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`test/test_sox_effects.py::Test_SoxEffectsChain::test_lowpass_speed` has some issue on our macOS CI, even though there was no issue at #777 .

While we figure out the fix, we disable this test for macOS.

Part of #764

 - Replace `whitenoise.wav` with on-the-fly data generation
 - Replace `torchaudio.load` with `common_utils.load_wav`
 - Replace `steam-train-whistle-daniel_simon.mp3` with `.wav`

In #779, we plan to remove `frames_per_chunk` parameter from `save` function, but it will take some time before we can land #779, so we go ahead and remove the parameter first to reduce the conflict caused by interface change.

* Change 'sox' to 'default'

* converted CommonVoice tartar mp3 to wav using rate 8000 Hz

* Remove Unused dtmf_30s_stereo.mp3

* add Waveforms for Testing Purposes section

* Update test/README.md

use wrapper function for scipy.io.wavfile.read
Co-authored-by: moto <855818+mthrok@users.noreply.github.com>

* remove un-used files from the doc

* Update test/README.md

Rename variable
Co-authored-by: moto <855818+mthrok@users.noreply.github.com>

* fix indent; remove mentions of unused files

* remove whitenoise* files from README.md
Co-authored-by: moto <855818+mthrok@users.noreply.github.com>

* upsamplenetwork

* update variable names

* update variable name

* add wavernn model

* update test

* update format

* update format

* update format

* fix conflicts and add transpose

* import update

* update transpose

* update format

* update docstring

* add n_channel in input

* add comment

* update docstring

* update docstring
Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

* Pin llvmlite

* Add comments

* upsamplenetwork

* update name

* update name and docstring

* update format

* rebase

* update docstring

* update docstring

* remove transpose and update docstring
Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

This is a part of PRs to add new "sox_io" backend. #726 and depends on #718, #728 and #731.

This PR adds `save` function to "sox_io" backend, which can save Tensor to a file with the following audio formats;
 - `wav`
 - `mp3`
 - `flac`
 - `ogg/vorbis`

* Use cmake for third party

* Apply patch to libmad

* Update gitignore

* Update docker test image

* update varible names and docstring

* update format

* update docsting and output value
Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

* Update functional.py

rollback torch.norm() in spectrogram() to v0.4.0.

* Update functional.py

comment out `spec_f = complex_norm(spec_f, power=power)`.

* fixed complex_norm() instead of spectrogram() for torch.norm() issue.

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

This is a part of PRs to add new "sox_io" backend. #726 and depends on #718 and #728 .

This PR adds `load` function to "sox_io" backend, which is  tested on the following audio formats;
 - `wav`
 - `mp3`
 - `flac`
 - `ogg/vorbis` *

By default, "sox_io" backend returns Tensor with `float32` dtype and the shape of `[channel, time]`. The samples are normalized to fit in the range of `[-1.0, 1.0]`.

Unlike existing "sox" backend, the new `load` function can handle WAV file natively, when the input format is WAV with integer type, (such as 32-bit signed integer, 16-bit signed integer and 8-bit unsigned integer) by providing `normalize=False`, this function can return integer Tensor, where the samples are expressed within the whole range of the corresponding dtype, that is, `int32` tensor for `32-bit PCM`, `int16` for `16-bit PCM` and `uint8` for `8-bit PCM`. This behavior follows [scipy.io.wavfile.read](https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.wavfile.read.html). `normalize` parameter has no effect for other formats and the load function always return normalized value with `float32` Tensor.

__* Note__ The current binary distribution of torchaudio does not contain `ogg/vorbis` and `opus` codecs. To handle these files, one needs to build torchaudio from the source with proper codecs in the system.

__Note 2__ Since this PR, `scipy` becomes required module for running test. 

* packaging: Add test channels to pytorch dependency resolution
Signed-off-by: Eli Uriegas <eliuriegas@fb.com>

* .circleci: Add test channel to smoke tests
Signed-off-by: Eli Uriegas <eliuriegas@fb.com>

* .circleci: Put pytorch-test into a higher priority

pytorch-nightly was getting prioritized over pytorch-nightly which
shouldn't be the case
Signed-off-by: Eli Uriegas <eliuriegas@fb.com>

Signed-off-by: Eli Uriegas <eliuriegas@fb.com>

In #728, linux unit test switches to libsox provided by apt.
For CPU jobs this is fine because all the job steps share the same Docker container,
but on CPU job, each job step runs a script in a new Docker container, so
libsox installed in a step is not available to the subsequent steps.

To fix this, this PR moves the installation of libsox and sox to Docker build.

This PR refactors cache generation mechanism by introducing dedicated command
and bust cache on daily basis.

At this moment, Windows unittest job for 3.6 and 3.7 are broken because of
broken scipy but the environment is cached this persists until the next week.

As we have nightly build, we do not need to keep cache for one week.

* add unittest in test_models

* update test method

* remove unittest main function
Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

This PR fixes the wrong member name of SignalInfo introduced in #718. 

 - `num_samples` == `num_frames` * `num_channels`.

This is a part of PRs to add new "sox_io" backend #726, and depends on #718.

This PR adds `info` function to "sox_io" backend, which allows users to fetch some metadata of an audio file. 
At this moment, the information retrieved are;

 - Number of samples in the audio file
 - Sampling rate
 - Number of channels

This is a part of PRs to add new "sox_io" backend. https://github.com/pytorch/audio/pull/726

This PR adds `SignalInfo` structure, which is data exchange interface between Python and C++ in coming TorchScript-based sox IO backend.
For the case, where C++ extension is not available (i.e. Windows), this PR also adds dummy class and module that will be substituted.
This logic is implemented in `torchaudio.extension` moduel.

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

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

* spacing and typing adjustment

* remove import list
Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

* Add MelResNet Block

* add default value

* update model and test

* rebase and small changes

* add pad variable

* update format

* update reference in docstrings

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

Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

* 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.