code: def __init__(
      self,
      in_channels,
      out_channels,
      norm_layer,
      norm_kwargs,
      height=64,
      width=64,
      **kwargs,
  ):
      super(_AsppPooling, self).__init__()
      self.gap = nn.HybridSequential()
      self._up_kwargs = {"height": height, "width": width}
      with self.gap.name_scope():
          self.gap.add(nn.GlobalAvgPool2D())
          self.gap.add(
              nn.Conv2D(
                  in_channels=in_channels,
                  channels=out_channels,
                  kernel_size=1,
                  use_bias=False,
              )
          )
          self.gap.add(
              norm_layer(
                  in_channels=out_channels,
                  **({} if norm_kwargs is None else norm_kwargs),
              )
          )
          self.gap.add(nn.Activation("relu"))
  
imports: from mxnet.gluon import nn
  from mxnet.context import cpu
  from mxnet.gluon.nn import HybridBlock
  from mxnet import gluon
  from .fcn import _FCNHead
  from .xception import get_xcetption
label_desc: Use image node_id 1 to create a new _AsppPooling object from inherited base classes: nn with example: obj = _AsppPooling(in_channels, out_channels, norm_layer, norm_kwargs, height, width)