code: def multigammaln(a, d):
      r"""Returns the log of multivariate gamma, also sometimes called the
      generalized gamma.
  
      Parameters
      ----------
      a : cupy.ndarray
          The multivariate gamma is computed for each item of `a`.
      d : int
          The dimension of the space of integration.
  
      Returns
      -------
      res : ndarray
          The values of the log multivariate gamma at the given points `a`.
  
      See Also
      --------
      :func:`scipy.special.multigammaln`
  
      """
      if not cupy.isscalar(d) or (math.floor(d) != d):
          raise ValueError("d should be a positive integer (dimension)")
      if cupy.isscalar(a):
          a = cupy.asarray(a, dtype=float)
      if int(cupy.any(a <= 0.5 * (d - 1))):
          raise ValueError("condition a > 0.5 * (d-1) not met")
      res = (d * (d - 1) * 0.25) * math.log(math.pi)
      gam0 = gammaln(a)
      if a.dtype.kind != "f":
          # make sure all integer dtypes do the summation with float64
          gam0 = gam0.astype(cupy.float64)
      res = res + gam0
      for j in range(2, d + 1):
          res += gammaln(a - (j - 1.0) / 2)
      return res
  
label_desc: Use image node_id 1 for calling a global function with example usage: multigammaln(a, d) and returns: res