code: def __init__(self, in_chan, out_chan, *args, **kwargs):
      super(FeatureFusionModule, self).__init__()
      self.convblk = ConvBNReLU(
          in_chan, out_chan, ks=1, stride=1, padding=0
      )
      self.conv1 = nn.Conv2d(
          out_chan,
          out_chan // 4,
          kernel_size=1,
          stride=1,
          padding=0,
          bias=False,
      )
      self.conv2 = nn.Conv2d(
          out_chan // 4,
          out_chan,
          kernel_size=1,
          stride=1,
          padding=0,
          bias=False,
      )
      self.relu = nn.ReLU(inplace=True)
      self.sigmoid = nn.Sigmoid()
      self.init_weight()
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from ParsingResnet import Resnet18
label_desc: Use image node_id 1 to create a new FeatureFusionModule object from inherited base classes: nn with example: obj = FeatureFusionModule(in_chan, out_chan)