code: def group_matcher(self, coarse=False):
      return dict(
          stem=r"^stem",
          blocks=r"^stages\.(\d+)"
          if coarse
          else r"^stages\.(\d+).blocks\.(\d+)",
      )
  
imports: from typing import List
  import torch
  import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import ConvNormAct, SeparableConvNormAct, BatchNormAct2d, ClassifierHead, DropPath, create_attn, create_norm_act_layer
  from ._builder import build_model_with_cfg
  from ._manipulate import checkpoint_seq
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 2 for calling the VovNet obj's underlying member method code with example usage: obj.group_matcher(coarse) and returns: dict