A Problem About Code

[LzqInsta]

Thanks for your great work!
I met a problem in the code, which is that crestereo always uses negative flow predictions from lower resolution RUM, e.g. the "flow_dw8 = -scale * F.nn.interpolate" in the code below.
This is strange and not consistent with the paper. Could you explain the reason about it ?

# Recurrent Update Module
            # RUM: 1/16
            for itr in range(iters // 2):
                if itr % 2 == 0:
                    small_patch = False
                else:
                    small_patch = True

                flow_dw16 = flow_dw16.detach()
                out_corrs = corr_fn_att_dw16(
                    flow_dw16, offset_dw16, small_patch=small_patch
                )

                with amp.autocast(enabled=self.mixed_precision):
                    net_dw16, up_mask, delta_flow = self.update_block(
                        net_dw16, inp_dw16, out_corrs, flow_dw16
                    )

                flow_dw16 = flow_dw16 + delta_flow
                flow = self.convex_upsample(flow_dw16, up_mask, rate=4)
                flow_up = -4 * F.nn.interpolate(
                    flow,
                    size=(4 * flow.shape[2], 4 * flow.shape[3]),
                    mode="bilinear",
                    align_corners=True,
                )
                predictions.append(flow_up)

            scale = fmap1_dw8.shape[2] / flow.shape[2]
            flow_dw8 = -scale * F.nn.interpolate(
                flow,
                size=(fmap1_dw8.shape[2], fmap1_dw8.shape[3]),
                mode="bilinear",
                align_corners=True,
            )