mygrad.operation_base.Operation.backward_var#
- abstract Operation.backward_var(grad: ndarray, index: int, **kwargs) ndarray[source]#
Given
grad = dℒ/df, computes∂ℒ/∂x_{i}, wherex_{i}is one ofx1, ...., xn.ℒis assumed to be the terminal node from whichℒ.backward()was called.- Parameters:
- gradnumpy.ndarray
The back-propagated total derivative with respect to the present operation: dℒ/df. This will have the same shape as f, the result of the forward pass.
- indexint
The index-location of
varinself.variables
- Returns:
- numpy.ndarray
∂ℒ/∂x_{i}
- Raises:
- SkipGradient