code: def __init__(self, num_channels, num_filters):
      super(Decoder, self).__init__()
  
      self.conv1 = nn.Conv2D(
          num_channels,
          num_filters,
          kernel_size=3,
          stride=1,
          padding=1,
          bias_attr=False,
      )
      self.bn1 = nn.BatchNorm(num_filters, act="relu")
  
      self.conv2 = nn.Conv2D(
          num_filters,
          num_filters,
          kernel_size=3,
          stride=1,
          padding=1,
          bias_attr=False,
      )
      self.bn2 = nn.BatchNorm(num_filters, act="relu")
  
      self.conv0 = nn.Conv2D(
          num_channels,
          num_filters,
          kernel_size=1,
          stride=1,
          padding=0,
          bias_attr=False,
      )
      self.bn0 = nn.BatchNorm(num_filters, act="relu")
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from paddle import nn
  import numpy
  import cv2
label_desc: Use image node_id 1 to create a new Decoder object from inherited base classes: nn with example: obj = Decoder(num_channels, num_filters)