fix bug: matrix multiplication errors caused by discontinuous memory

[bigcash]

When reading audio files in large quantities with multiple processes, it sometimes leads to discontinuous memory space for the audio. Then, when calling the fbank method, the continuous method is usually not called to make its stored content space continuous. Furthermore, an exception occurred in the torch.mm within the fbank method, ultimately leading to an unexpected segmentation fault. I ultimately identified this bug and added contigues() to the variables spectrum and mel_deergies. T to avoid this error.

[pytorch-bot[bot]]

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[pearu]

Furthermore, an exception occurred in the torch.mm within the fbank method, ultimately leading to an unexpected segmentation fault.

What was the exception and which torch version are you using?

torch.mm is able to handle non-contiguous inputs, for instance:

>>> import torch
>>> a = torch.randn(4, 4)[::2, ::2]
>>> b = torch.randn(4, 4)[::2, ::2]
>>> a.is_contiguous()
False
>>> torch.mm(a, b)
tensor([[ 0.2873, -0.2190],
        [-0.6884, -0.3184]])

[bigcash]

Furthermore, an exception occurred in the torch.mm within the fbank method, ultimately leading to an unexpected segmentation fault.

What was the exception and which torch version are you using?

torch.mm is able to handle non-contiguous inputs, for instance:

>>> import torch
>>> a = torch.randn(4, 4)[::2, ::2]
>>> b = torch.randn(4, 4)[::2, ::2]
>>> a.is_contiguous()
False
>>> torch.mm(a, b)
tensor([[ 0.2873, -0.2190],
        [-0.6884, -0.3184]])

thanks for reply!

and i make this exception with torch_npu, (not for gpu version) which whill raise this error.

Unfortunately, in this case, it's difficult to modify torch_npu, and easy to modify kaldi.py