code: def _make_layer(self, block, planes, blocks, stride=1, dcn=None):
      downsample = None
      if stride != 1 or self.inplanes != planes * block.expansion:
          downsample = nn.Sequential(
              nn.Conv2D(
                  self.inplanes,
                  planes * block.expansion,
                  kernel_size=1,
                  stride=stride,
                  bias_attr=False,
              ),
              BatchNorm2d(planes * block.expansion, momentum=0.1),
          )
  
      layers = []
      layers.append(
          block(self.inplanes, planes, stride, downsample, dcn=dcn)
      )
      self.inplanes = planes * block.expansion
      for i in range(1, blocks):
          layers.append(block(self.inplanes, planes, dcn=dcn))
      self.out_channels.append(planes * block.expansion)
      return nn.Sequential(*layers)
  
imports: import math
  import paddle
  from paddle import nn
label_desc: Use image node_id 2 for calling the ResNet obj's underlying member method code with example usage: obj._make_layer(block, planes, blocks, stride, dcn) and returns: nn