code: def __init__(self, in_channels, norm_layer=nn.BatchNorm2d, **kwargs):
      super(_DUHead, self).__init__()
      self.fuse = FeatureFused(norm_layer=norm_layer, **kwargs)
      self.block = nn.Sequential(
          nn.Conv2d(in_channels, 256, 3, padding=1, bias=False),
          norm_layer(256),
          nn.ReLU(True),
          nn.Conv2d(256, 256, 3, padding=1, bias=False),
          norm_layer(256),
          nn.ReLU(True),
      )
  
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 _DUHead object from inherited base classes: nn with example: obj = _DUHead(in_channels, norm_layer)