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Update NATS-Bench (tss version 1.0) and remove the trace of 301

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This commit is contained in:
D-X-Y
2020-09-16 08:28:27 +00:00
parent bd9288f45d
commit 9db28392c2
10 changed files with 169 additions and 249 deletions
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17
exps/NATS-Bench/test-nats-api.py
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@@ -26,7 +26,7 @@ from log_utils import time_string
from models import get_cell_based_tiny_net, CellStructure
def test_api(api, is_301=True):
def test_api(api, sss_or_tss=True):
print('{:} start testing the api : {:}'.format(time_string(), api))
api.clear_params(12)
api.reload(index=12)
@@ -39,7 +39,7 @@ def test_api(api, is_301=True):
info = api.query_by_index(113, 'cifar100')
print('{:}\n'.format(info))
info = api.query_meta_info_by_index(115, '90' if is_301 else '200')
info = api.query_meta_info_by_index(115, '90' if sss_or_tss else '200')
print('{:}\n'.format(info))
for dataset in ['cifar10', 'cifar100', 'ImageNet16-120']:
@@ -48,6 +48,7 @@ def test_api(api, is_301=True):
print('')
params = api.get_net_param(12, 'cifar10', None)
import pdb; pdb.set_trace()
# Obtain the config and create the network
config = api.get_net_config(12, 'cifar10')
print('{:}\n'.format(config))
@@ -74,7 +75,7 @@ def test_api(api, is_301=True):
print('{:}\n'.format(info))
print('{:} finish testing the api : {:}'.format(time_string(), api))
if not is_301:
if not sss_or_tss:
arch_str = '|nor_conv_3x3~0|+|nor_conv_3x3~0|avg_pool_3x3~1|+|skip_connect~0|nor_conv_3x3~1|skip_connect~2|'
matrix = api.str2matrix(arch_str)
print('Compute the adjacency matrix of {:}'.format(arch_str))
@@ -88,13 +89,13 @@ if __name__ == '__main__':
# api201 = create('./output/NATS-Bench-topology/process-FULL', 'topology', fast_mode=True, verbose=True)
for fast_mode in [True, False]:
for verbose in [True, False]:
api201 = create(None, 'tss', fast_mode=fast_mode, verbose=True)
api_nats_tss = create(None, 'tss', fast_mode=fast_mode, verbose=True)
print('{:} create with fast_mode={:} and verbose={:}'.format(time_string(), fast_mode, verbose))
test_api(api201, False)
test_api(api_nats_tss, False)
for fast_mode in [True, False]:
for verbose in [True, False]:
print('{:} create with fast_mode={:} and verbose={:}'.format(time_string(), fast_mode, verbose))
api301 = create(None, 'size', fast_mode=fast_mode, verbose=True)
print('{:} --->>> {:}'.format(time_string(), api301))
test_api(api301, True)
api_nats_sss = create(None, 'size', fast_mode=fast_mode, verbose=True)
print('{:} --->>> {:}'.format(time_string(), api_nats_sss))
test_api(api_nats_sss, True)

129
exps/NATS-Bench/tss-collect-patcher.py Normal file
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@@ -0,0 +1,129 @@
##############################################################################
# NATS-Bench: Benchmarking NAS algorithms for Architecture Topology and Size #
##############################################################################
# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2020.08 #
##############################################################################
# This file is used to re-orangize all checkpoints (created by main-tss.py) #
# into a single benchmark file. Besides, for each trial, we will merge the #
# information of all its trials into a single file. #
# #
# Usage: #
# python exps/NATS-Bench/tss-collect-patcher.py #
##############################################################################
import os, re, sys, time, shutil, random, argparse, collections
import numpy as np
from copy import deepcopy
import torch
from tqdm import tqdm
from pathlib import Path
from collections import defaultdict, OrderedDict
from typing import Dict, Any, Text, List
lib_dir = (Path(__file__).parent / '..' / '..' / 'lib').resolve()
if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir))
from log_utils import AverageMeter, time_string, convert_secs2time
from config_utils import load_config, dict2config
from datasets import get_datasets
from models import CellStructure, get_cell_based_tiny_net, get_search_spaces
from nats_bench import pickle_save, pickle_load, ArchResults, ResultsCount
from procedures import bench_pure_evaluate as pure_evaluate, get_nas_bench_loaders
from utils import get_md5_file
from nas_201_api import NASBench201API
NATS_TSS_BASE_NAME = 'NATS-tss-v1_0' # 2020.08.28
def simplify(save_dir, save_name, nets, total, sup_config):
hps, seeds = ['12', '200'], set()
for hp in hps:
sub_save_dir = save_dir / 'raw-data-{:}'.format(hp)
ckps = sorted(list(sub_save_dir.glob('arch-*-seed-*.pth')))
seed2names = defaultdict(list)
for ckp in ckps:
parts = re.split('-|\.', ckp.name)
seed2names[parts[3]].append(ckp.name)
print('DIR : {:}'.format(sub_save_dir))
nums = []
for seed, xlist in seed2names.items():
seeds.add(seed)
nums.append(len(xlist))
print(' [seed={:}] there are {:} checkpoints.'.format(seed, len(xlist)))
assert len(nets) == total == max(nums), 'there are some missed files : {:} vs {:}'.format(max(nums), total)
print('{:} start simplify the checkpoint.'.format(time_string()))
datasets = ('cifar10-valid', 'cifar10', 'cifar100', 'ImageNet16-120')
# Create the directory to save the processed data
# full_save_dir contains all benchmark files with trained weights.
# simplify_save_dir contains all benchmark files without trained weights.
full_save_dir = save_dir / (save_name + '-FULL')
simple_save_dir = save_dir / (save_name + '-SIMPLIFY')
full_save_dir.mkdir(parents=True, exist_ok=True)
simple_save_dir.mkdir(parents=True, exist_ok=True)
# all data in memory
arch2infos, evaluated_indexes = dict(), set()
end_time, arch_time = time.time(), AverageMeter()
# save the meta information
for index in tqdm(range(total)):
arch_str = nets[index]
hp2info = OrderedDict()
simple_save_path = simple_save_dir / '{:06d}.pickle'.format(index)
arch2infos[index] = pickle_load(simple_save_path)
evaluated_indexes.add(index)
# measure elapsed time
arch_time.update(time.time() - end_time)
end_time = time.time()
need_time = '{:}'.format(convert_secs2time(arch_time.avg * (total-index-1), True))
# print('{:} {:06d}/{:06d} : still need {:}'.format(time_string(), index, total, need_time))
print('{:} {:} done.'.format(time_string(), save_name))
final_infos = {'meta_archs' : nets,
'total_archs': total,
'arch2infos' : arch2infos,
'evaluated_indexes': evaluated_indexes}
save_file_name = save_dir / '{:}.pickle'.format(save_name)
pickle_save(final_infos, str(save_file_name))
# move the benchmark file to a new path
hd5sum = get_md5_file(str(save_file_name) + '.pbz2')
hd5_file_name = save_dir / '{:}-{:}.pickle.pbz2'.format(NATS_TSS_BASE_NAME, hd5sum)
shutil.move(str(save_file_name) + '.pbz2', hd5_file_name)
print('Save {:} / {:} architecture results into {:} -> {:}.'.format(len(evaluated_indexes), total, save_file_name, hd5_file_name))
# move the directory to a new path
hd5_full_save_dir = save_dir / '{:}-{:}-full'.format(NATS_TSS_BASE_NAME, hd5sum)
hd5_simple_save_dir = save_dir / '{:}-{:}-simple'.format(NATS_TSS_BASE_NAME, hd5sum)
shutil.move(full_save_dir, hd5_full_save_dir)
shutil.move(simple_save_dir, hd5_simple_save_dir)
def traverse_net(max_node):
aa_nas_bench_ss = get_search_spaces('cell', 'nats-bench')
archs = CellStructure.gen_all(aa_nas_bench_ss, max_node, False)
print ('There are {:} archs vs {:}.'.format(len(archs), len(aa_nas_bench_ss) ** ((max_node-1)*max_node/2)))
random.seed( 88 ) # please do not change this line for reproducibility
random.shuffle( archs )
assert archs[0 ].tostr() == '|avg_pool_3x3~0|+|nor_conv_1x1~0|skip_connect~1|+|nor_conv_1x1~0|skip_connect~1|skip_connect~2|', 'please check the 0-th architecture : {:}'.format(archs[0])
assert archs[9 ].tostr() == '|avg_pool_3x3~0|+|none~0|none~1|+|skip_connect~0|none~1|nor_conv_3x3~2|', 'please check the 9-th architecture : {:}'.format(archs[9])
assert archs[123].tostr() == '|avg_pool_3x3~0|+|avg_pool_3x3~0|nor_conv_1x1~1|+|none~0|avg_pool_3x3~1|nor_conv_3x3~2|', 'please check the 123-th architecture : {:}'.format(archs[123])
return [x.tostr() for x in archs]
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='NATS-Bench (topology search space)', formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--base_save_dir', type=str, default='./output/NATS-Bench-topology', help='The base-name of folder to save checkpoints and log.')
parser.add_argument('--max_node' , type=int, default=4, help='The maximum node in a cell.')
parser.add_argument('--channel' , type=int, default=16, help='The number of channels.')
parser.add_argument('--num_cells' , type=int, default=5, help='The number of cells in one stage.')
parser.add_argument('--check_N' , type=int, default=15625, help='For safety.')
parser.add_argument('--save_name' , type=str, default='process', help='The save directory.')
args = parser.parse_args()
nets = traverse_net(args.max_node)
if len(nets) != args.check_N:
raise ValueError('Pre-num-check failed : {:} vs {:}'.format(len(nets), args.check_N))
save_dir = Path(args.base_save_dir)
simplify(save_dir, args.save_name, nets, args.check_N, {'name': 'infer.tiny', 'channel': args.channel, 'num_cells': args.num_cells})

3
exps/NATS-Bench/tss-collect.py
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@@ -10,7 +10,7 @@
# Usage: #
# python exps/NATS-Bench/tss-collect.py #
##############################################################################
import os, re, sys, time, random, argparse, collections
import os, re, sys, time, shutil, random, argparse, collections
import numpy as np
from copy import deepcopy
import torch
@@ -26,6 +26,7 @@ from datasets import get_datasets
from models import CellStructure, get_cell_based_tiny_net, get_search_spaces
from nats_bench import pickle_save, pickle_load, ArchResults, ResultsCount
from procedures import bench_pure_evaluate as pure_evaluate, get_nas_bench_loaders
from utils import get_md5_file
from nas_201_api import NASBench201API