'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'

@Layer.accumulates
def bprop(self, error, alpha=1.0, beta=0.0):

    if self.deltas:
        self.be.bprop_conv(self.nglayer, self.W, error, self.deltas, alpha=alpha, beta=beta, layer_op=self)
    self.be.update_conv(self.nglayer, self.inputs, error, self.dW, layer_op=self)
    return self.deltas
