code: def chi_square_distance_numpy(object1, object2):
      """!
      @brief Calculate Chi square distance between two vectors using numpy.
  
      @param[in] object1 (array_like): The first vector.
      @param[in] object2 (array_like): The second vector.
  
      @return (float) Chi square distance between two objects.
  
      """
      with numpy.errstate(divide="ignore", invalid="ignore"):
          result = numpy.divide(
              numpy.power(object1 - object2, 2),
              numpy.abs(object1) + numpy.abs(object2),
          )
  
      if len(result.shape) > 1:
          return numpy.sum(numpy.nan_to_num(result), axis=1).T
      else:
          return numpy.sum(numpy.nan_to_num(result))
  
imports: import numpy
  from enum import IntEnum
label_desc: Use image node_id 14 for calling a global function with example usage: chi_square_distance_numpy(object1, object2) and returns: numpy, numpy