def main(dir_path, time_limit):
output_id_list = []
output_list = []
for i, file_name in enumerate(list(sorted(os.listdir(dir_path)))):
if file_name[-5:] == ".json":
p = Runner()
with open(dir_path + file_name, "r") as file:
data = json.load(file)
p.initialize_from_data(data)
try:
p.auto_run(time_limit=time_limit)
solved_dict = p.output()
for j in solved_dict.keys():
assert len(solved_dict[j]) <= 3
output_id_list.append(f'{file_name[:-5]}_{j}')
output_list.append(" ".join(solved_dict[j]))
except:
for j in range(len(data["test"])):
output_id_list.append(f'{file_name[:-5]}_{j}')
output_list.append("")
res_df = pd.DataFrame({"output_id": output_id_list, "output": output_list})
# print(res_df)
res_df.to_csv("submission.csv", index=False)
def run_local(kbn="training", time_limit=0.2, verbose=True):
total_ac = 0
total_wa = 0
res_list = []
p_list = []
ind_list = []
assert kbn == "training" or kbn == "evaluation"
for ind in range(400):
if kbn == "training":
p = Runner(ind, "train", verbose=verbose)
elif kbn == "evaluation":
p = Runner(ind, "eval", verbose=verbose)
else:
raise ValueError
p.auto_run(time_limit=time_limit)
solved_dict = p.output()
for j in solved_dict.keys():
p_list.append(ind)
ind_list.append(j)
assert len(solved_dict[j]) <= 3
answer_str = p.answer_list[j]
if answer_str in solved_dict[j]:
# print(f'AC: {i, j}')
total_ac += 1
res_list.append(1)
else:
# print(f'WA: {i, j}')
total_wa += 1
res_list.append(0)
pct = 1 - total_ac / (total_ac + total_wa)
print(f'{kbn} done, AC: {total_ac}, total: {total_ac + total_wa}, {pct}')
res_arr = np.concatenate([
np.array(res_list).reshape((-1, 1)),
np.array(p_list).reshape((-1, 1)),
np.array(ind_list).reshape((-1, 1))
],
axis=1)
np.save(f'../local_eval_log/{kbn}-{time_limit}-{pct}', res_arr)
return None
