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Update REA, REINFORCE, and RANDOM

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D-X-Y
2020-07-13 10:04:52 +00:00
parent 041a9aa4a3
commit 6dc494be08
12 changed files with 277 additions and 53 deletions
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33
exps/algos-v2/reinforce.py
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@@ -3,12 +3,12 @@
#####################################################################################################
# modified from https://github.com/pytorch/examples/blob/master/reinforcement_learning/reinforce.py #
#####################################################################################################
# python ./exps/algos-v2/reinforce.py --dataset cifar10 --search_space tss --time_budget 12000 --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset cifar100 --search_space tss --time_budget 12000 --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset ImageNet16-120 --search_space tss --time_budget 12000 --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset cifar10 --search_space sss --time_budget 12000 --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset cifar100 --search_space sss --time_budget 12000 --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset ImageNet16-120 --search_space sss --time_budget 12000 --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset cifar10 --search_space tss --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset cifar100 --search_space tss --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset ImageNet16-120 --search_space tss --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset cifar10 --search_space sss --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset cifar100 --search_space sss --learning_rate 0.001
# python ./exps/algos-v2/reinforce.py --dataset ImageNet16-120 --search_space sss --learning_rate 0.001
#####################################################################################################
import os, sys, time, glob, random, argparse
import numpy as np, collections
@@ -120,15 +120,10 @@ def select_action(policy):
def main(xargs, api):
assert torch.cuda.is_available(), 'CUDA is not available.'
torch.backends.cudnn.enabled = True
torch.backends.cudnn.benchmark = False
torch.backends.cudnn.deterministic = True
torch.set_num_threads(xargs.workers)
torch.set_num_threads(4)
prepare_seed(xargs.rand_seed)
logger = prepare_logger(args)
search_space = get_search_spaces(xargs.search_space, 'nas-bench-301')
if xargs.search_space == 'tss':
policy = PolicyTopology(search_space)
@@ -144,6 +139,7 @@ def main(xargs, api):
# nas dataset load
logger.log('{:} use api : {:}'.format(time_string(), api))
api.reset_time()
# REINFORCE
x_start_time = time.time()
@@ -153,7 +149,7 @@ def main(xargs, api):
start_time = time.time()
log_prob, action = select_action( policy )
arch = policy.generate_arch( action )
reward, _, current_total_cost = api.simulate_train_eval(arch, xargs.dataset, '12')
reward, _, _, current_total_cost = api.simulate_train_eval(arch, xargs.dataset, '12')
trace.append((reward, arch))
total_costs.append(current_total_cost)
@@ -177,7 +173,7 @@ def main(xargs, api):
logger.log('-'*100)
logger.close()
return logger.log_dir, [api.query_index_by_arch(x[0]) for x in trace], total_costs
return logger.log_dir, [api.query_index_by_arch(x[1]) for x in trace], total_costs
if __name__ == '__main__':
@@ -186,15 +182,14 @@ if __name__ == '__main__':
parser.add_argument('--dataset', type=str, choices=['cifar10', 'cifar100', 'ImageNet16-120'], help='Choose between Cifar10/100 and ImageNet-16.')
parser.add_argument('--search_space', type=str, choices=['tss', 'sss'], help='Choose the search space.')
parser.add_argument('--learning_rate', type=float, help='The learning rate for REINFORCE.')
parser.add_argument('--EMA_momentum', type=float, default=0.9, help='The momentum value for EMA.')
parser.add_argument('--time_budget', type=int, help='The total time cost budge for searching (in seconds).')
parser.add_argument('--loops_if_rand', type=int, default=500, help='The total runs for evaluation.')
parser.add_argument('--EMA_momentum', type=float, default=0.9, help='The momentum value for EMA.')
parser.add_argument('--time_budget', type=int, default=20000, help='The total time cost budge for searching (in seconds).')
parser.add_argument('--loops_if_rand', type=int, default=500, help='The total runs for evaluation.')
# log
parser.add_argument('--workers', type=int, default=2, help='number of data loading workers (default: 2)')
parser.add_argument('--save_dir', type=str, default='./output/search', help='Folder to save checkpoints and log.')
parser.add_argument('--arch_nas_dataset', type=str, help='The path to load the architecture dataset (tiny-nas-benchmark).')
parser.add_argument('--print_freq', type=int, help='print frequency (default: 200)')
parser.add_argument('--rand_seed', type=int, default=-1, help='manual seed')
parser.add_argument('--rand_seed', type=int, default=-1, help='manual seed')
args = parser.parse_args()
if args.search_space == 'tss':