code: def _make_layer(
      self, block, in_planes, out_planes, num_blocks, stride, drop_rate
  ):
      layers = []
      for i in range(int(num_blocks)):
          layers.append(
              block(
                  in_planes=in_planes if i == 0 else out_planes,
                  out_planes=out_planes,
                  stride=stride if i == 0 else 1,
                  drop_rate=drop_rate,
              )
          )
      return nn.Sequential(*layers)
  
imports: import math
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the ConvGroup obj's underlying member method code with example usage: obj._make_layer(block, in_planes, out_planes, num_blocks, stride, drop_rate) and returns: nn