code: def get_gaussian_erf_kernel1d(
      kernel_size: int,
      sigma: float | Tensor,
      force_even: bool = False,
      *,
      device: Optional[Device] = None,
      dtype: Optional[Dtype] = None,
  ) -> Tensor:
      """Function that returns Gaussian filter coefficients by interpolating the error function.
  
      Adapted from: https://github.com/Project-MONAI/MONAI/blob/master/monai/networks/layers/convutils.py.
  
      Args:
          kernel_size: filter size. It should be odd and positive.
          sigma: gaussian standard deviation. If a tensor, should be in a shape :math:`(B, 1)`
          force_even: overrides requirement for odd kernel size.
          device: This value will be used if sigma is a float. Device desired to compute.
          dtype: This value will be used if sigma is a float. Dtype desired for compute.
  
      Returns:
          1D tensor with gaussian filter coefficients. Shape :math:`(B, \text{kernel_size})`
  
      Examples:
          >>> get_gaussian_erf_kernel1d(3, 2.5)
          tensor([[0.3245, 0.3511, 0.3245]])
          >>> get_gaussian_erf_kernel1d(5, 1.5)
          tensor([[0.1226, 0.2331, 0.2887, 0.2331, 0.1226]])
          >>> get_gaussian_erf_kernel1d(5, torch.tensor([[1.5], [2.1]]))
          tensor([[0.1226, 0.2331, 0.2887, 0.2331, 0.1226],
                  [0.1574, 0.2198, 0.2456, 0.2198, 0.1574]])
      """
      _check_kernel_size(kernel_size, allow_even=force_even)
  
      return gaussian_discrete_erf(
          kernel_size, sigma, 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 29 for calling a global function with example usage: get_gaussian_erf_kernel1d(kernel_size, sigma, force_even) and returns: gaussian_discrete_erf