code: def forward(self, *inputs):
      feat = self.conv5(inputs[-1])
      if self.lateral:
          c2 = self.connect[0](inputs[1])
          c3 = self.connect[1](inputs[2])
          feat = self.fusion(torch.cat([feat, c2, c3], 1))
      outs = list(self.encmodule(feat))
      outs[0] = self.conv6(outs[0])
      return tuple(outs)
  
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 _EncHead obj's underlying member method code with example usage: obj.forward() and returns: tuple