code: def __init__(self, in_channels, out_channels):
      super().__init__()
      self.conv = nn.Conv2D(
          in_channels,
          out_channels,
          kernel_size=3,
          stride=1,
          padding=1,
          dilation=1,
      )
      self._relu = layers.Activation("relu")
      self._max_pool = nn.MaxPool2D(kernel_size=2, stride=2)
  
imports: import os
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
label_desc: Use image node_id 1 to create a new ConvReLUPool object from inherited base classes: nn with example: obj = ConvReLUPool(in_channels, out_channels)