code: def __init__(
      self,
      in_channels,
      nclass,
      se_loss=True,
      lateral=True,
      norm_layer=nn.BatchNorm2d,
      norm_kwargs=None,
      **kwargs,
  ):
      super(_EncHead, self).__init__()
      self.lateral = lateral
      self.conv5 = nn.Sequential(
          nn.Conv2d(in_channels, 512, 3, padding=1, bias=False),
          norm_layer(
              512, **({} if norm_kwargs is None else norm_kwargs)
          ),
          nn.ReLU(True),
      )
      if lateral:
          self.connect = nn.ModuleList(
              [
                  nn.Sequential(
                      nn.Conv2d(512, 512, 1, bias=False),
                      norm_layer(
                          512,
                          **(
                              {} if norm_kwargs is None else norm_kwargs
                          ),
                      ),
                      nn.ReLU(True),
                  ),
                  nn.Sequential(
                      nn.Conv2d(1024, 512, 1, bias=False),
                      norm_layer(
                          512,
                          **(
                              {} if norm_kwargs is None else norm_kwargs
                          ),
                      ),
                      nn.ReLU(True),
                  ),
              ]
          )
          self.fusion = nn.Sequential(
              nn.Conv2d(3 * 512, 512, 3, padding=1, bias=False),
              norm_layer(
                  512, **({} if norm_kwargs is None else norm_kwargs)
              ),
              nn.ReLU(True),
          )
      self.encmodule = EncModule(
          512,
          nclass,
          ncodes=32,
          se_loss=se_loss,
          norm_layer=norm_layer,
          norm_kwargs=norm_kwargs,
          **kwargs,
      )
      self.conv6 = nn.Sequential(
          nn.Dropout(0.1, False), nn.Conv2d(512, nclass, 1)
      )
  
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 1 to create a new _EncHead object from inherited base classes: nn with example: obj = _EncHead(in_channels, nclass, se_loss, lateral, norm_layer, norm_kwargs)