code: def __init__(
      self, in_channels, channels, norm_layer=nn.BatchNorm2d, **kwargs
  ):
      super(_FCNHead, self).__init__()
      inter_channels = in_channels // 4
      self.block = nn.Sequential(
          nn.Conv2d(
              in_channels, inter_channels, 3, padding=1, bias=False
          ),
          norm_layer(inter_channels),
          nn.ReLU(inplace=True),
          nn.Dropout(0.1),
          nn.Conv2d(inter_channels, channels, 1),
      )
  
file_path: pywick/pywick/models/segmentation/da_basenets/fcn.py
imports: import torch.nn
  import torch.nn.functional
  from .vgg import vgg16
label_desc: Use image node_id 1 to create a new _FCNHead object from inherited base classes: nn with example: obj = _FCNHead(in_channels, channels, norm_layer)