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Running
on
Zero
| import os | |
| from pathlib import Path | |
| import torch | |
| import torch.nn as nn | |
| import torch.nn.functional as F | |
| import torchaudio | |
| def load_audio(audiopath, sampling_rate): | |
| """_summary_ | |
| Args: | |
| audiopath (_type_): audio_path | |
| sampling_rate (_type_): sampling_rate | |
| Returns: | |
| _type_: _description_ | |
| """ | |
| audio, lsr = torchaudio.load(audiopath) | |
| # stereo to mono if needed | |
| if audio.size(0) != 1: | |
| audio = torch.mean(audio, dim=0, keepdim=True) | |
| # resample | |
| audio_resampled = torchaudio.functional.resample(audio, lsr, sampling_rate) | |
| if torch.any(audio > 10) or not torch.any(audio < 0): | |
| print(f"Error with {audiopath}. Max={audio.max()} min={audio.min()}") | |
| if torch.any(audio_resampled > 10) or not torch.any(audio_resampled < 0): | |
| print( | |
| f"Error with {audiopath}. Max={audio_resampled.max()} min={audio_resampled.min()}" | |
| ) | |
| # clip audio invalid values | |
| audio.clip_(-1, 1) | |
| audio_resampled.clip_(-1, 1) | |
| return audio, lsr, audio_resampled | |