def forward(self, x):
        """Forward feature from the regression head to get integral result of
        bounding box location.
        Args:
            x (Tensor): Features of the regression head, shape (N, 4*(n+1)),
                n is self.reg_max.
        Returns:
            x (Tensor): Integral result of box locations, i.e., distance
                offsets from the box center in four directions, shape (N, 4).
        """
        N, _, H, W = x.shape[:]
        prob = F.softmax(x.reshape([N, 4, -1, H, W]), axis=2)
        prob_topk, _ = prob.topk(self.reg_topk, axis=2)
        if self.add_mean:
            stat = paddle.concat(
                [prob_topk, prob_topk.mean(
                    axis=2, keepdim=True)], axis=2)
        else:
            stat = prob_topk
        y = F.relu(self.reg_conv1(stat.reshape([N, 4 * self.total_dim, H, W])))
        y = F.sigmoid(self.reg_conv2(y))
        return y
Forward feature from the regression head to get integral result of
        bounding box location.
        Args:
            x (Tensor): Features of the regression head, shape (N, 4*(n+1)),
                n is self.reg_max.
        Returns:
            x (Tensor): Integral result of box locations, i.e., distance
                offsets from the box center in four directions, shape (N, 4).
        
ppdet/modeling/heads/gfl_head.py