code: def eval(self):
      if not hasattr(self, "rbr_reparam"):
          self.rbr_reparam = nn.Conv2D(
              in_channels=self.in_channels,
              out_channels=self.out_channels,
              kernel_size=self.kernel_size,
              stride=self.stride,
              padding=self.padding,
              dilation=self.dilation,
              groups=self.groups,
              padding_mode=self.padding_mode,
          )
      self.training = False
      kernel, bias = self.get_equivalent_kernel_bias()
      self.rbr_reparam.weight.set_value(kernel)
      self.rbr_reparam.bias.set_value(bias)
      for layer in self.sublayers():
          layer.eval()
  
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 3 for calling the RepVGGBlock obj's underlying member method code with example usage: obj.eval() without return types