Hey, Patrick thanks for getting back. When I use a tensor then i get the following error. I am bit confused what the input should look like given an mel spectrogram of shape: torch.Size([288, 432, 4])

AssertionError                            Traceback (most recent call last)
 in ()
7
8 inv_mel = torchaudio.transforms.InverseMelScale(n_stft=1023)
----> 9 inv_mel(sample)
1 frames
/usr/local/lib/python3.7/dist-packages/torchaudio/transforms.py in forward(self, melspec)
394         freq, _ = self.fb.size()  # (freq, n_mels)
395         melspec = melspec.transpose(-1, -2)
 → 396         assert self.n_mels == n_mels
397
398         specgram = torch.rand(melspec.size()[0], time, freq, requires_grad=True,
AssertionError: