107 lines
4.2 KiB
Python
107 lines
4.2 KiB
Python
##############################################################################
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# NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size #
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##############################################################################
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# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2020.08 #
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##############################################################################
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# Usage: python exps/NATS-Bench/sss-file-manager.py --mode check #
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##############################################################################
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import os, sys, time, torch, argparse
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from typing import List, Text, Dict, Any
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from shutil import copyfile
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from collections import defaultdict
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from copy import deepcopy
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from pathlib import Path
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lib_dir = (Path(__file__).parent / ".." / ".." / "lib").resolve()
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if str(lib_dir) not in sys.path:
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sys.path.insert(0, str(lib_dir))
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from config_utils import dict2config, load_config
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from procedures import bench_evaluate_for_seed
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from procedures import get_machine_info
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from datasets import get_datasets
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from log_utils import Logger, AverageMeter, time_string, convert_secs2time
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def obtain_valid_ckp(save_dir: Text, total: int):
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possible_seeds = [777, 888, 999]
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seed2ckps = defaultdict(list)
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miss2ckps = defaultdict(list)
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for i in range(total):
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for seed in possible_seeds:
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path = os.path.join(save_dir, "arch-{:06d}-seed-{:04d}.pth".format(i, seed))
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if os.path.exists(path):
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seed2ckps[seed].append(i)
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else:
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miss2ckps[seed].append(i)
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for seed, xlist in seed2ckps.items():
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print(
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"[{:}] [seed={:}] has {:5d}/{:5d} | miss {:5d}/{:5d}".format(
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save_dir, seed, len(xlist), total, total - len(xlist), total
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)
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)
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return dict(seed2ckps), dict(miss2ckps)
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def copy_data(source_dir, target_dir, meta_path):
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target_dir = Path(target_dir)
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target_dir.mkdir(parents=True, exist_ok=True)
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miss2ckps = torch.load(meta_path)["miss2ckps"]
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s2t = {}
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for seed, xlist in miss2ckps.items():
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for i in xlist:
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file_name = "arch-{:06d}-seed-{:04d}.pth".format(i, seed)
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source_path = os.path.join(source_dir, file_name)
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target_path = os.path.join(target_dir, file_name)
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if os.path.exists(source_path):
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s2t[source_path] = target_path
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print(
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"Map from {:} to {:}, find {:} missed ckps.".format(
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source_dir, target_dir, len(s2t)
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)
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)
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for s, t in s2t.items():
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copyfile(s, t)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="NATS-Bench (size search space) file manager.",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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)
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parser.add_argument(
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"--mode",
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type=str,
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required=True,
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choices=["check", "copy"],
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help="The script mode.",
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)
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parser.add_argument(
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"--save_dir",
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type=str,
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default="output/NATS-Bench-size",
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help="Folder to save checkpoints and log.",
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)
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parser.add_argument("--check_N", type=int, default=32768, help="For safety.")
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# use for train the model
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args = parser.parse_args()
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possible_configs = ["01", "12", "90"]
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if args.mode == "check":
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for config in possible_configs:
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cur_save_dir = "{:}/raw-data-{:}".format(args.save_dir, config)
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seed2ckps, miss2ckps = obtain_valid_ckp(cur_save_dir, args.check_N)
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torch.save(
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dict(seed2ckps=seed2ckps, miss2ckps=miss2ckps),
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"{:}/meta-{:}.pth".format(args.save_dir, config),
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)
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elif args.mode == "copy":
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for config in possible_configs:
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cur_save_dir = "{:}/raw-data-{:}".format(args.save_dir, config)
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cur_copy_dir = "{:}/copy-{:}".format(args.save_dir, config)
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cur_meta_path = "{:}/meta-{:}.pth".format(args.save_dir, config)
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if os.path.exists(cur_meta_path):
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copy_data(cur_save_dir, cur_copy_dir, cur_meta_path)
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else:
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print("Do not find : {:}".format(cur_meta_path))
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else:
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raise ValueError("invalid mode : {:}".format(args.mode))
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