class_docstr: This class defines overparameterized large kernel conv block in `RepLKNet <https://arxiv.org/abs/2203.06717>`_
  Reference: https://github.com/DingXiaoH/RepLKNet-pytorch
  
  Args:
      opts: Command-line arguments.
      in_channels: Number of input channels.
      out_channels: Number of output channels.
      kernel_size: Kernel size of the large kernel conv branch.
      stride: Stride size. Default: 1
      dilation: Kernel dilation factor. Default: 1
      groups: Group number. Default: 1
      small_kernel_size: Kernel size of small kernel conv branch.
      inference_mode: If True, instantiates model in inference mode. Default: ``False``
      use_act: If True, activation is used. Default: ``True``
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docstr: Following works like `RepVGG: Making VGG-style ConvNets Great Again` -
  https://arxiv.org/pdf/2101.03697.pdf. We re-parameterize multi-branched
  architecture used at training time to obtain a plain CNN-like structure
  for inference.
docstr_tok: ["Following","works","like","`","RepVGG",":","Making","VGG-style","ConvNets","Great","Again","`","-","https",":","\/\/arxiv.org\/pdf\/2101.03697.pdf",".","We","re-parameterize","multi-branched","architecture","used","at","training","time","to","obtain","a","plain","CNN-like","structure","for","inference","."]
code: def reparameterize(self) -> None:
      """
      Following works like `RepVGG: Making VGG-style ConvNets Great Again` -
      https://arxiv.org/pdf/2101.03697.pdf. We re-parameterize multi-branched
      architecture used at training time to obtain a plain CNN-like structure
      for inference.
      """
      kernel, bias = self._get_kernel_bias()
      self.lkb_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,
          bias=True,
      )
      self.lkb_reparam.weight.data = kernel
      self.lkb_reparam.bias.data = bias
      self.__delattr__("lkb_origin")
      if hasattr(self, "small_conv"):
          self.__delattr__("small_conv")
  
imports: import argparse
  from typing import Tuple, Union
  import torch
  import torch.nn
  from cvnets.layers import ConvLayer2d, Identity
  from cvnets.layers.activation import build_activation_layer
  from cvnets.layers.normalization.batch_norm import BatchNorm2d
  from cvnets.modules import BaseModule, SqueezeExcitation
label_desc: Use image node_id 4 for calling the RepLKBlock obj's underlying member method code with example usage: obj.reparameterize() without return types