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This commit is contained in:
D-X-Y
2020-07-30 13:07:11 +00:00
parent df45e68366
commit 6061d74631
21 changed files with 1336 additions and 126 deletions
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2
exps/experimental/example-nas-bench.py
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@@ -16,7 +16,7 @@ matplotlib.use('agg')
import matplotlib.pyplot as plt
lib_dir = (Path(__file__).parent / '..' / '..' / 'lib').resolve()
if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir))
from nas_201_api import NASBench201API, NASBench301API
from nas_201_api import NASBench201API
from log_utils import time_string
from models import get_cell_based_tiny_net
from utils import weight_watcher

14
exps/experimental/test-ww-bench.py
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@@ -3,9 +3,6 @@
###########################################################################################################################################################
# Before run these commands, the files must be properly put.
#
# python exps/experimental/test-ww-bench.py --base_path $HOME/.torch/NAS-Bench-201-v1_0-e61699
# python exps/experimental/test-ww-bench.py --base_path $HOME/.torch/NAS-Bench-201-v1_1-096897 --dataset cifar10-valid --use_12 1 --use_valid 1
# CUDA_VISIBLE_DEVICES='' OMP_NUM_THREADS=4 python exps/experimental/test-ww-bench.py --base_path $HOME/.torch/NAS-Bench-201-v1_1-096897 --dataset cifar10
# CUDA_VISIBLE_DEVICES='' OMP_NUM_THREADS=4 python exps/experimental/test-ww-bench.py --search_space sss --base_path $HOME/.torch/NAS-Bench-301-v1_0 --dataset cifar10
# CUDA_VISIBLE_DEVICES='' OMP_NUM_THREADS=4 python exps/experimental/test-ww-bench.py --search_space sss --base_path $HOME/.torch/NAS-Bench-301-v1_0 --dataset cifar100
# CUDA_VISIBLE_DEVICES='' OMP_NUM_THREADS=4 python exps/experimental/test-ww-bench.py --search_space sss --base_path $HOME/.torch/NAS-Bench-301-v1_0 --dataset ImageNet16-120
@@ -22,8 +19,8 @@ matplotlib.use('agg')
import matplotlib.pyplot as plt
lib_dir = (Path(__file__).parent / '..' / '..' / 'lib').resolve()
if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir))
from nas_201_api import NASBench201API, NASBench301API
from log_utils import time_string
from nats_bench import create
from models import get_cell_based_tiny_net
from utils import weight_watcher
@@ -52,8 +49,8 @@ def evaluate(api, weight_dir, data: str):
# compute the weight watcher results
config = api.get_net_config(arch_index, data)
net = get_cell_based_tiny_net(config)
meta_info = api.query_meta_info_by_index(arch_index, hp='200' if isinstance(api, NASBench201API) else '90')
params = meta_info.get_net_param(data, 888 if isinstance(api, NASBench201API) else 777)
meta_info = api.query_meta_info_by_index(arch_index, hp='200' if api.search_space_name == 'topology' else '90')
params = meta_info.get_net_param(data, 888 if api.search_space_name == 'topology' else 777)
with torch.no_grad():
net.load_state_dict(params)
_, summary = weight_watcher.analyze(net, alphas=False)
@@ -70,7 +67,7 @@ def evaluate(api, weight_dir, data: str):
ok += 1
norms.append(cur_norm)
# query the accuracy
info = meta_info.get_metrics(data, 'ori-test', iepoch=None, is_random=888 if isinstance(api, NASBench201API) else 777)
info = meta_info.get_metrics(data, 'ori-test', iepoch=None, is_random=888 if api.search_space_name == 'topology' else 777)
accuracies.append(info['accuracy'])
del net, meta_info
# print the information
@@ -81,9 +78,8 @@ def evaluate(api, weight_dir, data: str):
def main(search_space, meta_file: str, weight_dir, save_dir, xdata):
API = NASBench201API if search_space == 'tss' else NASBench301API
save_dir.mkdir(parents=True, exist_ok=True)
api = API(meta_file, verbose=False)
api = create(meta_file, search_space, verbose=False)
datasets = ['cifar10-valid', 'cifar10', 'cifar100', 'ImageNet16-120']
print(time_string() + ' ' + '='*50)
for data in datasets:

