code: def forward(self, *xs):
      output = self.resolve0(xs[0])
      if self.scale_factors[0] != 1:
          output = nn.functional.interpolate(
              output,
              scale_factor=self.scale_factors[0],
              mode="bilinear",
              align_corners=True,
          )
  
      for i, x in enumerate(xs[1:], 1):
          output += self.__getattr__("resolve{}".format(i))(x)
          if self.scale_factors[i] != 1:
              output = nn.functional.interpolate(
                  output,
                  scale_factor=self.scale_factors[i],
                  mode="bilinear",
                  align_corners=True,
              )
  
      return output
  
imports: import torch.nn
label_desc: Use image node_id 2 for calling the MultiResolutionFusion obj's underlying member method code with example usage: obj.forward() and returns: output