examples
* DOC: Replace instances of ``config.output_attentions`` with function argument ``output_attentions``
* DOC: Apply Black Formatting
* Fix errors where output_attentions was undefined
* Remove output_attentions in classes per review
* Fix regressions on tests having `output_attention`
* Fix further regressions in tests relating to `output_attentions`
Ensure proper propagation of `output_attentions` as a function parameter
to all model subclasses
* Fix more regressions in `test_output_attentions`
* Fix issues with BertEncoder
* Rename related variables to `output_attentions`
* fix pytorch tests
* fix bert and gpt2 tf
* Fix most TF tests for `test_output_attentions`
* Fix linter errors and more TF tests
* fix conflicts
* DOC: Apply Black Formatting
* Fix errors where output_attentions was undefined
* Remove output_attentions in classes per review
* Fix regressions on tests having `output_attention`
* fix conflicts
* fix conflicts
* fix conflicts
* fix conflicts
* fix pytorch tests
* fix conflicts
* fix conflicts
* Fix linter errors and more TF tests
* fix tf tests
* make style
* fix isort
* improve output_attentions
* improve tensorflow
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* 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
* First pass on utility classes and python tokenizers
* finishing cleanup pass
* style and quality
* Fix tests
* Updating following @mfuntowicz comment
* style and quality
* Fix Roberta
* fix batch_size/seq_length inBatchEncoding
* add alignement methods + tests
* Fix OpenAI and Transfo-XL tokenizers
* adding trim_offsets=True default for GPT2 et RoBERTa
* style and quality
* fix tests
* add_prefix_space in roberta
* bump up tokenizers to rc7
* style
* unfortunately tensorfow does like these - removing shape/seq_len for now
* Update src/transformers/tokenization_utils.py
Co-Authored-By: Stefan Schweter <stefan@schweter.it>
* Adding doc and docstrings
* making flake8 happy
Co-authored-by: Stefan Schweter <stefan@schweter.it>
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 change is mostly autogenerated with:
$ python -m autoflake --in-place --recursive --remove-all-unused-imports --ignore-init-module-imports examples templates transformers utils hubconf.py setup.py
I made minor changes in the generated diff.
This change is mostly autogenerated with:
$ python -m autoflake --in-place --recursive examples templates transformers utils hubconf.py setup.py
I made minor changes in the generated diff.
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.
