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when the result of input_lengths >>2 is xx.75, the torchaudio.transforms.RNNTLoss will raise "input length mismatch" Error.
Maybe this is a bug when calculating the output lengths, I'm not sure of it.
The text was updated successfully, but these errors were encountered:
I've gotten same problem. Have you fixed that yet?
I'm sorry to bother you. I would like to use the lengths of conformer, but I'm not sure what the lengths of input_lengths should be.
The following paragraph is a description of the parameters in the source code, does it mean that I input a one-dimensional tensor (that is, batch)? But then I saw in his example that the input was a three-dimensional tensor. How did you enter the parameters when you used the conformer?
In conformer/convolution.py, line 183, the code
when the result of input_lengths >>2 is xx.75, the torchaudio.transforms.RNNTLoss will raise "input length mismatch" Error.
Maybe this is a bug when calculating the output lengths, I'm not sure of it.
The text was updated successfully, but these errors were encountered: