code: def get_laplacian_kernel2d(
      kernel_size: tuple[int, int] | int,
      *,
      device: Optional[Device] = None,
      dtype: Dtype = torch.float32,
  ) -> Tensor:
      r"""Function that returns Gaussian filter matrix coefficients.
  
      Args:
          kernel_size: filter size should be odd.
          device: tensor device desired to create the kernel
          dtype: tensor dtype desired to create the kernel
  
      Returns:
          2D tensor with laplacian filter matrix coefficients.
  
      Shape:
          - Output: :math:`(\text{kernel_size}_x, \text{kernel_size}_y)`
  
      Examples:
          >>> get_laplacian_kernel2d(3)
          tensor([[ 1.,  1.,  1.],
                  [ 1., -8.,  1.],
                  [ 1.,  1.,  1.]])
          >>> get_laplacian_kernel2d(5)
          tensor([[  1.,   1.,   1.,   1.,   1.],
                  [  1.,   1.,   1.,   1.,   1.],
                  [  1.,   1., -24.,   1.,   1.],
                  [  1.,   1.,   1.,   1.,   1.],
                  [  1.,   1.,   1.,   1.,   1.]])
      """
      # TODO: add default dtype as None when kornia relies on torch > 1.12
  
      ky, kx = _unpack_2d_ks(kernel_size)
      _check_kernel_size((ky, kx))
  
      kernel = torch.ones((ky, kx), device=device, dtype=dtype)
      mid_x = kx // 2
      mid_y = ky // 2
  
      kernel[mid_y, mid_x] = 1 - kernel.sum()
      return kernel
  
imports: from __future__ import annotations
  import math
  from math import sqrt
  from typing import Any, Optional
  import torch
  from kornia.core import Device, Dtype, Tensor, concatenate, cos, stack, tensor, where, zeros, zeros_like
  from kornia.core.check import KORNIA_CHECK, KORNIA_CHECK_IS_TENSOR, KORNIA_CHECK_SHAPE
  from kornia.utils import deprecated
label_desc: Use image node_id 33 for calling a global function with example usage: get_laplacian_kernel2d(kernel_size) and returns: kernel