code: def __init__(self, nChannels, out_channels, use_dropout):
      super(Transition, self).__init__()
      self.bn1 = nn.BatchNorm2D(out_channels)
      self.conv1 = nn.Conv2D(
          nChannels, out_channels, kernel_size=1, bias_attr=False
      )
      self.use_dropout = use_dropout
      self.dropout = nn.Dropout(p=0.2)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new Transition object from inherited base classes: nn with example: obj = Transition(nChannels, out_channels, use_dropout)