class_docstr: Decoder module of DeepLabV3P model
  
  Args:
      num_classes (int): The number of classes.
      decoder_channels (int): The channels of decoder.
      head_channels (int): The channels of head.
      class_key (list): The key name of output by classifier.
class_docstr_tok: ["Decoder","module","of","DeepLabV3P","model","Args",":","num_classes","(","int",")",":","The","number","of","classes",".","decoder_channels","(","int",")",":","The","channels","of","decoder",".","head_channels","(","int",")",":","The","channels","of","head",".","class_key","(","list",")",":","The","key","name","of","output","by","classifier","."]
code: def forward(self, x):
      pred = OrderedDict()
      # build classifier
      for i, key in enumerate(self.class_key):
          pred[key] = self.classifier[i](x)
  
      return pred
  
imports: from collections import OrderedDict
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the SinglePanopticDeepLabHead obj's underlying member method code with example usage: obj.forward(x) and returns: pred