'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'

def bprop(self, error, alpha=1.0, beta=0.0):

    self.error.fill(0)
    if self.bprop_enabled:
        self.be.roipooling_bprop(error, self.rois, self.error, self.max_idx, self.rois_per_img, self.fm_channel, self.fm_height, self.fm_width, self.roi_H, self.roi_W, self.spatial_scale)
    return self.error
