GitLab

closes #387

closes #382

Remove suspect logic.

Closes #304

See rationale writeup: https://github.com/pytorch/vision/pull/1321#issuecomment-531033978

* Declare file encoding to support special characters

* fix missing utf_8_encoder error in Travis tests

* Py 2.7 backwards-compat iterator

* ensure integer argument to torch.nn.functional.pad

* cast match.ceil result as integer

* test with jit.

* test passed after adding annotation, and removing get_default_dtype

* fix conversion error.

* moving test to transform.

* reverting to original test.

* move type.

* math.gcd added in python 3.5.
Co-authored-by: Vincent QB <vincentqb@users.noreply.github.com>

* Griffin-Lim Transformation Implementation

* Griffin-Lim Docs

* Remove f-string from backwards compatibility

* iSTFT is now jit-able.

* Comment changes

* Functional Implementation & now jitable

* flake8

* Doc & GPU Fix

* Librosa comparison test

* test directly griffinlim's output. tighter atol.

* matching signature to docstring.
Co-authored-by: Vincent QB <vincentqb@users.noreply.github.com>

* Fixed GPU tests

* Simplify lfilter functional

* use `torch.clamp` instead of `torch.min(..., torch.max(...))`
* remove unneeded creation of ones tensor for previous method

The current lfilter function uses min and max to essentially do a clamp
function.  I changed the code to use clamp instead.  It is more readable
than the previous version.

FYI, if you want to keep the previous way, you could make a
broadcastable tensor of size 1 instead of creating a tensor the size of
the input.
Signed-off-by: David Pollack <david@da3.net>

* Parallelize waveform windows calculation

I've parallelized the calculation of the waveform windows and also
removed the inefficient calculation within the for-loop.
Signed-off-by: David Pollack <david@da3.net>

* Refactoring and minor readability changes
Signed-off-by: David Pollack <david@da3.net>

* Remove one more creation of a temporary tensor
Signed-off-by: David Pollack <david@da3.net>

* move sox inside function calls.

* add backend switch mechanism.

* import sox at runtime, not import.

* add backend list.

* backend tests.

* creating hidden modules for backend.

* naming backend same as file: soundfile.

* remove docstring in backend file.

* test soundfile info.

* soundfile doesn't support int64.

* adding test for wav file.

* error with incorrect parameter instead of silent ignore.

* adding test across backend. using float32 as done in sox.

* backend guard decorator.

* Fix MelScale test and documentation

* revert change to tests

Skip librosa consistency test. unittest need one-line skip condition.

* Simpler amplitude_to_DB

* flake8

* use binaries just built for smoke test

* to trigger tests on PR

* trigger tests

* different build has different test

* test good, now move to official

* test good, now move to official

* Initial commit for SoX logic in VCTK

* change to train whistle file for tests

* apply probability

* adding smoke test

* adding smoke test

* fix config.yml

* trigger smoke test

* test aws erc credential

* test aws erc credential

* test aws erc credential

* test aws erc credential

* adding ecr cred

* test aws erc credential

* test aws erc credential

* test aws erc credential - different way

* test aws erc credential - different way #2

* test aws erc credential - different way #3

* test aws erc credential - different way #4

* test aws #1

* test aws erc credential, after enabling circleci setting

* fixing conda init

* add verbose output for smoke test

* add docker image build workflow

* add docker image build workflow

* fix aws ecr login

* use images build from circelci

* ready for review

* updated Readme with instructions on nightly install, also updated docker image which can make nightlies installed via pip pass

* nit

* reduce size

* fixing errors in docstring.

* move batch to functional.

* since we no longer use decoration, this fixes #165.

* remove import of _docs.

* sync docs with functionals.

* Adding transforms to documentations. Moving augmentations in transforms.

* nn.Module.

* generalizing spectrogram test.

* adding test to compile functionals.

* add cuda/cpu compilation test.

* adding transform test.

* remove standalone jit file.

* update mel scale.

* remove script decorator.

* apply to augmentations too.

* batching for transforms.

* test for batching.

* update readme.

* STFT transform and function from #285

* merge options in existing functionality.

* remove dimension 2 check. add test.

* using ...

* update spectrogram test.

* resume download, validate with md5 or sha256.

* split stream from saving. detect filename.

* validate at end too. check file size again.

* validate now operates on file object.

* expose choices of hash.

* OSS Automated Fix: Addition of Contributing

* close file.

* staying with datapoints as tuples until further notice.

* loading tsv as dict.

* BackgroundGenerator
* renaming disk cache.

Add peaking equalizer filter in functional.py and test it in test_functional_filter.py.