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Create NATS

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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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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: