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NaN during training when using own dataset #4

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cjay42 opened this issue Nov 8, 2022 · 1 comment
Open

NaN during training when using own dataset #4

cjay42 opened this issue Nov 8, 2022 · 1 comment

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@cjay42
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cjay42 commented Nov 8, 2022

While fine-tuning works as expected, doing regular training with a dataset that isn't LJSpeech would eventually cause a NaN loss at some point.
The culprit appears to be the following line, which causes a division by zero if wav happens to contain perfect silence:

wav = flip * gain * wav / wav.abs().max()

I'm not sure what the best solution for this would be, as a quick fix I simply clipped the divisor so it can't reach zero:

wav = flip * gain * wav / max([wav.abs().max(), 0.001])
@joan126
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joan126 commented Jan 8, 2023

met same issue with you!!

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