code: def __init__(
      self,
      in_channels,
      atrous_rates,
      norm_layer,
      norm_kwargs,
      height=60,
      width=60,
  ):
      super(_ASPP, self).__init__()
      out_channels = 256
      self.b0 = nn.HybridSequential()
      self.b0.add(
          nn.Conv2D(
              in_channels=in_channels,
              channels=out_channels,
              kernel_size=1,
              use_bias=False,
          )
      )
      self.b0.add(
          norm_layer(
              in_channels=out_channels,
              **({} if norm_kwargs is None else norm_kwargs),
          )
      )
      self.b0.add(nn.Activation("relu"))
  
      rate1, rate2, rate3 = tuple(atrous_rates)
      self.b1 = _ASPPConv(
          in_channels, out_channels, rate1, norm_layer, norm_kwargs
      )
      self.b2 = _ASPPConv(
          in_channels, out_channels, rate2, norm_layer, norm_kwargs
      )
      self.b3 = _ASPPConv(
          in_channels, out_channels, rate3, norm_layer, norm_kwargs
      )
      self.b4 = _AsppPooling(
          in_channels,
          out_channels,
          norm_layer=norm_layer,
          norm_kwargs=norm_kwargs,
          height=height,
          width=width,
      )
  
      self.project = nn.HybridSequential(prefix="bot_aspp_")
      self.project.add(
          nn.Conv2D(
              in_channels=5 * out_channels,
              channels=out_channels,
              kernel_size=1,
              use_bias=False,
          )
      )
  
imports: from mxnet.gluon import nn
  from mxnet.context import cpu
  from mxnet.gluon.nn import HybridBlock
  from .wideresnet import wider_resnet38_a2
label_desc: Use image node_id 1 to create a new _ASPP object from inherited base classes: nn with example: obj = _ASPP(in_channels, atrous_rates, norm_layer, norm_kwargs, height, width)