code: def gaussian_filter1d(
      input,
      sigma,
      axis=-1,
      order=0,
      output=None,
      mode="reflect",
      cval=0.0,
      truncate=4.0,
  ):
      """One-dimensional Gaussian filter along the given axis.
  
      The lines of the array along the given axis are filtered with a Gaussian
      filter of the given standard deviation.
  
      Args:
          input (cupy.ndarray): The input array.
          sigma (scalar): Standard deviation for Gaussian kernel.
          axis (int): The axis of input along which to calculate. Default is -1.
          order (int): An order of ``0``, the default, corresponds to convolution
              with a Gaussian kernel. A positive order corresponds to convolution
              with that derivative of a Gaussian.
          output (cupy.ndarray, dtype or None): The array in which to place the
              output. Default is is same dtype as the input.
          mode (str): The array borders are handled according to the given mode
              (``'reflect'``, ``'constant'``, ``'nearest'``, ``'mirror'``,
              ``'wrap'``). Default is ``'reflect'``.
          cval (scalar): Value to fill past edges of input if mode is
              ``'constant'``. Default is ``0.0``.
          truncate (float): Truncate the filter at this many standard deviations.
              Default is ``4.0``.
  
      Returns:
          cupy.ndarray: The result of the filtering.
  
      .. seealso:: :func:`scipy.ndimage.gaussian_filter1d`
  
      .. note::
          When the output data type is integral (or when no output is provided
          and input is integral) the results may not perfectly match the results
          from SciPy due to floating-point rounding of intermediate results.
      """
      radius = int(float(truncate) * float(sigma) + 0.5)
      weights_dtype = _util._init_weights_dtype(input)
      weights = _gaussian_kernel1d(
          sigma, int(order), radius, dtype=weights_dtype
      )
      return correlate1d(input, weights, axis, output, mode, cval)
  
imports: import numpy
  import cupy
  from cupy import _core
  from cupy._core import internal
  from cupyx.scipy.ndimage import _util
  from cupyx.scipy.ndimage import _filters_core
  from cupyx.scipy.ndimage import _filters_generic
label_desc: Use image node_id 10 for calling a global function with example usage: gaussian_filter1d(input, sigma, axis, order, output, mode, cval, truncate) and returns: correlate1d