code: def _create_vision_transformer_relpos(
      variant, pretrained=False, **kwargs
  ):
      if kwargs.get("features_only", None):
          raise RuntimeError(
              "features_only not implemented for Vision Transformer models."
          )
  
      model = build_model_with_cfg(
          VisionTransformerRelPos, variant, pretrained, **kwargs
      )
      return model
  
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 1 for calling a global function with example usage: _create_vision_transformer_relpos(variant, pretrained) and returns: model