code: def _compute_interpolation_tiles(
      padded_imgs: torch.Tensor, tile_size: Tuple[int, int]
  ) -> torch.Tensor:
      r"""Compute interpolation tiles on a properly padded set of images.
  
      Note that images must be padded. So, the tile_size (TH, TW) * grid_size (GH, GW) = image_size (H, W)
  
      Args:
          padded_imgs: batch of 2D images with shape (B, C, H, W) already padded to extract tiles
                                      of size (TH, TW).
          tile_size: shape of the current tiles (TH, TW).
  
      Returns:
          tensor with the interpolation tiles (B, 2GH, 2GW, C, TH/2, TW/2).
      """
      if padded_imgs.dim() != 4:
          raise AssertionError("Images Tensor must be 4D.")
  
      if padded_imgs.shape[-2] % tile_size[0] != 0:
          raise AssertionError("Images are not correctly padded.")
  
      if padded_imgs.shape[-1] % tile_size[1] != 0:
          raise AssertionError("Images are not correctly padded.")
  
      # tiles to be interpolated are built by dividing in 4 each already existing
      interp_kernel_vert: int = tile_size[0] // 2
      interp_kernel_horz: int = tile_size[1] // 2
  
      c: int = padded_imgs.shape[-3]
      interp_tiles: torch.Tensor = (
          padded_imgs.unfold(1, c, c)
          .unfold(2, interp_kernel_vert, interp_kernel_vert)
          .unfold(3, interp_kernel_horz, interp_kernel_horz)
          .squeeze(1)
      ).contiguous()  # 2GH x 2GW x C x TH/2 x TW/2
  
      if interp_tiles.shape[-3] != c:
          raise AssertionError
  
      if interp_tiles.shape[-2] != tile_size[0] / 2:
          raise AssertionError
  
      if interp_tiles.shape[-1] != tile_size[1] / 2:
          raise AssertionError
  
      return interp_tiles
  
file_path: kornia/kornia/enhance/equalization.py
imports: import math
  from typing import Tuple
  import torch
  import torch.nn.functional
  from kornia.utils.helpers import _torch_histc_cast
  from kornia.utils.image import perform_keep_shape_image
  from .histogram import histogram
label_desc: Use image node_id 2 for calling a global function with example usage: _compute_interpolation_tiles(padded_imgs, tile_size) and returns: interp_tiles