code: def _make_layer(self, planes, num_cells):
      layers = []
      for _ in range(num_cells):
          layers.append(
              self.cell_type(self.in_planes, planes, stride=1)
          )
          self.in_planes = planes
      return nn.Sequential(*layers)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the PNASNet obj's underlying member method code with example usage: obj._make_layer(planes, num_cells) and returns: nn