code: def _make_layer(self, block, conv_builder, planes, blocks, stride=1):
      downsample = None
  
      if stride != 1 or self.inplanes != planes * block.expansion:
          ds_stride = conv_builder.get_downsample_stride(stride)
          downsample = nn.Sequential(
              nn.Conv3d(
                  self.inplanes,
                  planes * block.expansion,
                  kernel_size=1,
                  stride=ds_stride,
                  bias=False,
              ),
              nn.BatchNorm3d(planes * block.expansion),
          )
      layers = []
      layers.append(
          block(self.inplanes, planes, conv_builder, stride, downsample)
      )
  
      self.inplanes = planes * block.expansion
      for i in range(1, blocks):
          layers.append(block(self.inplanes, planes, conv_builder))
  
      return nn.Sequential(*layers)
  
imports: import torch.nn
  from torch.hub import load_state_dict_from_url
label_desc: Use image node_id 4 for calling the VideoResNet obj's underlying member method code with example usage: obj._make_layer(block, conv_builder, planes, blocks, stride) and returns: nn