4cc818ed198714a2f77927657df9ebfe9a2af49e,chainercv/functions/ps_roi_average_align_2d.py,PSROIAverageAlign2D,backward_cpu,#PSROIAverageAlign2D#,357

Before Change

            gh = np.floor(float(ph) * group_size / pooled_height)
            gw = np.floor(float(pw) * group_size / pooled_width)
            gh = int(min(max(gh, 0), group_size - 1))
            gw = int(min(max(gw, 0), group_size - 1))
            c = (ctop * group_size + gh) * group_size + gw

            top_diff_this_bin = top_diff[n, ctop, ph, pw]

            if self.sampling_ratio[0] is None:
                roi_bin_grid_h = int(np.ceil(roi_height / pooled_height))
            else:
                roi_bin_grid_h = self.sampling_ratio[0]
            if self.sampling_ratio[1] is None:
                roi_bin_grid_w = int(np.ceil(roi_width / pooled_width))
            else:
                roi_bin_grid_w = self.sampling_ratio[1]

            count = roi_bin_grid_h * roi_bin_grid_w

            for iy in six.moves.range(roi_bin_grid_h):
                y = roi_start_h + ph * bin_size_h + \
                    (iy + .5) * bin_size_h / roi_bin_grid_h
                y, y_low, y_high = _get_bounds(y, height)
                if y is None or y_low is None or y_high is None:
                    continue
                for ix in six.moves.range(roi_bin_grid_w):
                    x = roi_start_w + pw * bin_size_w + \
                        (ix + .5) * bin_size_w / roi_bin_grid_w

                    x, x_low, x_high = _get_bounds(x, width)
                    if x is None or x_low is None or x_high is None:
                        continue
                    // bilinear_interpolation_gradient {{
                    w1, w2, w3, w4 = _get_bilinear_interp_params(
                        y, x, y_low, x_low, y_high, x_high)

                    g1 = top_diff_this_bin * w1 / count
                    g2 = top_diff_this_bin * w2 / count
                    g3 = top_diff_this_bin * w3 / count
                    g4 = top_diff_this_bin * w4 / count

                    if (x_low >= 0 and x_high >= 0 and
                            y_low >= 0 and y_high >= 0):
                        bottom_diff[roi_batch_ind, c, y_low, x_low] += g1
                        bottom_diff[roi_batch_ind, c, y_low, x_high] += g2
                        bottom_diff[roi_batch_ind, c, y_high, x_low] += g3
                        bottom_diff[roi_batch_ind, c, y_high, x_high] += g4
                    // }}

        return bottom_diff, None, None

After Change

            gh = int(np.floor(ph * group_size / pooled_height))
            gw = int(np.floor(pw * group_size / pooled_width))
            gh = min(max(gh, 0), group_size - 1)
            gw = min(max(gw, 0), group_size - 1)
            c = (ctop * group_size + gh) * group_size + gw

            top_diff_this_bin = top_diff[n, ctop, ph, pw]

            if self.sampling_ratio[0] is None:
                roi_bin_grid_h = int(np.ceil(roi_height / pooled_height))
            else:
                roi_bin_grid_h = self.sampling_ratio[0]
            if self.sampling_ratio[1] is None:
                roi_bin_grid_w = int(np.ceil(roi_width / pooled_width))
            else:
                roi_bin_grid_w = self.sampling_ratio[1]

            count = roi_bin_grid_h * roi_bin_grid_w

            for iy in six.moves.range(roi_bin_grid_h):
                y = roi_start_h + ph * bin_size_h + \
                    (iy + .5) * bin_size_h / roi_bin_grid_h
                y, y_low, y_high = _get_bounds(y, height)
                if y is None or y_low is None or y_high is None:
                    continue
                for ix in six.moves.range(roi_bin_grid_w):
                    x = roi_start_w + pw * bin_size_w + \
                        (ix + .5) * bin_size_w / roi_bin_grid_w

                    x, x_low, x_high = _get_bounds(x, width)
                    if x is None or x_low is None or x_high is None:
                        continue
                    // bilinear_interpolation_gradient {{
                    w1, w2, w3, w4 = _get_bilinear_interp_params(
                        y, x, y_low, x_low, y_high, x_high)

                    g1 = top_diff_this_bin * w1 / count
                    g2 = top_diff_this_bin * w2 / count
                    g3 = top_diff_this_bin * w3 / count
                    g4 = top_diff_this_bin * w4 / count

                    if (x_low >= 0 and x_high >= 0 and
                            y_low >= 0 and y_high >= 0):
                        bottom_diff[roi_batch_ind, c, y_low, x_low] += g1
                        bottom_diff[roi_batch_ind, c, y_low, x_high] += g2
                        bottom_diff[roi_batch_ind, c, y_high, x_low] += g3
                        bottom_diff[roi_batch_ind, c, y_high, x_high] += g4
                    // }}

        return bottom_diff, None, None

Instances