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)
