code: def __init__(self, mode, in_channels, feature_channels, out_channels):
      super(FeaturesConnector, self).__init__()
      self.mode = mode if feature_channels else ""
  
      if self.mode == "catc":
          self.reduce_conv = nn.Conv2d(
              in_channels + feature_channels,
              out_channels,
              kernel_size=1,
          )
      elif self.mode == "sum":
          self.reduce_conv = nn.Conv2d(
              feature_channels, out_channels, kernel_size=1
          )
  
      self.output_channels = (
          out_channels
          if self.mode != "cat"
          else in_channels + feature_channels
      )
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new FeaturesConnector object from inherited base classes: nn with example: obj = FeaturesConnector(mode, in_channels, feature_channels, out_channels)