code: def _make_stage(self, planes, num_blocks, stride):
      strides = [stride] + [1] * (num_blocks - 1)
      blocks = []
      for stride in strides:
          cur_groups = self.override_groups_map.get(
              self.cur_layer_idx, 1
          )
          blocks.append(
              RepVGGBlock(
                  in_channels=self.in_planes,
                  out_channels=planes,
                  kernel_size=3,
                  stride=stride,
                  padding=1,
                  groups=cur_groups,
              )
          )
          self.in_planes = planes
          self.cur_layer_idx += 1
      return nn.Sequential(*blocks)
  
imports: import os
  from typing import Union
  import paddle
  import paddle.nn
  import paddlehub.vision.transforms
  import numpy
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.cv_module import ImageClassifierModule
label_desc: Use image node_id 2 for calling the RepVGG_B2G4 obj's underlying member method code with example usage: obj._make_stage(planes, num_blocks, stride) and returns: nn