code: def __init__(self, in_planes, out_planes, stride=1):
      super(CellB, self).__init__()
      self.stride = stride
      # Left branch
      self.sep_conv1 = SepConv(
          in_planes, out_planes, kernel_size=7, stride=stride
      )
      self.sep_conv2 = SepConv(
          in_planes, out_planes, kernel_size=3, stride=stride
      )
      # Right branch
      self.sep_conv3 = SepConv(
          in_planes, out_planes, kernel_size=5, stride=stride
      )
      if stride == 2:
          self.conv1 = nn.Conv2d(
              in_planes,
              out_planes,
              kernel_size=1,
              stride=1,
              padding=0,
              bias=False,
          )
          self.bn1 = nn.BatchNorm2d(out_planes)
      # Reduce channels
      self.conv2 = nn.Conv2d(
          2 * out_planes,
          out_planes,
          kernel_size=1,
          stride=1,
          padding=0,
          bias=False,
      )
      self.bn2 = nn.BatchNorm2d(out_planes)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new CellB object from inherited base classes: nn with example: obj = CellB(in_planes, out_planes, stride)