class_docstr: Vision Transformer with support for patch or hybrid CNN input stage
class_docstr_tok: ["Vision","Transformer","with","support","for","patch","or","hybrid","CNN","input","stage"]
code: def no_weight_decay(self):
      return {"pos_embed", "cls_token"}
  
imports: import copy
  import logging
  import math
  from functools import partial
  from typing import List
  import torch
  import torch.nn
  import torch.nn.functional
  from vissl.config import AttrDict
  from vissl.models.model_helpers import DropPath, to_2tuple, trunc_normal_
  from vissl.models.trunks import register_model_trunk
label_desc: Use image node_id 4 for calling the BEiT obj's underlying member method code with example usage: obj.no_weight_decay() and returns: unknown