'Conv Layer forward propagation.
Arguments:
fprop_in (Tensor): Inputs
scale_weights (float): Scale weights by scale/mean if nonzero
Returns:
fprop_out (Tensor): Output activations
or
(self.fprop_out, self.batch_sum) (tuple): Tuple with batch_sum
added as the second entry.'

def fprop(self, fprop_in, scale_weights=0):

    fprop_in = super(ConvLayer, self).fprop(fprop_in)
    self.lib.fprop_conv(self, fprop_in, self.weights, self.fprop_out, bsum=self.batch_sum)
    if scale_weights:
        self.scale_weights(scale_weights)
        self.fprop(fprop_in)
    if self.bsum:
        return (self.fprop_out, self.batch_sum)
    return self.fprop_out
