code: def get_relative_position_index(win_h: int, win_w: int):
      # get pair-wise relative position index for each token inside the window
      coords = torch.stack(
          torch.meshgrid([torch.arange(win_h), torch.arange(win_w)])
      )  # 2, Wh, Ww
      coords_flatten = torch.flatten(coords, 1)  # 2, Wh*Ww
      relative_coords = (
          coords_flatten[:, :, None] - coords_flatten[:, None, :]
      )  # 2, Wh*Ww, Wh*Ww
      relative_coords = relative_coords.permute(
          1, 2, 0
      ).contiguous()  # Wh*Ww, Wh*Ww, 2
      relative_coords[:, :, 0] += win_h - 1  # shift to start from 0
      relative_coords[:, :, 1] += win_w - 1
      relative_coords[:, :, 0] *= 2 * win_w - 1
      return relative_coords.sum(-1)
  
imports: import logging
  import math
  from typing import Callable, List, Optional, Tuple, Union
  import torch
  import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import PatchEmbed, Mlp, DropPath, ClassifierHead, to_2tuple, to_ntuple, trunc_normal_, _assert, use_fused_attn, resize_rel_pos_bias_table, resample_patch_embed
  from ._builder import build_model_with_cfg
  from ._features_fx import register_notrace_function
  from ._manipulate import checkpoint_seq, named_apply
  from ._registry import generate_default_cfgs, register_model, register_model_deprecations
  from .vision_transformer import get_init_weights_vit
label_desc: Use image node_id 3 for calling a global function with example usage: get_relative_position_index(win_h, win_w) and returns: relative_coords