class_docstr: Module for fused features
code: def forward(self, c2, c3, c4):
      size = c4.size()[2:]
      c2 = self.conv2(
          F.interpolate(c2, size, mode="bilinear", align_corners=True)
      )
      c3 = self.conv3(
          F.interpolate(c3, size, mode="bilinear", align_corners=True)
      )
      fused_feature = torch.cat([c4, c3, c2], dim=1)
      return fused_feature
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pywick.models.segmentation.da_basenets.segbase import SegBaseModel
  from pywick.models.segmentation.da_basenets.fcn import _FCNHead
label_desc: Use image node_id 2 for calling the FeatureFused obj's underlying member method code with example usage: obj.forward(c2, c3, c4) and returns: fused_feature