GitLab

* [whisper integration] use parquet dataset for testing

* propagate to others

* more propagation

* last one

* First testing updating config tests

* Use run_common_tests

* Pass datasets trust_remote_code

* Pass trust_remote_code in more tests

* Add trust_remote_dataset_code arg to some tests

* Revert "Temporarily pin datasets upper version to fix CI"

This reverts commit b7672826.

* Pass trust_remote_code in librispeech_asr_dummy docstrings

* Revert "Pin datasets<2.20.0 for examples"

This reverts commit 833fc17a.

* Pass trust_remote_code to all examples

* Revert "Add trust_remote_dataset_code arg to some tests" to research_projects

* Pass trust_remote_code to tests

* Pass trust_remote_code to docstrings

* Fix flax examples tests requirements

* Pass trust_remote_dataset_code arg to tests

* Replace trust_remote_dataset_code with trust_remote_code in one example

* Fix duplicate trust_remote_code

* Replace args.trust_remote_dataset_code with args.trust_remote_code

* Replace trust_remote_dataset_code with trust_remote_code in parser

* Replace trust_remote_dataset_code with trust_remote_code in dataclasses

* Replace trust_remote_dataset_code with trust_remote_code arg

* Rename to test_model_common_attributes
The method name is misleading - it is testing being able to get and set embeddings, not common attributes to all models

* Explicitly skip

* add tests for batching support

* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* fixes and comments

* use cosine distance for conv models

* skip mra model testing

* Update tests/models/vilt/test_modeling_vilt.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* finzalize  and make style

* check model type by input names

* Update tests/models/vilt/test_modeling_vilt.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fixed batch size for all testers

* Revert "fixed batch size for all testers"

This reverts commit 525f3a0a058f069fbda00352cf202b728d40df99.

* add batch_size for all testers

* dict from model output

* do not skip layoutlm

* bring back some code from git revert

* Update tests/test_modeling_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/test_modeling_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* clean-up

* where did minus go in tolerance

* make whisper happy

* deal with consequences of losing minus

* deal with consequences of losing minus

* maskformer needs its own test for happiness

* fix more models

* tag flaky CV models from Amy's approval

* make codestyle

---------
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

fix
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* initial commit

* Add inital testing files and modify __init__ files to add UnivNet imports.

* Fix some bugs

* Add checkpoint conversion script and add references to transformers pre-trained model.

* Add UnivNet entries for auto.

* Add initial docs for UnivNet.

* Handle input and output shapes in UnivNetGan.forward and add initial docstrings.

* Write tests and make them pass.

* Write docs.

* Add UnivNet doc to _toctree.yml and improve docs.

* fix typo

* make fixup

* make fix-copies

* Add upsample_rates parameter to config and improve config documentation.

* make fixup

* make fix-copies

* Remove unused upsample_rates config parameter.

* apply suggestions from review

* make style

* Verify and add reason for skipped tests inherited from ModelTesterMixin.

* Add initial UnivNetGan integration tests

* make style

* Remove noise_length input to UnivNetGan and improve integration tests.

* Fix bug and make style

* Make UnivNet integration tests pass

* Add initial code for UnivNetFeatureExtractor.

* make style

* Add initial tests for UnivNetFeatureExtractor.

* make style

* Properly initialize weights for UnivNetGan

* Get feature extractor fast tests passing

* make style

* Get feature extractor integration tests passing

* Get UnivNet integration tests passing

* make style

* Add UnivNetGan usage example

* make style and use feature extractor from hub in integration tests

* Update tips in docs

* apply suggestions from review

* make style

* Calculate padding directly instead of using get_padding methods.

* Update UnivNetFeatureExtractor.to_dict to be UnivNet-specific.

* Update feature extractor to support using model(**inputs) and add the ability to generate noise and pad the end of the spectrogram in __call__.

* Perform padding before generating noise to ensure the shapes are correct.

* Rename UnivNetGan.forward's noise_waveform argument to noise_sequence.

* make style

* Add tests to test generating noise and padding the end for UnivNetFeatureExtractor.__call__.

* Add tests for checking batched vs unbatched inputs for UnivNet feature extractor and model.

* Add expected mean and stddev checks to the integration tests and make them pass.

* make style

* Make it possible to use model(**inputs), where inputs is the output of the feature extractor.

* fix typo in UnivNetGanConfig example

* Calculate spectrogram_zero from other config values.

* apply suggestions from review

* make style

* Refactor UnivNet conversion script to use load_state_dict (following persimmon).

* Rename UnivNetFeatureExtractor to UnivNetGanFeatureExtractor.

* make style

* Switch to using torch.tensor and torch.testing.assert_close for testing expected values/slices.

* make style

* Use config in UnivNetGan modeling blocks.

* make style

* Rename the spectrogram argument of UnivNetGan.forward to input_features, following Whisper.

* make style

* Improving padding documentation.

* Add UnivNet usage example to the docs.

* apply suggestions from review

* Move dynamic_range_compression computation into the mel_spectrogram method of the feature extractor.

* Improve UnivNetGan.forward return docstring.

* Update table in docs/source/en/index.md.

* make fix-copies

* Rename UnivNet components to have pattern UnivNet*.

* make style

* make fix-copies

* Update docs

* make style

* Increase tolerance on flaky unbatched integration test.

* Remove torch.no_grad decorators from UnivNet integration tests to try to avoid flax/Tensorflow test errors.

* Add padding_mask argument to UnivNetModel.forward and add batch_decode feature extractor method to remove padding.

* Update documentation and clean up padding code.

* make style

* make style

* Remove torch dependency from UnivNetFeatureExtractor.

* make style

* Fix UnivNetModel usage example

* Clean up feature extractor code/docstrings.

* apply suggestions from review

* make style

* Add comments for tests skipped via ModelTesterMixin flags.

* Add comment for model parallel tests skipped via the test_model_parallel ModelTesterMixin flag.

* Add # Copied from statements to copied UnivNetFeatureExtractionTest tests.

* Simplify UnivNetFeatureExtractorTest.test_batch_decode.

* Add support for unbatched padding_masks in UnivNetModel.forward.

* Refactor unbatched padding_mask support.

* make style