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bump to torch 2.x and librosa 0.10.0 #1

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bump to torch 2.x and librosa 0.10.0 #1

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11 changes: 6 additions & 5 deletions mel_processing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,8 +64,8 @@ def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False)
y = y.squeeze(1)

spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
center=center, pad_mode='reflect', normalized=False, onesided=True)

center=center, pad_mode='reflect', normalized=False, onesided=True, return_complex=True)
spec = torch.view_as_real(spec)
spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
return spec

Expand All @@ -75,7 +75,7 @@ def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
dtype_device = str(spec.dtype) + '_' + str(spec.device)
fmax_dtype_device = str(fmax) + '_' + dtype_device
if fmax_dtype_device not in mel_basis:
mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax)
mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=spec.dtype, device=spec.device)
spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
spec = spectral_normalize_torch(spec)
Expand All @@ -93,7 +93,7 @@ def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, win_size,
fmax_dtype_device = str(fmax) + '_' + dtype_device
wnsize_dtype_device = str(win_size) + '_' + dtype_device
if fmax_dtype_device not in mel_basis:
mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax)
mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=y.dtype, device=y.device)
if wnsize_dtype_device not in hann_window:
hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
Expand All @@ -102,7 +102,8 @@ def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, win_size,
y = y.squeeze(1)

spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
center=center, pad_mode='reflect', normalized=False, onesided=True)
center=center, pad_mode='reflect', normalized=False, onesided=True, return_complex=True)
spec = torch.view_as_real(spec)

spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)

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2 changes: 1 addition & 1 deletion requirements.txt
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@@ -1,5 +1,5 @@
Cython
librosa==0.8.0
librosa==0.10.0
matplotlib
numpy
scipy
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