28
exps/experimental/vis-bench-algos.py → exps/experimental/vis-nats-bench-algos.py
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@@ -3,8 +3,8 @@
###############################################################
# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2020.06 #
###############################################################
# Usage: python exps/experimental/vis-bench-algos.py --search_space tss
# Usage: python exps/experimental/vis-bench-algos.py --search_space sss
# Usage: python exps/experimental/vis-nats-bench-algos.py --search_space tss
# Usage: python exps/experimental/vis-nats-bench-algos.py --search_space sss
###############################################################
import os, gc, sys, time, torch, argparse
import numpy as np
@@ -22,7 +22,7 @@ import matplotlib.ticker as ticker
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 nas_201_api import NASBench201API, NASBench301API
from nats_bench import create
from log_utils import time_string
@@ -48,18 +48,19 @@ def fetch_data(root_dir='./output/search', search_space='tss', dataset=None):
def query_performance(api, data, dataset, ticket):
results, is_301 = [], isinstance(api, NASBench301API)
results, is_size_space = [], api.search_space_name == 'size'
for i, info in data.items():
time_w_arch = sorted(info['time_w_arch'], key=lambda x: abs(x[0]-ticket))
time_a, arch_a = time_w_arch[0]
time_b, arch_b = time_w_arch[1]
info_a = api.get_more_info(arch_a, dataset=dataset, hp=90 if is_301 else 200, is_random=False)
info_b = api.get_more_info(arch_b, dataset=dataset, hp=90 if is_301 else 200, is_random=False)
info_a = api.get_more_info(arch_a, dataset=dataset, hp=90 if is_size_space else 200, is_random=False)
info_b = api.get_more_info(arch_b, dataset=dataset, hp=90 if is_size_space else 200, is_random=False)
accuracy_a, accuracy_b = info_a['test-accuracy'], info_b['test-accuracy']
interplate = (time_b-ticket) / (time_b-time_a) * accuracy_a + (ticket-time_a) / (time_b-time_a) * accuracy_b
results.append(interplate)
return sum(results) / len(results)
y_min_s = {('cifar10', 'tss'): 90,
('cifar10', 'sss'): 92,
('cifar100', 'tss'): 65,
@@ -74,6 +75,10 @@ y_max_s = {('cifar10', 'tss'): 94.5,
('ImageNet16-120', 'tss'): 44,
('ImageNet16-120', 'sss'): 46}
name2label = {'cifar10': 'CIFAR-10',
'cifar100': 'CIFAR-100',
'ImageNet16-120': 'ImageNet-16-120'}
def visualize_curve(api, vis_save_dir, search_space, max_time):
vis_save_dir = vis_save_dir.resolve()
vis_save_dir.mkdir(parents=True, exist_ok=True)
@@ -99,8 +104,8 @@ def visualize_curve(api, vis_save_dir, search_space, max_time):
alg2accuracies[alg] = accuracies
ax.plot([x/100 for x in time_tickets], accuracies, c=colors[idx], label='{:}'.format(alg))
ax.set_xlabel('Estimated wall-clock time (1e2 seconds)', fontsize=LabelSize)
ax.set_ylabel('Test accuracy on {:}'.format(dataset), fontsize=LabelSize)
ax.set_title('Searching results on {:}'.format(dataset), fontsize=LabelSize+4)
ax.set_ylabel('Test accuracy on {:}'.format(name2label[dataset]), fontsize=LabelSize)
ax.set_title('Searching results on {:}'.format(name2label[dataset]), fontsize=LabelSize+4)
ax.legend(loc=4, fontsize=LegendFontsize)
fig, axs = plt.subplots(1, 3, figsize=figsize)
@@ -123,10 +128,5 @@ if __name__ == '__main__':
save_dir = Path(args.save_dir)
if args.search_space == 'tss':
api = NASBench201API(verbose=False)
elif args.search_space == 'sss':
api = NASBench301API(verbose=False)
else:
raise ValueError('Invalid search space : {:}'.format(args.search_space))
api = create(None, args.search_space, verbose=False)
visualize_curve(api, save_dir, args.search_space, args.max_time)

30
exps/experimental/vis-bench-ws.py → exps/experimental/vis-nats-bench-ws.py
View File

