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Description
When the input tensor shape is [1, 800] or [1, 320] and When I use the following code
mel_tensor = wav2mel(wav_tensor, 16000) # 16000 is the sample rate
I met with the following error:
Traceback of TorchScript, serialized code (most recent call last):
File "code/torch/data/wav2mel.py", line 20, in forward
sample_rate: int) -> Tensor:
wav_tensor0 = (self.sox_effects).forward(wav_tensor, sample_rate, )
mel_tensor = (self.log_melspectrogram).forward(wav_tensor0, )
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
return mel_tensor
class SoxEffects(Module):
File "code/torch/data/wav2mel.py", line 43, in forward
def forward(self: torch.data.wav2mel.LogMelspectrogram,
wav_tensor: Tensor) -> Tensor:
_3 = (self.melspectrogram).forward(wav_tensor, )
~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
mel_tensor = torch.numpy_T(torch.squeeze(_3, 0))
_4 = torch.clamp(mel_tensor, 1.0000000000000001e-09, None)
File "code/torch/torchaudio/transforms.py", line 20, in forward
def forward(self: torch.torchaudio.transforms.MelSpectrogram,
waveform: Tensor) -> Tensor:
specgram = (self.spectrogram).forward(waveform, )
~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
mel_specgram = (self.mel_scale).forward(specgram, )
return mel_specgram
File "code/torch/torchaudio/transforms.py", line 41, in forward
waveform: Tensor) -> Tensor:
_0 = torch.torchaudio.functional.functional.spectrogram
_1 = _0(waveform, 0, self.window, 400, 160, 400, 2., False, self.center, self.pad_mode, self.onesided, )
~~ <--- HERE
return _1
class MelScale(Module):
File "code/torch/torchaudio/functional/functional.py", line 18, in spectrogram
waveform0 = waveform
shape = torch.size(waveform0)
waveform2 = torch.reshape(waveform0, [-1, shape[-1]])
~~~~~~~~~~~~~ <--- HERE
spec_f = torch.torch.functional.stft(waveform2, n_fft, hop_length, win_length, window, center, pad_mode, False, onesided, True, )
_0 = torch.slice(shape, 0, -1, 1)Traceback of TorchScript, original code (most recent call last):
File "/home/yist/.pyenv/versions/3.8.5/lib/python3.8/site-packages/torchaudio/transforms.py", line 96, in forward
Fourier bins, and time is the number of window hops (n_frame).
"""
return F.spectrogram(
~~~~~~~~~~~~~ <--- HERE
waveform,
self.pad,
File "/home/yist/.pyenv/versions/3.8.5/lib/python3.8/site-packages/torchaudio/functional/functional.py", line 88, in spectrogram
# pack batch
shape = waveform.size()
waveform = waveform.reshape(-1, shape[-1])
~~~~~~~~~~~~~~~~ <--- HERE# default values are consistent with librosa.core.spectrum._spectrogramRuntimeError: cannot reshape tensor of 0 elements into shape [-1, 0] because the unspecified dimension size -1 can be any value and is ambiguous
How can I solve this problem?