# ctc_loss¶

dragon.losses.ctc_loss(
inputs,
**kwargs
)[source]

Compute the ctc loss with batched labels. [Graves & Gomez, 2006].

The shape of logit and label should be $$(T, N, C)$$, $$(N, C)$$ respectively, where $$T$$ is the sequence length, $$N$$ is the batch size, and $$C$$ is max label length. The range of labels should be $$[1, C)$$, as $$0$$ is reserved for blank.

Use padding_mask to fill it when length is not sufficient.

Parameters:
• inputs (Sequence[dragon.Tensor]) – The tensor logit and label.