class_docstr: Building block of Conv2Plus1D
  
  Parameters
  ----------
  inplanes : int.
      Input channels of each block.
  planes : int.
      Output channels of each block.
  midplanes : int.
      Intermediate channels of each block.
  stride : int, default is 1.
      Stride in each dimension of 3D convolutional layers in a block.
  padding : int, default is 1.
      Padding in each dimension of the feature map.
  norm_layer : object
      Normalization layer used (default: :class:`mxnet.gluon.nn.BatchNorm`)
      Can be :class:`mxnet.gluon.nn.BatchNorm` or :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
  norm_kwargs : dict
      Additional `norm_layer` arguments, for example `num_devices=4`
      for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
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code: def __init__(
      self,
      inplanes,
      planes,
      midplanes,
      stride=1,
      padding=1,
      norm_layer=BatchNorm,
      norm_kwargs=None,
      **kwargs,
  ):
      super(Conv2Plus1D, self).__init__()
  
      with self.name_scope():
          self.conv1 = nn.Conv3D(
              in_channels=inplanes,
              channels=midplanes,
              kernel_size=(1, 3, 3),
              strides=(1, stride, stride),
              padding=(0, padding, padding),
              use_bias=False,
          )
          self.bn1 = norm_layer(
              in_channels=midplanes,
              **({} if norm_kwargs is None else norm_kwargs),
          )
          self.relu = nn.Activation("relu")
          self.conv2 = nn.Conv3D(
              in_channels=midplanes,
              channels=planes,
              kernel_size=(3, 1, 1),
              strides=(stride, 1, 1),
              padding=(padding, 0, 0),
              use_bias=False,
          )
  
imports: from mxnet import init
  from mxnet.context import cpu
  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 Conv2Plus1D object from inherited base classes: HybridBlock with example: obj = Conv2Plus1D(inplanes, planes, midplanes, stride, padding, norm_layer, norm_kwargs)