class_docstr: Vision Transformer w/ Relative Position Bias
  
  Differing from classic vit, this impl
    * uses relative position index (swin v1 / beit) or relative log coord + mlp (swin v2) pos embed
    * defaults to no class token (can be enabled)
    * defaults to global avg pool for head (can be changed)
    * layer-scale (residual branch gain) enabled
class_docstr_tok: ["Vision","Transformer","w\/","Relative","Position","Bias","Differing","from","classic","vit",",","this","impl","*","uses","relative","position","index","(","swin","v1","\/","beit",")","or","relative","log","coord","+","mlp","(","swin","v2",")","pos","embed","*","defaults","to","no","class","token","(","can","be","enabled",")","*","defaults","to","global","avg","pool","for","head","(","can","be","changed",")","*","layer-scale","(","residual","branch","gain",")","enabled"]
code: def get_classifier(self):
      return self.head
  
imports: import logging
  import math
  from functools import partial
  from typing import Optional, Tuple
  import torch
  import torch.nn
  from torch.jit import Final
  from torch.utils.checkpoint import checkpoint
  from timm.data import IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
  from timm.layers import PatchEmbed, Mlp, DropPath, RelPosMlp, RelPosBias, use_fused_attn
  from ._builder import build_model_with_cfg
  from ._registry import generate_default_cfgs, register_model
label_desc: Use image node_id 6 for calling the VisionTransformerRelPos obj's underlying member method code with example usage: obj.get_classifier() and returns: self