code: def __init__(
      self,
      num_classes,
      backbone_indices=(-1,),
      backbone_channels=(270,),
      channels=None,
  ):
      super(FCNHead, self).__init__()
  
      self.num_classes = num_classes
      self.backbone_indices = backbone_indices
      if channels is None:
          channels = backbone_channels[0]
  
      self.conv_1 = layers.ConvBNReLU(
          in_channels=backbone_channels[0],
          out_channels=channels,
          kernel_size=1,
          stride=1,
          bias_attr=True,
      )
      self.cls = nn.Conv2D(
          in_channels=channels,
          out_channels=self.num_classes,
          kernel_size=1,
          stride=1,
          bias_attr=True,
      )
      self.init_weight()
  
file_path: PaddleSeg/contrib/RSSegBenchmark/c2fnet/models/c2fnet.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import paddleseg.utils.logger
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 1 to create a new FCNHead object from inherited base classes: nn with example: obj = FCNHead(num_classes, backbone_indices, backbone_channels, channels)