GitLab

Co-authored-by: Jeff Zhang <jeffzhang@fb.com>

* Add libritts

Add LibriTTS dataset draft

* Add libritts

Use two separate ids for utterance_id.

* Update output form

Use full_id as utterance_id.

* Update format

Add space and test black format

* Update test method

* Add audio and text test

Generate audio and test files on-the-fly in test 

* Update format

* Fix test error and remove assets libritts

The test error is fixed by sorting the file in 4th element instead of 2nd element in samples. Since the files are generated on-the-fly, so the the libritts files in assets are removed.

* Add seed in `get_whitenoise` function

* Change utterance to text

Change `_utterance` to `_text`.
Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

* Change 'sox' to 'default'

* Make tests backend aware by introducing TorchaudioTestCase and reset backend for each TestCase.

* Set backends for the test cases that require specific backend.

* Refactor backend switching

1. Do not rely on global variables for backend switch
   So that load/save/info/load_wav functions will be torchscript-able
2. Add no_backend module to for the case there is no backend module available
   [bonus] This allows the whole codebase importable on systems that do not have torchaudio C++ extension nor soundfile.

* Add cmu_arctic dataset

* add dataset name

* update audio test file with whitenoise.wav file

* add test text file

* update text method and file name

* update comment

* change datasets order in doc

* add line length
Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

* Added the popular GTZAN dataset:

* Added the GTZAN class in torchaudio.datasets using the same format as the rest of the datasets.
* Added the appropriate test function in test_datasets.py.
* Added the GTZAN class in the datasets.rst documentation file.

* Addressed review issues in PR #668

* Added dummy noise .wav in `test/assets/`
* Removed transforms of input and output from the dataset
  `__init__` function, as well as the corresponding methods.
* Replaced rendundant `filtered` and `subset` methods from
  class initialization and also changed the corresponding
  assertion message.

* Fixed E303: too many blank lines error

* Added GTZAN to __init__.__all__

* Fixed incorrectly not importing GTZAN

* removed duplicate warning

* lint
Co-authored-by: Vincent QB <vincentqb@users.noreply.github.com>

* Turn on tests when building through conda-build

* skip one failling test on windows.

* Switch to unittest

* Fix conda env activation

* add linux only condition

* Fix librosa installation

* conda-forge channel as a fallback

* Revert "conda-forge channel as a fallback"

This reverts commit 8c15f6638e34792640a3de3e057d9c2995425180.

* Try the pytorch way

* Use conda-forge

* Disable conda-forge

* Install future at setup env

* Move linux unittest CI job tools to dedicated directory

* Restore Linux scripts and move the updated souces to a new subdir

* Add back future

* Remove comments
Co-authored-by: Vincent Quenneville-Belair <vincentqb@gmail.com>
Co-authored-by: moto <855818+mthrok@users.noreply.github.com>

This PR aims the following things;
1. Introduce and adopt helper function `get_asset_path` that abstract the logic to construct path to test assets.
2. Remove `create_temp_assets_dir` anywhere except `test_io`.

The benefits of doing so are,
a. the test code becomes simpler (no manual construction of asset path with `os.path.join`)
b. No unnecessary directory creation and file copies.

For 2. and b. tests in `test_io.py` (or tests that use `torchaudio.save`) are the only tests that need to write file to the disc, where the use of temporary directory makes it cleaner, therefore, `create_temp_assets_dir` is not necessary elsewhere. (still, `test_io` does not need to copy the entire asset directory, but that's not the point here.)

Also if any test is accidentally overwriting an asset data, not using a copy will make us aware of such behavior, so it is better to get rid of `create_temp_assets_dir`.

* fix download

* fix reading tsv archive

* add new languages

* maintain same structure as other datasets

* update CommonVoice Tests

* fix

* change directory name

* remove extra line

* add speechcommand dataset and test

* prepend the full path to each result

* add missing param on docstring in walk_files

* add file to run tests on SpeechCommand Dataset

* reduce logic

* update test on SpeechCommands

* correct the indentation on docstring walk_files

* flake8 compliance

* change tuple type returned. move path split logic in load item.

* typo in name.

* redundant file path.

* filter background noise.
Co-authored-by: Vincent QB <vincentqb@users.noreply.github.com>

* LJ Speech dataset

* refactoring

as per @vincentqb's suggestions

* close file.

* staying with datapoints as tuples until further notice.

* loading tsv as dict.

* BackgroundGenerator
* renaming disk cache.

Fix test for datasets.

* new dataset format.
* add basic test.
* files for testing.
* serialization using torch.
* add diskcache.
* adding deprecation warnings.
* removing legacy.
* warning about transforms.
* detecting file format using reader.