code: def gaussian_gradient_magnitude(
      input, sigma, output=None, mode="reflect", cval=0.0, **kwargs
  ):
      """Multi-dimensional gradient magnitude using Gaussian derivatives.
  
      Args:
          input (cupy.ndarray): The input array.
          sigma (scalar or sequence of scalar): Standard deviations for each axis
              of Gaussian kernel. A single value applies to all axes.
          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``.
          kwargs (dict, optional):
              dict of extra keyword arguments to pass ``gaussian_filter()``.
  
      Returns:
          cupy.ndarray: The result of the filtering.
  
      .. seealso:: :func:`scipy.ndimage.gaussian_gradient_magnitude`
  
      .. 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.
      """
  
      def derivative(input, axis, output, mode, cval):
          order = [0] * input.ndim
          order[axis] = 1
          return gaussian_filter(
              input, sigma, order, output, mode, cval, **kwargs
          )
  
      return generic_gradient_magnitude(
          input, derivative, 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 20 for calling a global function with example usage: gaussian_gradient_magnitude(input, sigma, output, mode, cval) and returns: generic_gradient_magnitude, gaussian_filter