importpygadimportnumpyfunction_inputs= [4,-2,3.5,5,-11,-4.7]desired_output=44deffitness_func(ga_instance,solution,solution_idx):output=numpy.sum(solution*function_inputs)fitness=1.0/ (numpy.abs(output-desired_output)+0.000001)returnfitnessga_instance=pygad.GA(num_generations=10,num_parents_mating=10,sol_per_pop=20,num_genes=len(function_inputs),fitness_func=fitness_func,suppress_warnings=True)ga_instance.run()# Saving the GA instance.filename='genetic'ga_instance.save(filename=filename)# Loading the saved GA instance.loaded_ga_instance=pygad.load(filename=filename)loaded_ga_instance.plot_fitness()