code: def __init__(
      self,
      inplanes,
      planes,
      stride=1,
      dilation=1,
      norm_layer=BatchNorm,
      norm_kwargs=None,
      **kwargs,
  ):
      super(BottleneckX, self).__init__(**kwargs)
      if norm_kwargs is None:
          norm_kwargs = {}
      cardinality = BottleneckX.cardinality
      bottle_planes = planes * cardinality // 32
      with self.name_scope():
          self.conv1 = nn.Conv2D(
              in_channels=inplanes,
              channels=bottle_planes,
              kernel_size=1,
              use_bias=False,
          )
          self.bn1 = norm_layer(
              in_channels=bottle_planes, **norm_kwargs
          )
          self.conv2 = nn.Conv2D(
              in_channels=bottle_planes,
              channels=bottle_planes,
              kernel_size=3,
              strides=stride,
              padding=dilation,
              use_bias=False,
              dilation=dilation,
              groups=cardinality,
          )
          self.bn2 = norm_layer(
              in_channels=bottle_planes, **norm_kwargs
          )
          self.conv3 = nn.Conv2D(
              in_channels=bottle_planes,
              channels=planes,
              kernel_size=1,
              use_bias=False,
          )
          self.bn3 = norm_layer(**norm_kwargs)
          self.relu = nn.Activation("relu")
          self.stride = stride
  
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 BottleneckX object from inherited base classes: HybridBlock with example: obj = BottleneckX(inplanes, planes, stride, dilation, norm_layer, norm_kwargs)