def get_random_topology(num_model, output_file_name):
data_dict = implement_topology(num_model)
data_dict = fix_dict(data_dict)
output_file_name = save_topology_in_csv(output_file_name, data_dict)
print("\nCreate file of random topology named: ", output_file_name,
" sucessfull!\n")
return output_file_name
def main():
file_name = "fixed_model_dict.csv"
file_name = "COMPLETE_CIFAR10.csv"
data = get_data_from_csv(file_name)
data = format_data_without_header(data)
print(data)
output_file = "bad_model.csv"
accuracy_threshold = 0.7
# loss_threshold = 1.0
bad_model = get_bad_topology(data, accuracy_threshold, "accuracy")
# bad_model = get_bad_topology(data,loss_threshold,"loss")
print(bad_model)
bad_model_file = save_topology_in_csv(output_file, bad_model)
def main():
FILE_NAME = "fixed_model_dict.csv"
FILE_NAME = "COMPLETE_CIFAR10.csv"
data = get_data_from_csv(FILE_NAME)
data = format_data_without_header(data)
OUTPUT_FILE = "bad_model.csv"
accuracy_threshold = 0.7
bad_model = get_bad_topology(data, accuracy_threshold, "accuracy")
# loss_threshold = 1.0
# bad_model = get_bad_topology(data,loss_threshold,"loss")
bad_model_file = save_topology_in_csv(OUTPUT_FILE, bad_model)
print("Create file for bad topology: ", bad_model_file, " successfully!!")
def main():
CURRENT_DIR = os.getcwd()
INPUT_FOLDER_NAME = 'CIFAR_DICT'
INPUT_PATH = CURRENT_DIR +'/'+INPUT_FOLDER_NAME
OUTPUT_FILE_NAME = "COMPLETE_DICT.csv"
OUTPUT_FILE_PATH = CURRENT_DIR + '/'+ OUTPUT_FILE_NAME
INDEX_ACCURACY = -2
INDEX_LOSS = -1
SORTING_INDEX = INDEX_ACCURACY
# SORTING_INDEX = INDEX_LOSS
data = combine_file(INPUT_PATH, OUTPUT_FILE_PATH)
data = sort_data(data, SORTING_INDEX)
result_file_name = save_topology_in_csv(OUTPUT_FILE_PATH,data)
print("Combine file from: ",INPUT_PATH, " : and get ", OUTPUT_FILE_NAME, " successfully!")
def get_random_topology(num_model, output_file_name):
data_dict = implement_topology(num_model)
data_dict = fix_dict(data_dict)
output_file_name = save_topology_in_csv(output_file_name, data_dict)
return output_file_name