code: def group_matcher(self, coarse=False):
      matcher = dict(
          stem=r"^stem",
          blocks=[(r"^blocks\.(\d+)", None), (r"^norm", (99999,))],
      )  # stem and embed
      return matcher
  
imports: import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from ._registry import register_model, generate_default_cfgs
  from ._builder import build_model_with_cfg
  from timm.layers import SqueezeExcite, trunc_normal_, to_ntuple, to_2tuple
  from ._manipulate import checkpoint_seq
  import torch
label_desc: Use image node_id 2 for calling the RepVit obj's underlying member method code with example usage: obj.group_matcher(coarse) and returns: matcher