code: def __init__(
      self,
      inplanes,
      planes,
      midplanes,
      stride=1,
      padding=1,
      norm_layer=BatchNorm3d,
      norm_kwargs=None,
      **kwargs,
  ):
      super(Conv2Plus1D, self).__init__()
  
      self.conv1 = nn.Conv3d(
          in_channels=inplanes,
          out_channels=midplanes,
          kernel_size=(1, 3, 3),
          stride=(1, stride, stride),
          padding=(0, padding, padding),
          bias=False,
      )
      self.bn1 = norm_layer(
          num_features=midplanes,
          **({} if norm_kwargs is None else norm_kwargs),
      )
      self.relu = nn.ReLU(inplace=False)
      self.conv2 = nn.Conv3d(
          in_channels=midplanes,
          out_channels=planes,
          kernel_size=(3, 1, 1),
          stride=(stride, 1, 1),
          padding=(padding, 0, 0),
          bias=False,
      )
  
imports: import torch
  import torch.nn
  from torch.nn import BatchNorm3d
label_desc: Use image node_id 1 to create a new Conv2Plus1D object from inherited base classes: nn with example: obj = Conv2Plus1D(inplanes, planes, midplanes, stride, padding, norm_layer, norm_kwargs)