code: def vit_relpos_small_patch16_rpn_224(
      pretrained=False, **kwargs
  ) -> VisionTransformerRelPos:
      """ViT-Base (ViT-B/16) w/ relative log-coord position and residual post-norm, no class token"""
      model_args = dict(
          patch_size=16,
          embed_dim=384,
          depth=12,
          num_heads=6,
          qkv_bias=False,
          block_fn=ResPostRelPosBlock,
      )
      model = _create_vision_transformer_relpos(
          "vit_relpos_small_patch16_rpn_224",
          pretrained=pretrained,
          **dict(model_args, **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 13 for calling a global function with example usage: vit_relpos_small_patch16_rpn_224(pretrained) and returns: model