(self, error, alpha=1.0, beta=0.0)
return self.deltas
Apply the backward pass transformation to the input data.

        Arguments:
            error (Tensor): deltas back propagated from the adjacent higher layer
            alpha (float, optional): scale to apply to input for activation
                                     gradient bprop.  Defaults to 1.0
            beta (float, optional): scale to apply to output activation
                                    gradient bprop.  Defaults to 0.0

        Returns:
            Tensor: deltas to propagate to the adjacent lower layer
Apply the backward pass transformation to the input data.
Apply the backward pass transformation to the input data .
def bprop(self, error, alpha=1.0, beta=0.0):
        """
        Apply the backward pass transformation to the input data.

        Arguments:
            error (Tensor): deltas back propagated from the adjacent higher layer
            alpha (float, optional): scale to apply to input for activation
                                     gradient bprop.  Defaults to 1.0
            beta (float, optional): scale to apply to output activation
                                    gradient bprop.  Defaults to 0.0

        Returns:
            Tensor: deltas to propagate to the adjacent lower layer
        """
        self.be.bprop_mergesum(self.ngLayer, alpha, beta,
                               self.layers, error, self.deltas)
        return self.deltas
def bprop ( self , error , alpha = 1.0 , beta = 0.0 ) : self . be . bprop_mergesum ( self . ngLayer , alpha , beta , self . layers , error , self . deltas ) return self . deltas