class_docstr: Vision Transformer w/ Distillation Token and Head
  
  Distillation token & head support for `DeiT: Data-efficient Image Transformers`
      - https://arxiv.org/abs/2012.12877
code: def group_matcher(self, coarse=False):
      return dict(
          stem=r"^cls_token|pos_embed|patch_embed|dist_token",
          blocks=[
              (r"^blocks\.(\d+)", None),
              (r"^norm", (99999,)),
          ],  # final norm w/ last block
      )
  
imports: from functools import partial
  from typing import Sequence, Union
  import torch
  from torch import nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import resample_abs_pos_embed
  from timm.models.vision_transformer import VisionTransformer, trunc_normal_, checkpoint_filter_fn
  from ._builder import build_model_with_cfg
  from ._manipulate import checkpoint_seq
  from ._registry import generate_default_cfgs, register_model, register_model_deprecations
label_desc: Use image node_id 3 for calling the VisionTransformerDistilled obj's underlying member method code with example usage: obj.group_matcher(coarse) and returns: dict