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: Method to obtain re-parameterized kernel and bias.
  Reference: https://github.com/DingXiaoH/RepLKNet-pytorch
  
  Returns:
      Tuple of (kernel, bias) after fusing branches.
docstr_tok: ["Method","to","obtain","re-parameterized","kernel","and","bias",".","Reference",":","https",":","\/\/github.com\/DingXiaoH\/RepLKNet-pytorch","Returns",":","Tuple","of","(","kernel",",","bias",")","after","fusing","branches","."]
code: def _get_kernel_bias(self) -> Tuple[torch.Tensor, torch.Tensor]:
      """
      Method to obtain re-parameterized kernel and bias.
      Reference: https://github.com/DingXiaoH/RepLKNet-pytorch
  
      Returns:
          Tuple of (kernel, bias) after fusing branches.
      """
      lk_kernel, lk_bias = MobileOneBlock._fuse_conv_bn(
          self.lkb_origin.block.conv.weight, self.lkb_origin.block.norm
      )
      if hasattr(self, "small_conv"):
          sk_kernel, sk_bias = MobileOneBlock._fuse_conv_bn(
              self.small_conv.block.conv.weight,
              self.small_conv.block.norm,
          )
          lk_bias += sk_bias
          #   add to the central part
          lk_kernel += nn.functional.pad(
              sk_kernel,
              [(self.kernel_size - self.small_kernel_size) // 2] * 4,
          )
      return lk_kernel, lk_bias
  
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 3 for calling the RepLKBlock obj's underlying member method code with example usage: obj._get_kernel_bias() and returns: lk_kernel,  lk_bias