reliability_setting)][iteration - 1] = calc_expected_accuracy( ResiliNet_failout_rate_fixed, no_information_flow_map, reliability_setting, output_list, data=data, ) # clear session so that model will recycled back into memory K.clear_session() gc.collect() del ResiliNet_failout_rate_fixed # calculate average accuracies for variable failout rate for reliability_setting in reliability_settings: ResiliNet_failout_rate_acc = average( output["Variable Failout 1x"][str(reliability_setting)]) output_list.append( str(reliability_setting) + " Variable Failout 1x: " + str(ResiliNet_failout_rate_acc) + "\n") print(reliability_setting, "Variable Failout 1x:", ResiliNet_failout_rate_acc) ResiliNet_failout_rate_std = np.std( output["Variable Failout 1x"][str(reliability_setting)], ddof=1) output_list.append( str(reliability_setting) + " Variable Failout 1x std: " + str(ResiliNet_failout_rate_std) + "\n") print( str(reliability_setting), " Variable Failout 1x std:", ResiliNet_failout_rate_std,
no_information_flow_map[tuple( skip_hyperconnection_configuration)], reliability_setting, skip_hyperconnection_configuration, output_list, data, ) K.clear_session() gc.collect() del weight_sesitivity for reliability_setting in reliability_settings: output_list.append(str(reliability_setting) + "\n") for skip_hyperconnection_configuration in skip_hyperconnection_configurations: output_list.append(str(skip_hyperconnection_configuration) + "\n") acc = average(output[model_name][str(reliability_setting)][str( skip_hyperconnection_configuration)]) std = np.std( output[model_name][str(reliability_setting)][str( skip_hyperconnection_configuration)], ddof=1, ) # write to output list output_list.append( str(reliability_setting) + " " + str(skip_hyperconnection_configuration) + " accuracy: " + str(acc) + "\n") print( str(reliability_setting), str(skip_hyperconnection_configuration), "accuracy:", acc,
Vanilla, Vanilla_no_information_flow_map, reliability_setting, output_list, data, ) # clear session so that model will recycled back into memory K.clear_session() gc.collect() del DFG del ResiliNet del Vanilla # calculate average accuracies from all expected accuracies for reliability_setting in reliability_settings: ResiliNet_acc = average(output["ResiliNet"][str(reliability_setting)]) DFG_acc = average(output["DFG"][str(reliability_setting)]) Vanilla_acc = average(output["Vanilla"][str(reliability_setting)]) output_list.append( str(reliability_setting) + " ResiliNet accuracy: " + str(ResiliNet_acc) + "\n") output_list.append( str(reliability_setting) + " DFG accuracy: " + str(DFG_acc) + "\n") output_list.append( str(reliability_setting) + " Vanilla accuracy: " + str(Vanilla_acc) + "\n") print(str(reliability_setting), "ResiliNet accuracy:", ResiliNet_acc) print(str(reliability_setting), "DFG accuracy:", DFG_acc) print(str(reliability_setting), "Vanilla accuracy:", Vanilla_acc)
1] = calc_expected_accuracy( hyperconnection_weight, no_information_flow_map, reliability_setting, output_list, data=data, ) # clear session so that model will recycled back into memory K.clear_session() gc.collect() del hyperconnection_weight # calculate average accuracies for reliability_setting in reliability_settings: for weight_scheme in weight_schemes: hyperconnection_weight_acc = average( output[model_name][weight_scheme][str(reliability_setting)]) output_list.append( str(reliability_setting) + str(weight_scheme) + " " + model_name + ": " + str(hyperconnection_weight_acc) + "\n") print( str(reliability_setting), weight_scheme, model_name, ":", hyperconnection_weight_acc, ) hyperconnection_weight_std = np.std( output[model_name][weight_scheme][str(reliability_setting)], ddof=1) output_list.append(
model, no_information_flow_map, reliability_setting, output_list, data=data, ) # clear session so that model will recycled back into memory K.clear_session() gc.collect() del model for reliability_setting in reliability_settings: for weight_scheme in weight_schemes: output_list.append( str(reliability_setting) + str(weight_scheme) + "\n") acc = average( output[model_name][weight_scheme][str(reliability_setting)]) output_list.append( str(reliability_setting) + str(weight_scheme) + str(acc) + "\n") print(str(reliability_setting), weight_scheme, acc) std = np.std( output[model_name][weight_scheme][str(reliability_setting)], ddof=1) output_list.append( str(reliability_setting) + str(weight_scheme) + str(std) + "\n") print(str(reliability_setting), weight_scheme, std) save_output(output_name, output_list) print(output)