code: def zscore(a, axis=0, ddof=0, nan_policy="propagate"):
      """Compute the z-score.
  
      Compute the z-score of each value in the sample, relative to
      the sample mean and standard deviation.
  
      Parameters
      ----------
      a : array-like
          An array like object containing the sample data
      axis : int or None, optional
          Axis along which to operate. Default is 0. If None,
          compute over the whole arrsy `a`
      ddof : int, optional
          Degrees of freedom correction in the calculation of the
          standard deviation. Default is 0
      nan_policy : {'propagate', 'raise', 'omit'}, optional
          Defines how to handle when input contains nan. 'propagate'
          returns nan, 'raise' throws an error, 'omit' performs
          the calculations ignoring nan values. Default is
          'propagate'. Note that when the value is 'omit',
          nans in the input also propagate to the output,
          but they do not affect the z-scores computed
          for the non-nan values
  
      Returns
      -------
      zscore : array-like
          The z-scores, standardized by mean and standard deviation of
          input array `a`
  
      """
  
      return zmap(a, a, axis=axis, ddof=ddof, nan_policy=nan_policy)
  
imports: import cupy
label_desc: Use image node_id 3 for calling a global function with example usage: zscore(a, axis, ddof, nan_policy) and returns: zmap