@@ -3,8 +3,8 @@
###############################################################
# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2020.06 #
###############################################################
# Usage: python exps/experimental/vis-bench-ws.py --search_space tss
# Usage: python exps/experimental/vis-bench-ws.py --search_space sss
# Usage: python exps/experimental/vis-nats-bench-ws.py --search_space tss
# Usage: python exps/experimental/vis-nats-bench-ws.py --search_space sss
###############################################################
import os, gc, sys, time, torch, argparse
import numpy as np
@@ -22,15 +22,16 @@ import matplotlib.ticker as ticker
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 nas_201_api import NASBench201API, NASBench301API
from nats_bench import create
from log_utils import time_string
def fetch_data(root_dir='./output/search', search_space='tss', dataset=None):
ss_dir = '{:}-{:}'.format(root_dir, search_space)
alg2name, alg2path = OrderedDict(), OrderedDict()
seeds = [777, 888, 999]
print('\n[fetch data] from {:} on {:}'.format(search_space, dataset))
if search_space == 'tss':
seeds = [777]
alg2name['GDAS'] = 'gdas-affine0_BN0-None'
alg2name['RSPS'] = 'random-affine0_BN0-None'
alg2name['DARTS (1st)'] = 'darts-v1-affine0_BN0-None'
@@ -38,7 +39,6 @@ def fetch_data(root_dir='./output/search', search_space='tss', dataset=None):
alg2name['ENAS'] = 'enas-affine0_BN0-None'
alg2name['SETN'] = 'setn-affine0_BN0-None'
else:
seeds = [777, 888, 999]
alg2name['TAS'] = 'tas-affine0_BN0'
alg2name['FBNetV2'] = 'fbv2-affine0_BN0'
alg2name['TuNAS'] = 'tunas-affine0_BN0'
@@ -46,13 +46,19 @@ def fetch_data(root_dir='./output/search', search_space='tss', dataset=None):
alg2path[alg] = os.path.join(ss_dir, dataset, name, 'seed-{:}-last-info.pth')
alg2data = OrderedDict()
for alg, path in alg2path.items():
alg2data[alg] = []
alg2data[alg], ok_num = [], 0
for seed in seeds:
xpath = path.format(seed)
assert os.path.isfile(xpath), 'invalid path : {:}'.format(xpath)
if os.path.isfile(xpath):
ok_num += 1
else:
print('This is an invalid path : {:}'.format(xpath))
continue
data = torch.load(xpath, map_location=torch.device('cpu'))
data = torch.load(data['last_checkpoint'], map_location=torch.device('cpu'))
alg2data[alg].append(data['genotypes'])
print('This algorithm : {:} has {:} valid ckps.'.format(alg, ok_num))
assert ok_num > 0, 'Must have at least 1 valid ckps.'
return alg2data
@@ -95,7 +101,7 @@ def visualize_curve(api, vis_save_dir, search_space):
for iepoch in range(epochs+1):
structures, accs = [_[iepoch-1] for _ in data], []
for structure in structures:
info = api.get_more_info(structure, dataset=dataset, hp=90 if isinstance(api, NASBench301API) else 200, is_random=False)
info = api.get_more_info(structure, dataset=dataset, hp=90 if api.search_space_name == 'size' else 200, is_random=False)
accs.append(info['test-accuracy'])
accuracies.append(sum(accs)/len(accs))
xs.append(iepoch)
@@ -124,12 +130,6 @@ if __name__ == '__main__':
args = parser.parse_args()
save_dir = Path(args.save_dir)
alg2data = fetch_data(search_space='tss', dataset='cifar10')
if args.search_space == 'tss':
api = NASBench201API(verbose=False)
elif args.search_space == 'sss':
api = NASBench301API(verbose=False)
else:
raise ValueError('Invalid search space : {:}'.format(args.search_space))
api = create(None, args.search_space, verbose=False)
visualize_curve(api, save_dir, args.search_space)

6
exps/experimental/visualize-nas-bench-x.py
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@@ -21,9 +21,9 @@ import matplotlib.ticker as ticker
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 nas_201_api import NASBench201API, NASBench301API
from log_utils import time_string
from models import get_cell_based_tiny_net
from nats_bench import create
def visualize_info(api, vis_save_dir, indicator):
@@ -391,11 +391,11 @@ if __name__ == '__main__':
to_save_dir = Path(args.save_dir)
datasets = ['cifar10', 'cifar100', 'ImageNet16-120']
api201 = NASBench201API(None, verbose=True)
api201 = create(None, 'tss', verbose=True)
for xdata in datasets:
visualize_tss_info(api201, xdata, to_save_dir)
api301 = NASBench301API(None, verbose=True)
api301 = create(None, 'size', verbose=True)
for xdata in datasets:
visualize_sss_info(api301, xdata, to_save_dir)