def main():
prediction_file = os.path.join(output_path, "cppnc",
sys.argv[1] + ".score")
info_dir = os.path.join(output_path, "cppnc", sys.argv[2])
score_d = summarize_score(info_dir, prediction_file)
map_score = eval_map("train", score_d)
print(map_score)
def main():
info_dir = "/mnt/nfs/work3/youngwookim/job_man/ppnc_50_pers_val"
#prediction_file = os.path.join(output_path, "ppnc_50_val_prediction")
prediction_file = os.path.join(output_path, "ppnc_pred_100K")
score_d = summarize_score(info_dir, prediction_file)
map_score = eval_map("train", score_d)
print(map_score)
def main():
save_name = sys.argv[1]
out_dir = os.path.join(output_path, "cppnc")
exist_or_mkdir(out_dir)
info_file_path = os.path.join(out_dir, save_name + ".info")
pred_file_path = os.path.join(out_dir, save_name + ".score")
score_d = summarize_score(info_file_path, pred_file_path)
map_score = eval_map("dev", score_d, False)
print(map_score)
def main():
save_name = sys.argv[1]
out_dir = os.path.join(output_path, "cppnc")
exist_or_mkdir(out_dir)
info_file_path = os.path.join(out_dir, sys.argv[2])
pred_file_path = os.path.join(out_dir, save_name + ".score")
debug = False
split = "dev"
if len(sys.argv) > 3:
if sys.argv[3] == "debug":
debug = True
if len(sys.argv) > 4:
if sys.argv[4] == "train":
split = "train"
score_d = summarize_score(info_file_path, pred_file_path)
map_score = eval_map(split, score_d, debug)
print(map_score)
def bert_eval():
pc_score_d: Dict[CPID,
float] = load_from_pickle("pc_bert_baseline_score_d")
score_d: Dict[CPIDPair, float] = {
CPID_to_CPIDPair(k): v
for k, v in pc_score_d.items()
}
target_cids = [
628, 286, 591, 664, 842, 598, 707, 457, 166, 864, 493, 807, 609, 515,
641, 116, 496, 608, 24, 694, 684, 722, 572, 676, 160, 575, 514, 960,
927, 463, 838, 921, 638, 34, 835, 194, 464, 159, 595, 812, 25, 1004
]
selected_score_d = {
k: v
for k, v in score_d.items() if k[0] in target_cids
}
print("selected_score_d :", len(selected_score_d))
map_score = eval_map("dev", score_d, True)
print(map_score)
def main():
info_dir = "/mnt/nfs/work3/youngwookim/job_man/cppnc_val_info"
prediction_file = os.path.join(output_path, "cppnc_pred")
score_d = summarize_score(info_dir, prediction_file)
map_score = eval_map("train", score_d)
print(map_score)
