def forward(self, inputs):
        """
        Args:
            inputs (Tensor): input image.

        Returns:
            Tuple[Tensor]: FPN output features..
        """
        #  backbone
        out_features = self.backbone(inputs)
        x2, x1, x0 = [out_features[f] for f in self.in_features]

        #  yolo branch 1
        x1_in = self.out1_cbl(x0)
        x1_in = self.upsample(x1_in)
        x1_in = torch.cat([x1_in, x1], 1)
        out_dark4 = self.out1(x1_in)

        #  yolo branch 2
        x2_in = self.out2_cbl(out_dark4)
        x2_in = self.upsample(x2_in)
        x2_in = torch.cat([x2_in, x2], 1)
        out_dark3 = self.out2(x2_in)

        outputs = (out_dark3, out_dark4, x0)
        return outputs

        Args:
            inputs (Tensor): input image.

        Returns:
            Tuple[Tensor]: FPN output features..
        
yolox/models/yolo_fpn.py