code: def normalize_pixel_coordinates3d(
      pixel_coordinates: Tensor,
      depth: int,
      height: int,
      width: int,
      eps: float = 1e-8,
  ) -> Tensor:
      r"""Normalize pixel coordinates between -1 and 1.
  
      Normalized, -1 if on extreme left, 1 if on extreme right (x = w-1).
  
      Args:
          pixel_coordinates: the grid with pixel coordinates. Shape can be :math:`(*, 3)`.
          depth: the maximum depth in the z-axis.
          height: the maximum height in the y-axis.
          width: the maximum width in the x-axis.
          eps: safe division by zero.
  
      Return:
          the normalized pixel coordinates.
      """
      if pixel_coordinates.shape[-1] != 3:
          raise ValueError(
              f"Input pixel_coordinates must be of shape (*, 3). Got {pixel_coordinates.shape}"
          )
      # compute normalization factor
      dhw: Tensor = (
          stack([tensor(depth), tensor(width), tensor(height)])
          .to(pixel_coordinates.device)
          .to(pixel_coordinates.dtype)
      )
  
      factor: Tensor = tensor(2.0) / (dhw - 1).clamp(eps)
  
      return factor * pixel_coordinates - 1
  
imports: from __future__ import annotations
  from typing import Optional
  import torch
  import torch.nn.functional
  from kornia.constants import pi
  from kornia.core import Tensor, concatenate, cos, pad, sin, stack, tensor, where, zeros_like
  from kornia.core.check import KORNIA_CHECK, KORNIA_CHECK_SHAPE
  from kornia.utils import deprecated
  from kornia.utils.helpers import _torch_inverse_cast
label_desc: Use image node_id 27 for calling a global function with example usage: normalize_pixel_coordinates3d(pixel_coordinates, depth, height, width, eps) and returns: unknown