# tensorplay.nn.functional.ctc_loss

Source: https://www.tensorplay.cn/docs/generated/tensorplay.nn.functional.ctc_loss.html

```python
tensorplay.nn.functional.ctc_loss(log_probs: Tensor, targets: Tensor, input_lengths, target_lengths, blank: int = 0, reduction: str = 'mean', zero_infinity: bool = False) → Tensor
```

Compute the Connectionist Temporal Classification loss.

(alpha recurrence over the blank-extended target sequence); autograd flows
through log_probs via the composed primitives.

Parameters:

- log_probs – $(T, N, C)$ or $(T, C)$ log-softmax outputs.

- targets – $(N, S)$ or concatenated $(\sum S_n,)$.

- target_lengths (input_lengths /) – $(N,)$ or scalars.

- blank – index of the blank label. Default: 0.

- reduction – 'none' | 'mean' | 'sum'.

- zero_infinity – zero out infinite losses (targets too long for T).