code: def __init__(
      self,
      in_channels,
      out_channels,
      stride,
      affine,
      track_running_stats,
      use_bn=True,
      num_nodes=4,
      keep_mask=None,
  ):
      super(SearchCell, self).__init__()
      self.num_nodes = num_nodes
      self.options = nn.ModuleList()
      for curr_node in range(self.num_nodes - 1):
          for prev_node in range(curr_node + 1):
              for _op_name in OPS.keys():
                  op = OPS[_op_name](
                      in_channels,
                      out_channels,
                      stride,
                      affine,
                      track_running_stats,
                      use_bn,
                  )
                  self.options.append(op)
  
      if keep_mask is not None:
          self.keep_mask = keep_mask
      else:
          self.keep_mask = [True] * len(self.options)
  
imports: import torch.nn
label_desc: Use image node_id 1 to create a new SearchCell object from inherited base classes: nn with example: obj = SearchCell(in_channels, out_channels, stride, affine, track_running_stats, use_bn, num_nodes, keep_mask)