code: def forward(self, img, lr8x, hr2x):
      lr4x = F.interpolate(
          lr8x, scale_factor=2, mode="bilinear", align_corners=False
      )
      lr4x = self.conv_lr4x(lr4x)
      lr2x = F.interpolate(
          lr4x, scale_factor=2, mode="bilinear", align_corners=False
      )
  
      f2x = self.conv_f2x(paddle.concat((lr2x, hr2x), axis=1))
      f = F.interpolate(
          f2x, scale_factor=2, mode="bilinear", align_corners=False
      )
      f = self.conv_f(paddle.concat((f, img), axis=1))
      pred_matte = F.sigmoid(f)
  
      return pred_matte
  
imports: from collections import defaultdict
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import numpy
  import scipy
  import paddleseg
  from paddleseg.models import layers, losses
  from paddleseg import utils
  from paddleseg.cvlibs import manager, param_init
label_desc: Use image node_id 2 for calling the FusionBranch obj's underlying member method code with example usage: obj.forward(img, lr8x, hr2x) and returns: pred_matte