(self, y, t)
return self.scale * (y - t)
Returns the derivative of the binary cross entropy cost.

        Args:
            y (Tensor or OpTree): Output of previous layer or model
            t (Tensor or OpTree): True targets corresponding to y

        Returns:
            OpTree: Returns the (mean) shortcut derivative of the binary entropy
                    cost function ``(y - t) / y.shape[1]``
Returns the derivative of the binary cross entropy cost.
Returns the derivative of the binary cross entropy cost .
def bprop(self, y, t):
        """
        Returns the derivative of the binary cross entropy cost.

        Args:
            y (Tensor or OpTree): Output of previous layer or model
            t (Tensor or OpTree): True targets corresponding to y

        Returns:
            OpTree: Returns the (mean) shortcut derivative of the binary entropy
                    cost function ``(y - t) / y.shape[1]``
        """
        return self.scale * (y - t)
def bprop ( self , y , t ) : return self . scale * ( y - t )