class_docstr: The PFPNHead implementation.
  
  Args:
      inplane (int): Input channels of PPM module.
      num_class (int): The unique number of target classes.
      fpn_inplanes (list): The feature channels from backbone.
      fpn_dim (int, optional): The input channels of FPN module. Default: 512.
      enable_auxiliary_loss (bool, optional): A bool value indicates whether adding auxiliary loss. Default: False.
class_docstr_tok: ["The","PFPNHead","implementation",".","Args",":","inplane","(","int",")",":","Input","channels","of","PPM","module",".","num_class","(","int",")",":","The","unique","number","of","target","classes",".","fpn_inplanes","(","list",")",":","The","feature","channels","from","backbone",".","fpn_dim","(","int",",","optional",")",":","The","input","channels","of","FPN","module",".","Default",":","512.","enable_auxiliary_loss","(","bool",",","optional",")",":","A","bool","value","indicates","whether","adding","auxiliary","loss",".","Default",":","False","."]
code: def cls_seg(self, feat):
      if self.dropout is not None:
          feat = self.dropout(feat)
      output = self.conv_seg(feat)
      return output
  
file_path: PaddleSeg/paddleseg/models/pfpnnet.py
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the PFPNHead obj's underlying member method code with example usage: obj.cls_seg(feat) and returns: output