def __initialize_population(self):
    print('\n\n===== Evaluating initial random population =====')
    start_initial_population_time = time.time()
    while (len(self.population) < self.population_size):
        individual = self._generate_random_individual()
        ind_actions = self._construct_action([individual])
        gnn = self.form_gnn_info(ind_actions[0])
        (_, ind_acc) = self.submodel_manager.train(gnn, format=self.args.format)
        print('individual:', individual, ' val_score:', ind_acc)
        self.accuracies.append(ind_acc)
        self.population.append(individual)
    end_initial_pop_time = time.time()
    self.init_time = (end_initial_pop_time - start_initial_population_time)
    print(('Time elapsed initializing population: ' + str(self.init_time)))
    print('===== Evaluating initial random population DONE ====')
def __initialize_population(self):
    print('\n\n===== Evaluating initial random population =====')
    start_initial_population_time = time.time()
    while (len(self.population) < self.population_size):
        individual = self._generate_random_individual()
        ind_actions = self._construct_action([individual])
        gnn = self.form_gnn_info(ind_actions[0])
        (_, ind_acc) = self.submodel_manager.train(gnn, format=self.args.format)
        print('individual:', individual, ' val_score:', ind_acc)
        self.accuracies.append(ind_acc)
        self.population.append(individual)
    end_initial_pop_time = time.time()
    self.init_time = (end_initial_pop_time - start_initial_population_time)
    print(('Time elapsed initializing population: ' + str(self.init_time)))
    print('===== Evaluating initial random population DONE ====')