* TF Model train and eval step metrics for seq2seq models.
When using a model with a seq2seq output compute metrics against logits.
* Removing vestigial code
Co-authored-by: matt <rocketknight1@gmail.com>
* Fix Bart
* Fix Blenderbot{,_small}
* Fix LED
* Fix Marian
* Fix MBart
* Fix Pegasus
* Fix T5
* Add test for generation with head_mask
* Add a common TF test
* Override a test for the LED model as head masking is not yet properly implemented
* Remove all head_masks from input preparation for LED
* Drop masking for T5 as it needs a bit of refactor
* Add check-ops script
* Finish to implement check_tf_ops and start the test
* Make the test mandatory only for BERT
* Update tf_ops folder
* Remove useless classes
* Add the ONNX test for GPT2 and BART
* Add a onnxruntime slow test + better opset flexibility
* Fix test + apply style
* fix tests
* Switch min opset from 12 to 10
* Update src/transformers/file_utils.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Fix GPT2
* Remove extra shape_list usage
* Fix GPT2
* Address Morgan's comments
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Add head_mask/decoder_head_mask for TF BART models
* Add head_mask and decoder_head_mask input arguments for TF BART-based
models as a TF counterpart to the PR #9569
* Add test_headmasking functionality to tests/test_modeling_tf_common.py
* TODO: Add a test to verify that we can get a gradient back for
importance score computation
* Remove redundant #TODO note
Remove redundant #TODO note from tests/test_modeling_tf_common.py
* Fix assertions
* Make style
* Fix ...Model input args and adjust one new test
* Add back head_mask and decoder_head_mask to BART-based ...Model
after the last commit
* Remove head_mask ande decoder_head_mask from input_dict
in TF test_train_pipeline_custom_model as these two have different
shape than other input args (Necessary for passing this test)
* Revert adding global_rng in test_modeling_tf_common.py
* Resize the biases in same time than the embeddings
* Trigger CI
* Biases are not reset anymore
* Remove get_output_embeddings + better LM model detection in generation utils
* Apply style
* First test on BERT
* Update docstring + new name
* Apply the new resizing logic to all the models
* fix tests
* Apply style
* Update the template
* Fix naming
* Fix naming
* Apply style
* Apply style
* Remove unused import
* Revert get_output_embeddings
* Trigger CI
* Update num parameters
* Restore get_output_embeddings in TFPretrainedModel and add comments
* Style
* Add decoder resizing
* Style
* Fix tests
* Separate bias and decoder resize
* Fix tests
* Fix tests
* Apply style
* Add bias resizing in MPNet
* Trigger CI
* Apply style
* Use the CI to identify failing tests
* Remove from all examples and tests
* More default switch
* Fixes
* More test fixes
* More fixes
* Last fixes hopefully
* Use the CI to identify failing tests
* Remove from all examples and tests
* More default switch
* Fixes
* More test fixes
* More fixes
* Last fixes hopefully
* Run on the real suite
* Fix slow tests
* Test TF GPU CI
* Change cache
* Fix missing torch requirement
* Fix some model tests
Style
* LXMERT
* MobileBERT
* Longformer skip test
* XLNet
* The rest of the tests
* RAG goes OOM in multi gpu setup
* YAML test files
* Last fixes
* Skip doctests
* Fill mask tests
* Yaml files
* Last test fix
* Style
* Update cache
* Change ONNX tests to slow + use tiny model
* splitting fast and slow tokenizers [WIP]
* [WIP] splitting sentencepiece and tokenizers dependencies
* update dummy objects
* add name_or_path to models and tokenizers
* prefix added to file names
* prefix
* styling + quality
* spliting all the tokenizer files - sorting sentencepiece based ones
* update tokenizer version up to 0.9.0
* remove hard dependency on sentencepiece 🎉
* and removed hard dependency on tokenizers 🎉
* update conversion script
* update missing models
* fixing tests
* move test_tokenization_fast to main tokenization tests - fix bugs
* bump up tokenizers
* fix bert_generation
* update ad fix several tokenizers
* keep sentencepiece in deps for now
* fix funnel and deberta tests
* fix fsmt
* fix marian tests
* fix layoutlm
* fix squeezebert and gpt2
* fix T5 tokenization
* fix xlnet tests
* style
* fix mbart
* bump up tokenizers to 0.9.2
* fix model tests
* fix tf models
* fix seq2seq examples
* fix tests without sentencepiece
* fix slow => fast conversion without sentencepiece
* update auto and bert generation tests
* fix mbart tests
* fix auto and common test without tokenizers
* fix tests without tokenizers
* clean up tests lighten up when tokenizers + sentencepiece are both off
* style quality and tests fixing
* add sentencepiece to doc/examples reqs
* leave sentencepiece on for now
* style quality split hebert and fix pegasus
* WIP Herbert fast
* add sample_text_no_unicode and fix hebert tokenization
* skip FSMT example test for now
* fix style
* fix fsmt in example tests
* update following Lysandre and Sylvain's comments
* Update src/transformers/testing_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/testing_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* 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
* 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
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
* add some t5 integration tests
* finish summarization and translation integration tests for T5 - results loook good
* add tf test
* fix == vs is bug
* fix tf beam search error and make tf t5 tests pass
* make decoder input ids optional for t5 training
* lm_lables should not be shifted in t5
* add tests
* finish shift right functionality for PT T5
* move shift right to correct class
* cleaner code
* replace -100 values with pad token id
* add assert statement
* remove unnecessary for loop
* make style
* fix conflicts
* update bart max length test
* correct spelling mistakes
* implemented model specific encode function
* fix merge conflicts
* better naming
* save intermediate state -> need to rethink strucuture a bit
* leave tf problem as it is for now
* current version
* add layers.pop
* remove ipdb
* make style
* clean return cut decoding
* remove ipdbs
* Fix restoring layers in the decoders that doesnt exists.
* push good intermediate solution for now
* fix conflicts
* always good to refuse to merge conflicts when rebasing
* fix small bug
* improve function calls
* remove unused file
* add correct scope behavior for t5_generate
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>
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.
