code: def _transform_warp_impl3d(
      src: Tensor,
      dst_pix_trans_src_pix: Tensor,
      dsize_src: tuple[int, int, int],
      dsize_dst: tuple[int, int, int],
      grid_mode: str,
      padding_mode: str,
      align_corners: bool,
  ) -> Tensor:
      """Compute the transform in normalized coordinates and perform the warping."""
      dst_norm_trans_src_norm: Tensor = normalize_homography3d(
          dst_pix_trans_src_pix, dsize_src, dsize_dst
      )
  
      src_norm_trans_dst_norm = torch.inverse(dst_norm_trans_src_norm)
      return homography_warp3d(
          src,
          src_norm_trans_dst_norm,
          dsize_dst,
          grid_mode,
          padding_mode,
          align_corners,
          True,
      )
  
imports: from __future__ import annotations
  from typing import Optional
  import torch
  import torch.nn.functional
  from kornia.core import Tensor, concatenate, ones, ones_like, stack, tan, tensor, zeros
  from kornia.core.check import KORNIA_CHECK, KORNIA_CHECK_SHAPE
  from kornia.geometry.conversions import angle_to_rotation_matrix, axis_angle_to_rotation_matrix, convert_affinematrix_to_homography, convert_affinematrix_to_homography3d, deg2rad, normalize_homography, normalize_homography3d, normalize_pixel_coordinates
  from kornia.geometry.linalg import transform_points
  from kornia.utils import create_meshgrid, create_meshgrid3d, eye_like
  from kornia.utils.helpers import _torch_inverse_cast, _torch_solve_cast
label_desc: Use image node_id 23 for calling a global function with example usage: _transform_warp_impl3d(src, dst_pix_trans_src_pix, dsize_src, dsize_dst, grid_mode, padding_mode, align_corners) and returns: homography_warp3d