code: def rdp_data_independent_gaussian(sigma, orders):
      """Computes a data-independent RDP curve for GNMax.
  
      Implementation of Proposition 8.
  
      Args:
        sigma: Standard deviation of Gaussian noise.
        orders: An array_like list of Renyi orders.
  
      Returns:
        Upper bound on RPD for all orders. A scalar if orders is a scalar.
  
      Raises:
        ValueError: If the input is malformed.
      """
      if sigma < 0 or np.any(orders <= 1):  # not defined for alpha=1
          raise ValueError("Inputs are malformed.")
  
      variance = sigma**2
      if np.isscalar(orders):
          return orders / variance
      else:
          return np.atleast_1d(orders) / variance
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from absl import app
  import numpy
  import scipy.stats
label_desc: Use image node_id 5 for calling a global function with example usage: rdp_data_independent_gaussian(sigma, orders) and returns: unknown, unknown