class_docstr: RepLKNet model
  
  Args:
      large_kernel_sizes `tuple or list`: large kernel sizes
      layers (`tuple or list`): number of blocks at different stages
      channels (`tuple or list`): dimensions used at different stages
      drop_rate (`float`): drop rate used for stochastic depth
      small_kernel (`int`): the small kernel size
      dw_ratio (`int`): times of dim over input dim in depthwise conv
      ffn_ratio (`int`): times of internal dim over input dim in conv FFN
      in_channels (`int`): input dimension
      num_classes (`int`): number of classes for linear projection at the end
      out_indices (`tuple or list`): layer indices to return outputs
      small_kernel_merged (`bool`): flag to merge small kernels in ReparamLargeKernelConv
      norm_intermediate_features (`bool`): flag to return normalized features for downstream tasks
      deep_fuse (`bool`): flag to manually fuse BN
class_docstr_tok: ["RepLKNet","model","Args",":","large_kernel_sizes","`","tuple","or","list","`",":","large","kernel","sizes","layers","(","`","tuple","or","list","`",")",":","number","of","blocks","at","different","stages","channels","(","`","tuple","or","list","`",")",":","dimensions","used","at","different","stages","drop_rate","(","`","float","`",")",":","drop","rate","used","for","stochastic","depth","small_kernel","(","`","int","`",")",":","the","small","kernel","size","dw_ratio","(","`","int","`",")",":","times","of","dim","over","input","dim","in","depthwise","conv","ffn_ratio","(","`","int","`",")",":","times","of","internal","dim","over","input","dim","in","conv","FFN","in_channels","(","`","int","`",")",":","input","dimension","num_classes","(","`","int","`",")",":","number","of","classes","for","linear","projection","at","the","end","out_indices","(","`","tuple","or","list","`",")",":","layer","indices","to","return","outputs","small_kernel_merged","(","`","bool","`",")",":","flag","to","merge","small","kernels","in","ReparamLargeKernelConv","norm_intermediate_features","(","`","bool","`",")",":","flag","to","return","normalized","features","for","downstream","tasks","deep_fuse","(","`","bool","`",")",":","flag","to","manually","fuse","BN"]
code: def structural_reparam(self):
      for m in self.modules():
          if hasattr(m, "merge_kernel"):
              m.merge_kernel()
  
file_path: towhee/towhee/models/replknet/replknet.py
imports: import torch
  from torch import nn
  from towhee.models.utils import create_model
  from towhee.models.replknet import RepLKNetStage, fuse_bn, conv_bn_relu, get_configs
label_desc: Use image node_id 4 for calling the RepLKNet obj's underlying member method code with example usage: obj.structural_reparam() without return types