code: def get_laplacian_kernel1d(
      kernel_size: int,
      *,
      device: Optional[Device] = None,
      dtype: Dtype = torch.float32,
  ) -> Tensor:
      r"""Function that returns the coefficients of a 1D Laplacian filter.
  
      Args:
          kernel_size: filter size. It should be odd and positive.
          device: tensor device desired to create the kernel
          dtype: tensor dtype desired to create the kernel
  
      Returns:
          1D tensor with laplacian filter coefficients.
  
      Shape:
          - Output: math:`(\text{kernel_size})`
  
      Examples:
          >>> get_laplacian_kernel1d(3)
          tensor([ 1., -2.,  1.])
          >>> get_laplacian_kernel1d(5)
          tensor([ 1.,  1., -4.,  1.,  1.])
      """
      # TODO: add default dtype as None when kornia relies on torch > 1.12
  
      _check_kernel_size(kernel_size)
  
      return laplacian_1d(kernel_size, device=device, dtype=dtype)
  
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 32 for calling a global function with example usage: get_laplacian_kernel1d(kernel_size) and returns: laplacian_1d