Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

About the "input length mismatch" bug in torchaudio's RNNT loss #37

Open
Zain-Jiang opened this issue Nov 10, 2021 · 2 comments
Open

About the "input length mismatch" bug in torchaudio's RNNT loss #37

Zain-Jiang opened this issue Nov 10, 2021 · 2 comments

Comments

@Zain-Jiang
Copy link

In conformer/convolution.py, line 183, the code

output_lengths = input_lengths >> 2
output_lengths -= 1

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.

@longlnOff
Copy link

I've gotten same problem. Have you fixed that yet?

@zzzendurance
Copy link

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?

image

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants