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)