code: def group_matcher(self, coarse=False):
      matcher = dict(
          stem=r"^stem",
          blocks=r"^features\.(\d+)",
      )
      return matcher
  
imports: from functools import partial
  from math import ceil
  import torch
  import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import ClassifierHead, create_act_layer, ConvNormAct, DropPath, make_divisible, SEModule
  from ._builder import build_model_with_cfg
  from ._efficientnet_builder import efficientnet_init_weights
  from ._manipulate import checkpoint_seq
  from ._registry import generate_default_cfgs, register_model
label_desc: Use image node_id 2 for calling the RexNet obj's underlying member method code with example usage: obj.group_matcher(coarse) and returns: matcher