code: def __init__(self, in_channels, out_channels, is_batchnorm):
      super(MaxPoolConv2D, self).__init__(
          nn.MaxPool2D(kernel_size=2),
          UnetConv2D(in_channels, out_channels, is_batchnorm),
      )
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models.layers.layer_libs import SyncBatchNorm
  from paddleseg.cvlibs.param_init import kaiming_normal_init
label_desc: Use image node_id 1 to create a new MaxPoolConv2D object from inherited base classes: nn with example: obj = MaxPoolConv2D(in_channels, out_channels, is_batchnorm)