I have some questions about RNNT loss.

[girlsending0]

hello
I would like to ask you a question that may be somewhat trivial.
The shape of logits of RNN T loss is Batch, max_seq_len, max_target_len+1, class.
Why is max_target_len+1 here?
Shouldn't the number of classes be +1 to the size of the total vocab? Because blank is included.
I don't understand at all.
Is there anyone who can help?

https://pytorch.org/audio/main/generated/torchaudio.functional.rnnt_loss.html

[csukuangfj]

max_target_len+1 is not the vocab size. They are two different things.

You can find my implementation at
https://github.com/csukuangfj/optimized_transducer/blob/master/optimized_transducer/csrc/cpu.cc#L83

[girlsending0]

@csukuangfj Thank you.

I said that in a misleading way.

What I'm curious about is why target_length +1 needs to be entered as the RNNT loss's 3rd input. Looking at your code, I noticed that you wrote target length+1 because it includes a blank label.

Isn't the blank input already included in n_class? (When setting n_class, I think len(vocab)+1 should be set. Similar to CTC loss.)

I don't quite understand

[csukuangfj]

You need to differentiate between target length and number of classes.

The transcript of an utterance is converted to tokens. The target length is the number of tokens of the transcript. It is not number of classes. The possible value of a token is in the range [1, num_of_classes-1].

[girlsending0]

So the number of classes should be len(vocab)?
I understand.
I had misunderstood the mechanism of RNN-Transducer.
Since model will start from a blank label, it should be target_length+1.

[csukuangfj]

Great to hear it resolves your issue.

[girlsending0]

@csukuangfj
Thank you for your kindness.