blackteay/GPT-SoVITS
1
0
Fork 0
mirror of https://github.com/RVC-Boss/GPT-SoVITS.git synced 2025-10-08 16:00:01 +08:00
Code Issues Packages Projects Releases Wiki Activity

Replace 'return_complex=False'

Browse Source
This commit is contained in:
KamioRinn 2024-07-25 15:29:57 +08:00
parent 29e2fdc62c
commit d93b43b6a8
2 changed files with 9 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
GPT_SoVITS/module/mel_processing.py
View File

@ -68,7 +68,7 @@ def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False)
mode="reflect", mode="reflect",
) )
y = y.squeeze(1) y = y.squeeze(1)
spec = torch.stft( spec = torch.view_as_real(torch.stft(
y, y,
n_fft, n_fft,
hop_length=hop_size, hop_length=hop_size,
@ -78,8 +78,8 @@ def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False)
pad_mode="reflect", pad_mode="reflect",
normalized=False, normalized=False,
onesided=True, onesided=True,
return_complex=False, return_complex=True,
) ))
spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6) spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
return spec return spec
@ -132,7 +132,7 @@ def mel_spectrogram_torch(
) )
y = y.squeeze(1) y = y.squeeze(1)
spec = torch.stft( spec = torch.view_as_real(torch.stft(
y, y,
n_fft, n_fft,
hop_length=hop_size, hop_length=hop_size,
@ -142,8 +142,8 @@ def mel_spectrogram_torch(
pad_mode="reflect", pad_mode="reflect",
normalized=False, normalized=False,
onesided=True, onesided=True,
return_complex=False, return_complex=True,
) ))
spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6) spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)

6
GPT_SoVITS/onnx_export.py
View File

@ -23,7 +23,7 @@ def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False)
mode="reflect", mode="reflect",
) )
y = y.squeeze(1) y = y.squeeze(1)
spec = torch.stft( spec = torch.view_as_real(torch.stft(
y, y,
n_fft, n_fft,
hop_length=hop_size, hop_length=hop_size,
@ -33,8 +33,8 @@ def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False)
pad_mode="reflect", pad_mode="reflect",
normalized=False, normalized=False,
onesided=True, onesided=True,
return_complex=False, return_complex=True,
) ))
spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6) spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
return spec return spec