code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      residual,
      norm_layer=BatchNorm,
      norm_kwargs=None,
      **kwargs,
  ):
      super(Root, self).__init__(**kwargs)
      if norm_kwargs is None:
          norm_kwargs = {}
      with self.name_scope():
          self.conv = nn.Conv2D(
              in_channels=in_channels,
              channels=out_channels,
              kernel_size=1,
              strides=1,
              use_bias=False,
              padding=(kernel_size - 1) // 2,
          )
          self.bn = norm_layer(in_channels=out_channels, **norm_kwargs)
          self.relu = nn.Activation("relu")
          self.residual = residual
  
imports: from __future__ import division
  import os
  import mxnet
  from mxnet.gluon.block import HybridBlock
  from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
label_desc: Use image node_id 1 to create a new Root object from inherited base classes: HybridBlock with example: obj = Root(in_channels, out_channels, kernel_size, residual, norm_layer, norm_kwargs)