def forward(self, x_p: Tensor, x_i: Tensor, x_d: Tensor) -> Tensor:
        """Forward function.
        Args:
            x_p (Tensor): The featrue map from P branch.
            x_i (Tensor): The featrue map from I branch.
            x_d (Tensor): The featrue map from D branch.

        Returns:
            Tensor: The feature map with light boundary-attention-guided
                fusion.
        """
        sigma = F.sigmoid(x_d)

        f_p = self.f_p((1 - sigma) * x_i + x_p)
        f_i = self.f_i(x_i + sigma * x_p)

        return f_p + f_i
Forward function.
        Args:
            x_p (Tensor): The featrue map from P branch.
            x_i (Tensor): The featrue map from I branch.
            x_d (Tensor): The featrue map from D branch.

        Returns:
            Tensor: The feature map with light boundary-attention-guided
                fusion.
        
paddleseg/models/backbones/pidnet.py