class_docstr: A simple implementation for FCNHead based on PaddlePaddle
  
  Args:
      num_classes (int): The unique number of target classes.
      backbone_indices (tuple, optional): The values in the tuple indicate the indices of output of backbone.
          Default: (-1, ).
      channels (int, optional): The channels between conv layer and the last layer of FCNHead.
          If None, it will be the number of channels of input features. Default: None.
      pretrained (str, optional): The path of pretrained model. Default: None
code: def forward(self, feat_list):
      logit_list = []
      x = feat_list[self.backbone_indices[0]]
      x = self.conv_1(x)
      logit = self.cls(x)
      logit_list.append(logit)
      return logit_list
  
file_path: PaddleSeg/paddleseg/models/fcn.py
imports: import paddle.nn
  import paddle.nn.functional
  import paddle
  from paddleseg import utils
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
label_desc: Use image node_id 2 for calling the FCNHead obj's underlying member method code with example usage: obj.forward(feat_list) and returns: logit_list