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Summary:
Adding py3.10 to audio

Pull Request resolved: https://github.com/pytorch/audio/pull/2224

Reviewed By: malfet, atalman, mthrok

Differential Revision: D34442377

Pulled By: seemethere

fbshipit-source-id: 2656de73427063958d609a74c01b526a476cb06a

Summary:
Currently, macOS CI jobs install `pkg-config` and `wget` with `brew`.
This is problematic as brew takes a long time with auto-update, and disabling the auto-update is not an ideal solution.
Conda also distributes these packages, so switching to conda.

Example issues with brew installation.
https://app.circleci.com/pipelines/github/pytorch/audio/7825/workflows/53965bcf-6ddf-4e42-ad52-83fd1bbab717

This commit removes the use of `brew` by
1. Replacing the use of `wget` with `curl` (pre-installed in most distro)
2. Install `pkg-condig` from conda.
    Note: All the macOS jobs, including binary build jobs, uses conda. Using `pkg-config` from Conda makes it easy to discover the packages installed from conda. (like `ffmpeg` in https://github.com/pytorch/audio/issues/2122)
3. Add `pkg-config` to conda build-time dependency
4. Make sure that the availability of `pkg-config` is explicitly checked when `sox` is being configured. (otherwise, it will fail at somewhere in the middle of build process with somewhat unintuitve error message)

Pull Request resolved: https://github.com/pytorch/audio/pull/1873

Reviewed By: carolineechen, nateanl

Differential Revision: D33404975

Pulled By: mthrok

fbshipit-source-id: ae512d3a3a422ebfe3b46c492bed44deecc36e72

Summary:
Preparation to land Python front-end of ffmpeg-related features.

- Set BUILD_FFMPEG=1 in Linux/macOS unit test jobs
- Install ffmpeg and pkg-config from conda-forge
- Add note about Windows build process
- Temporarily avoid `av_err2str`

Pull Request resolved: https://github.com/pytorch/audio/pull/2114

Reviewed By: hwangjeff

Differential Revision: D33371346

Pulled By: mthrok

fbshipit-source-id: b0e16a35959a49a2166109068f3e0cbbb836e888

Summary:
The unit test failures seems to be caused by [conda 4.11](https://github.com/conda/conda/issues/11096)
Remove conda update line fixes the issue.

Pull Request resolved: https://github.com/pytorch/audio/pull/2069

Reviewed By: carolineechen

Differential Revision: D33023851

Pulled By: nateanl

fbshipit-source-id: 73246189d4ccc541e366a5367f532a5b456af8f8

* Switch to cmake for build
* Hide symbols

* Use cmake for third party

* Apply patch to libmad

* Update gitignore

* Update docker test image

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 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

* Clean up extension build mechanism and extension location

* Add back the switch to depend on external sox

* Remove print

* Fix

* 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>

* Add test image with Kaldi executable and third_parties

* Use Ubuntu as bese image since pytorch/many-linux is huge

* wip

* Add test

* add caching

* fixup! add caching

* fixup! fixup! add caching