|
import mmengine |
|
import os |
|
import argparse |
|
import numpy as np |
|
|
|
|
|
def parse_args(): |
|
parser = argparse.ArgumentParser() |
|
parser.add_argument('--result_path', type=str) |
|
args = parser.parse_args() |
|
return args |
|
|
|
def convert_results(result_path): |
|
result = mmengine.load(result_path) |
|
instruct_list = [(result['instruct_json']['json_format_metric'] + result['instruct_json']['json_args_em_metric']) / 2, \ |
|
(result['instruct_json']['string_format_metric'] + result['instruct_json']['string_args_em_metric']) / 2] |
|
plan_list = [result['plan_str']['f1_score'], result['plan_json']['f1_score']] |
|
reason_list = [result['reason_str']['thought'], result['rru_json']['thought']] |
|
retrieve_list = [result['retrieve_str']['name'], result['rru_json']['name']] |
|
understand_list = [result['understand_str']['args'], result['rru_json']['args']] |
|
review_list = [result['review_str']['review_quality'], result['review_str']['review_quality']] |
|
|
|
final_score = [np.mean(instruct_list), np.mean(plan_list), np.mean(reason_list), \ |
|
np.mean(retrieve_list), np.mean(understand_list), np.mean(review_list)] |
|
overall = np.mean(final_score) |
|
final_score.insert(0, overall) |
|
name_list = ['Overall', 'Instruct', 'Plan', 'Reason', 'Retrieve', 'Understand', 'Review'] |
|
print("Cut Paste Results: ", np.array(final_score) * 100) |
|
for i in range(len(name_list)): |
|
print("%s: %.1f" % (name_list[i], final_score[i]*100), end='\t') |
|
|
|
|
|
if __name__ == '__main__': |
|
args = parse_args() |
|
convert_results(args.result_path) |
|
|
