2023-10-07 06:48:34 +02:00
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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2022-12-19 04:18:56 +01:00
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# All rights reserved.
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#
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# This source code is licensed under the license found in the
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# LICENSE file in the root directory of this source tree.
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"""Conveniance wrapper to perform STFT and iSTFT"""
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import torch as th
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def spectro(x, n_fft=512, hop_length=None, pad=0):
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*other, length = x.shape
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x = x.reshape(-1, length)
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2023-10-17 08:02:16 +02:00
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device_type = x.device.type
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is_other_gpu = not device_type in ["cuda", "cpu"]
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if is_other_gpu:
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2023-10-07 06:48:34 +02:00
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x = x.cpu()
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2022-12-19 04:18:56 +01:00
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z = th.stft(x,
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n_fft * (1 + pad),
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hop_length or n_fft // 4,
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window=th.hann_window(n_fft).to(x),
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win_length=n_fft,
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normalized=True,
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center=True,
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return_complex=True,
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pad_mode='reflect')
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_, freqs, frame = z.shape
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return z.view(*other, freqs, frame)
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def ispectro(z, hop_length=None, length=None, pad=0):
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*other, freqs, frames = z.shape
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n_fft = 2 * freqs - 2
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z = z.view(-1, freqs, frames)
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win_length = n_fft // (1 + pad)
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2023-10-17 08:02:16 +02:00
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device_type = z.device.type
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is_other_gpu = not device_type in ["cuda", "cpu"]
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if is_other_gpu:
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2023-10-07 06:48:34 +02:00
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z = z.cpu()
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2022-12-19 04:18:56 +01:00
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x = th.istft(z,
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n_fft,
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hop_length,
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window=th.hann_window(win_length).to(z.real),
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win_length=win_length,
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normalized=True,
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length=length,
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center=True)
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_, length = x.shape
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return x.view(*other, length)
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