code: def get_abs_pos(abs_pos, has_cls_token, hw):
      """
      Calculate absolute positional embeddings. If needed, resize embeddings and remove cls_token
          dimension for the original embeddings.
      Args:
          abs_pos (Tensor): absolute positional embeddings with (1, num_position, C).
          has_cls_token (bool): If true, has 1 embedding in abs_pos for cls token.
          hw (Tuple): size of input image tokens.
  
      Returns:
          Absolute positional embeddings after processing with shape (1, H, W, C)
      """
      h, w = hw
      if has_cls_token:
          abs_pos = abs_pos[:, 1:]
      xy_num = abs_pos.shape[1]
      size = int(math.sqrt(xy_num))
      assert size * size == xy_num
  
      if size != h or size != w:
          new_abs_pos = F.interpolate(
              abs_pos.reshape(1, size, size, -1).permute(0, 3, 1, 2),
              size=(h, w),
              mode="bicubic",
              align_corners=False,
          )
  
          return new_abs_pos.permute(0, 2, 3, 1)
      else:
          return abs_pos.reshape(1, h, w, -1)
  
file_path: detectron2/detectron2/modeling/backbone/utils.py
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 5 for calling a global function with example usage: get_abs_pos(abs_pos, has_cls_token, hw) and returns: new_abs_pos, abs_pos