Procs
proc sigmoid_cross_entropy[T](input, target: Tensor[T]): T
-
Sigmoid function + Cross-Entropy loss fused in one layer.
Input:
- A Tensor
- The target values
Returns:
- Apply a sigmoid activation and returns the cross-entropy loss.
Shape:
- Both the cache and target shape should be batch_size, features i.e. number of samples as first dimension
proc sigmoid_cross_entropy_backward[T](gradient: Tensor[T] or T; cached_tensor: Tensor[T]; target: Tensor[T]): Tensor[T] {.noinit.}
-
Derivatives of sigmoid_cross_entropy Input:
- The input gradient as a scalar or a Tensor
- A cache tensor that contains data from before the forward pass
- The target values
Shape:
- Both the cache and target shape should be batch_size, features i.e. number of samples as first dimension