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|
| | from pathlib import Path |
| | import typing as tp |
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|
| | import torch |
| | import torchaudio |
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|
| | def get_white_noise(chs: int = 1, num_frames: int = 1): |
| | wav = torch.randn(chs, num_frames) |
| | return wav |
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|
| | def get_batch_white_noise(bs: int = 1, chs: int = 1, num_frames: int = 1): |
| | wav = torch.randn(bs, chs, num_frames) |
| | return wav |
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|
| | def save_wav(path: str, wav: torch.Tensor, sample_rate: int): |
| | fp = Path(path) |
| | kwargs: tp.Dict[str, tp.Any] = {} |
| | if fp.suffix == '.wav': |
| | kwargs['encoding'] = 'PCM_S' |
| | kwargs['bits_per_sample'] = 16 |
| | elif fp.suffix == '.mp3': |
| | kwargs['compression'] = 320 |
| | torchaudio.save(str(fp), wav, sample_rate, **kwargs) |
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