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Update time_budget for NATS (algos)

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This commit is contained in:
D-X-Y
2020-11-26 14:43:28 +08:00
parent 8caf85917b
commit 5456939d81
6 changed files with 106 additions and 19 deletions
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3
exps/NATS-algos/bohb.py
View File

@@ -169,7 +169,8 @@ if __name__ == '__main__':
api = create(None, args.search_space, fast_mode=True, verbose=False)
args.save_dir = os.path.join('{:}-{:}'.format(args.save_dir, args.search_space), args.dataset, 'BOHB')
args.save_dir = os.path.join('{:}-{:}'.format(args.save_dir, args.search_space),
'{:}-T{:}'.format(args.dataset, args.time_budget), 'BOHB')
print('save-dir : {:}'.format(args.save_dir))
if args.rand_seed < 0:

3
exps/NATS-algos/random_wo_share.py
View File

@@ -73,7 +73,8 @@ if __name__ == '__main__':
api = create(None, args.search_space, fast_mode=True, verbose=False)
args.save_dir = os.path.join('{:}-{:}'.format(args.save_dir, args.search_space), args.dataset, 'RANDOM')
args.save_dir = os.path.join('{:}-{:}'.format(args.save_dir, args.search_space),
'{:}-T{:}'.format(args.dataset, args.time_budget), 'RANDOM')
print('save-dir : {:}'.format(args.save_dir))
if args.rand_seed < 0:

3
exps/NATS-algos/regularized_ea.py
View File

@@ -200,7 +200,8 @@ if __name__ == '__main__':
api = create(None, args.search_space, fast_mode=True, verbose=False)
args.save_dir = os.path.join('{:}-{:}'.format(args.save_dir, args.search_space), args.dataset, 'R-EA-SS{:}'.format(args.ea_sample_size))
args.save_dir = os.path.join('{:}-{:}'.format(args.save_dir, args.search_space),
'{:}-T{:}'.format(args.dataset, args.time_budget), 'R-EA-SS{:}'.format(args.ea_sample_size))
print('save-dir : {:}'.format(args.save_dir))
print('xargs : {:}'.format(args))

3
exps/NATS-algos/reinforce.py
View File

@@ -194,7 +194,8 @@ if __name__ == '__main__':
api = create(None, args.search_space, fast_mode=True, verbose=False)
args.save_dir = os.path.join('{:}-{:}'.format(args.save_dir, args.search_space), args.dataset, 'REINFORCE-{:}'.format(args.learning_rate))
args.save_dir = os.path.join('{:}-{:}'.format(args.save_dir, args.search_space),
'{:}-T{:}'.format(args.dataset, args.time_budget), 'REINFORCE-{:}'.format(args.learning_rate))
print('save-dir : {:}'.format(args.save_dir))
if args.rand_seed < 0:

65
exps/NATS-algos/run-all.sh
View File

@@ -10,26 +10,61 @@ if [ "$#" -ne 1 ] ;then
exit 1
fi
datasets="cifar10 cifar100 ImageNet16-120"
alg_type=$1
if [ "$alg_type" == "mul" ]; then
search_spaces="tss sss"
# datasets="cifar10 cifar100 ImageNet16-120"
# The topology search space
dataset="cifar10"
search_space="tss"
time_budget="20000"
python ./exps/NATS-algos/reinforce.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --learning_rate 0.01
python ./exps/NATS-algos/regularized_ea.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --ea_cycles 200 --ea_population 10 --ea_sample_size 3
python ./exps/NATS-algos/random_wo_share.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget}
python ./exps/NATS-algos/bohb.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --num_samples 4 --random_fraction 0.0 --bandwidth_factor 3
for dataset in ${datasets}
do
for search_space in ${search_spaces}
do
python ./exps/NATS-algos/reinforce.py --dataset ${dataset} --search_space ${search_space} --learning_rate 0.01
python ./exps/NATS-algos/regularized_ea.py --dataset ${dataset} --search_space ${search_space} --ea_cycles 200 --ea_population 10 --ea_sample_size 3
python ./exps/NATS-algos/random_wo_share.py --dataset ${dataset} --search_space ${search_space}
python ./exps/NATS-algos/bohb.py --dataset ${dataset} --search_space ${search_space} --num_samples 4 --random_fraction 0.0 --bandwidth_factor 3
done
done
dataset="cifar100"
search_space="tss"
time_budget="40000"
python ./exps/NATS-algos/reinforce.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --learning_rate 0.01
python ./exps/NATS-algos/regularized_ea.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --ea_cycles 200 --ea_population 10 --ea_sample_size 3
python ./exps/NATS-algos/random_wo_share.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget}
python ./exps/NATS-algos/bohb.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --num_samples 4 --random_fraction 0.0 --bandwidth_factor 3
python exps/experimental/vis-bench-algos.py --search_space tss
python exps/experimental/vis-bench-algos.py --search_space sss
dataset="ImageNet16-120"
search_space="tss"
time_budget="120000"
python ./exps/NATS-algos/reinforce.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --learning_rate 0.01
python ./exps/NATS-algos/regularized_ea.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --ea_cycles 200 --ea_population 10 --ea_sample_size 3
python ./exps/NATS-algos/random_wo_share.py --dataset ${dataset} --search_space ${search_space}
python ./exps/NATS-algos/bohb.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --num_samples 4 --random_fraction 0.0 --bandwidth_factor 3
# The size search space
dataset="cifar10"
search_space="sss"
time_budget="20000"
python ./exps/NATS-algos/reinforce.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --learning_rate 0.01
python ./exps/NATS-algos/regularized_ea.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --ea_cycles 200 --ea_population 10 --ea_sample_size 3
python ./exps/NATS-algos/random_wo_share.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget}
python ./exps/NATS-algos/bohb.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --num_samples 4 --random_fraction 0.0 --bandwidth_factor 3
dataset="cifar100"
search_space="sss"
time_budget="40000"
python ./exps/NATS-algos/reinforce.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --learning_rate 0.01
python ./exps/NATS-algos/regularized_ea.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --ea_cycles 200 --ea_population 10 --ea_sample_size 3
python ./exps/NATS-algos/random_wo_share.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget}
python ./exps/NATS-algos/bohb.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --num_samples 4 --random_fraction 0.0 --bandwidth_factor 3
dataset="ImageNet16-120"
search_space="tss"
time_budget="60000"
python ./exps/NATS-algos/reinforce.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --learning_rate 0.01
python ./exps/NATS-algos/regularized_ea.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --ea_cycles 200 --ea_population 10 --ea_sample_size 3
python ./exps/NATS-algos/random_wo_share.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget}
python ./exps/NATS-algos/bohb.py --dataset ${dataset} --search_space ${search_space} --time_budget ${time_budget} --num_samples 4 --random_fraction 0.0 --bandwidth_factor 3
# python exps/experimental/vis-bench-algos.py --search_space tss
# python exps/experimental/vis-bench-algos.py --search_space sss
else
seeds="777 888 999"
algos="darts-v1 darts-v2 gdas setn random enas"