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Summary:
This PR adds ``apply_beamforming`` method to ``torchaudio.functional``.
The method employs the beamforming weight to the multi-channel noisy spectrum to obtain the single-channel enhanced spectrum.
The input arguments are the complex-valued beamforming weight Tensor and the multi-channel noisy spectrum.

Pull Request resolved: https://github.com/pytorch/audio/pull/2232

Reviewed By: mthrok

Differential Revision: D34474561

Pulled By: nateanl

fbshipit-source-id: 2910251a8f111e65375dfb50495b6a415113f06d

Summary:
This PR adds ``rtf_power`` method to ``torchaudio.functional``.
The method computes the relative transfer function (RTF) or the steering vector by [the power iteration method](https://onlinelibrary.wiley.com/doi/abs/10.1002/zamm.19290090206).
[This paper](https://arxiv.org/pdf/2011.15003.pdf) describes the power iteration method in English.
The input arguments are the complex-valued power spectral density (PSD) matrix of the target speech, PSD matrix of noise, int or one-hot Tensor to indicate the reference channel, number of iterations, respectively.

Pull Request resolved: https://github.com/pytorch/audio/pull/2231

Reviewed By: mthrok

Differential Revision: D34474503

Pulled By: nateanl

fbshipit-source-id: 47011427ec4373f808755f0e8eff1efca57655eb

Summary:
This PR adds ``mvdr_weights_rtf`` method to ``torchaudio.functional``.
It computes the MVDR weight matrix based on the solution that applies relative transfer function (RTF). See [the paper](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.725.673&rep=rep1&type=pdf) for the reference.
The input arguments are the complex-valued RTF Tensor of the target speech, power spectral density (PSD) matrix of noise, int or one-hot Tensor to indicate the reference channel, respectively.

Pull Request resolved: https://github.com/pytorch/audio/pull/2229

Reviewed By: mthrok

Differential Revision: D34474119

Pulled By: nateanl

fbshipit-source-id: 2d6f62cd0858f29ed6e4e03c23dcc11c816204e2

Summary:
This PR adds ``mvdr_weights_souden`` method to ``torchaudio.functional``.
It computes the MVDR weight matrix based on the solution proposed by [``Souden et, al.``](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.725.673&rep=rep1&type=pdf).
The input arguments are the complex-valued power spectral density (PSD) matrix of the target speech, PSD matrix of noise, int or one-hot Tensor to indicate the reference channel, respectively.

Pull Request resolved: https://github.com/pytorch/audio/pull/2228

Reviewed By: mthrok

Differential Revision: D34474018

Pulled By: nateanl

fbshipit-source-id: 725df812f8f6e6cc81cc37e8c3cb0da2ab3b74fb

Summary:
This PR adds ``psd`` method to ``torchaudio.functional``.
It computes the power spectral density (PSD) matrix of the complex-valued spectrum.
The method also supports normalization of Time-Frequency mask.

Pull Request resolved: https://github.com/pytorch/audio/pull/2227

Reviewed By: mthrok

Differential Revision: D34473908

Pulled By: nateanl

fbshipit-source-id: c1cfc584085d77881b35d41d76d39b26fca1dda9

Summary:
In autograd tests, to guarantee the precision, the dtype of Tensors are converted to `torch.float64` if they are real. However, the complex dtype is not considered. This PR adds `self.complex_dtype` support to the inputs.

Pull Request resolved: https://github.com/pytorch/audio/pull/2244

Reviewed By: mthrok

Differential Revision: D34272998

Pulled By: nateanl

fbshipit-source-id: e8698a74d7b8d99ee0fcb5f5cb5f2ffc8c80b9b5

Summary:
Pull Request resolved: https://github.com/pytorch/audio/pull/2096

run: `arc lint --apply-patches --paths-cmd 'hg files -I "./**/*.py"'`

Reviewed By: mthrok

Differential Revision: D33297351

fbshipit-source-id: 7bf5956edf0717c5ca90219f72414ff4eeaf5aa8

* Add basic filtfilt implementation

* Add filtfilt to functional package; add tests
Co-authored-by: V G <vladislav.goncharenko@phystech.edu>

Use shorter input sequences to avoid time out error on CI