code: def _get_rel_pos_bias(self):
      relative_position_bias = self.relative_position_bias_table[
          self.relative_position_index.view(-1)
      ].view(
          self.window_size[0] * self.window_size[1] + 1,
          self.window_size[0] * self.window_size[1] + 1,
          -1,
      )  # Wh*Ww,Wh*Ww,nH
      relative_position_bias = relative_position_bias.permute(
          2, 0, 1
      ).contiguous()  # nH, Wh*Ww, Wh*Ww
      return relative_position_bias.unsqueeze(0)
  
imports: import math
  from typing import Callable, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.checkpoint import checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import PatchEmbed, Mlp, SwiGLU, LayerNorm, DropPath, trunc_normal_, use_fused_attn
  from timm.layers import resample_patch_embed, resample_abs_pos_embed, resize_rel_pos_bias_table
  from ._builder import build_model_with_cfg
  from ._registry import generate_default_cfgs, register_model
  from .vision_transformer import checkpoint_filter_fn
label_desc: Use image node_id 2 for calling the Attention obj's underlying member method code with example usage: obj._get_rel_pos_bias() and returns: relative_position_bias