code: def group_matcher(self, coarse=False):
      matcher = dict(
          stem=r"^patch_embed",  # stem and embed
          blocks=r"^stages\.(\d+)",
      )
      return matcher
  
imports: import math
  from typing import Tuple, List, Callable, Union
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import DropPath, to_2tuple, to_ntuple, trunc_normal_, LayerNorm, use_fused_attn
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 5 for calling the PyramidVisionTransformerV2 obj's underlying member method code with example usage: obj.group_matcher(coarse) and returns: matcher