def backward(self) -> ndarray:
self.input_grad = self._input_grad()
assert_same_shape(self.prediction, self.input_grad)
return self.input_grad
def backward(self, output_grad: ndarray) -> ndarray:
assert_same_shape(self.output, output_grad)
self.input_grad = self._input_grad(output_grad)
assert_same_shape(self.input_, self.input_grad)
return self.input_grad
def forward(self, prediction: ndarray, target: ndarray) -> float:
# batch size x num_classes
assert_same_shape(prediction, target)
self.prediction = prediction
self.target = target
self.output = self._output()
return self.output
def backward(self, output_grad: ndarray) -> ndarray:
assert_same_shape(self.output, output_grad)
for operation in self.operations[::-1]:
output_grad = operation.backward(output_grad)
input_grad = output_grad
assert_same_shape(self.input_, input_grad)
self._param_grads()
return input_grad
