############################################################### # NAS-Bench-201, ICLR 2020 (https://arxiv.org/abs/2001.00326) # ############################################################### # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2020.01 # ############################################################### # Usage: python exps/NAS-Bench-201/xshape-file.py --mode check ############################################################### import os, sys, time, torch, argparse from typing import List, Text, Dict, Any from tqdm import tqdm from collections import defaultdict from copy import deepcopy from pathlib import Path lib_dir = (Path(__file__).parent / '..' / '..' / 'lib').resolve() if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir)) from config_utils import dict2config, load_config from procedures import bench_evaluate_for_seed from procedures import get_machine_info from datasets import get_datasets from log_utils import Logger, AverageMeter, time_string, convert_secs2time def obtain_valid_ckp(save_dir: Text, total: int): possible_seeds = [777, 888] seed2ckps = defaultdict(list) miss2ckps = defaultdict(list) for i in range(total): for seed in possible_seeds: path = os.path.join(save_dir, 'arch-{:06d}-seed-{:04d}.pth'.format(i, seed)) if os.path.exists(path): seed2ckps[seed].append(i) else: miss2ckps[seed].append(i) """ ckps = [x for x in save_dir.glob('arch-{:06d}-seed-*.pth'.format(i))] for ckp in ckps: seed = ckp.name.split('-seed-')[-1].split('.pth')[0] seed2ckps[int(seed)].append(i) """ for seed, xlist in seed2ckps.items(): print('[{:}] [seed={:}] has {:}/{:}'.format(save_dir, seed, len(xlist), total)) return dict(seed2ckps), dict(miss2ckps) if __name__ == '__main__': parser = argparse.ArgumentParser(description='NAS-Bench-X', formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('--mode', type=str, required=True, choices=['check', 'copy'], help='The script mode.') parser.add_argument('--save_dir', type=str, default='output/NAS-BENCH-202', help='Folder to save checkpoints and log.') parser.add_argument('--check_N', type=int, default=32768, help='For safety.') # use for train the model args = parser.parse_args() possible_configs = ['01', '12', '90'] if args.mode == 'check': for config in possible_configs: cur_save_dir = '{:}/raw-data-{:}'.format(args.save_dir, config) seed2ckps, miss2ckps = obtain_valid_ckp(cur_save_dir, args.check_N) torch.save(dict(seed2ckps=seed2ckps, miss2ckps=miss2ckps), '{:}/meta-{:}.pth'.format(args.save_dir, config))