code: def argrelmax(data, axis=0, order=1, mode="clip"):
      """
      Calculate the relative maxima of `data`.
  
      Parameters
      ----------
      data : ndarray
          Array in which to find the relative maxima.
      axis : int, optional
          Axis over which to select from `data`.  Default is 0.
      order : int, optional
          How many points on each side to use for the comparison
          to consider ``comparator(n, n+x)`` to be True.
      mode : str, optional
          How the edges of the vector are treated.
          Available options are 'wrap' (wrap around) or 'clip' (treat overflow
          as the same as the last (or first) element).
          Default 'clip'. See cupy.take.
  
      Returns
      -------
      extrema : tuple of ndarrays
          Indices of the maxima in arrays of integers.  ``extrema[k]`` is
          the array of indices of axis `k` of `data`.  Note that the
          return value is a tuple even when `data` is one-dimensional.
  
      See Also
      --------
      argrelextrema, argrelmin, find_peaks
  
      Notes
      -----
      This function uses `argrelextrema` with cupy.greater as comparator.
      Therefore it requires a strict inequality on both sides of a value to
      consider it a maximum. This means flat maxima (more than one sample wide)
      are not detected. In case of one-dimensional `data` `find_peaks` can be
      used to detect all local maxima, including flat ones.
  
      Examples
      --------
      >>> from cupyx.scipy.signal import argrelmax
      >>> import cupy
      >>> x = cupy.array([2, 1, 2, 3, 2, 0, 1, 0])
      >>> argrelmax(x)
      (array([3, 6]),)
      >>> y = cupy.array([[1, 2, 1, 2],
      ...               [2, 2, 0, 0],
      ...               [5, 3, 4, 4]])
      ...
      >>> argrelmax(y, axis=1)
      (array([0]), array([1]))
      """
      data = cupy.asarray(data)
      return argrelextrema(data, cupy.greater, axis, order, mode)
  
imports: import math
  import cupy
  from cupy._core._scalar import get_typename
  from cupy_backends.cuda.api import runtime
  from cupyx import jit
label_desc: Use image node_id 20 for calling a global function with example usage: argrelmax(data, axis, order, mode) and returns: argrelextrema