def init_config():
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=True)
args = parser.parse_args()
config = process_config(args.config)
return config
def init_config():
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=True)
parser.add_argument('--run', type=str, default='')
args = parser.parse_args()
runs = None
if len(args.run) > 0:
runs = args.run
config = process_config(args.config, runs)
return config
def init_config():
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=True)
parser.add_argument('--run', type=str, default='')
parser.add_argument('--seed', default=0, type=int, help='seed for initializing training. ')
args = parser.parse_args()
runs = None
if len(args.run) > 0:
runs = args.run
seed = args.seed
config = process_config(args.config, runs, seed)
return config, seed
def init_config():
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=False)
parser.add_argument('--run', type=str, default='')
args = parser.parse_args()
os.environ['CUDA_VISIBLE_DEVICES'] = '3'
args.config = '/home/wzn/PycharmProjects/GraSP/configs/tiny_imagenet/resnet32/GraSP_90.json'
runs = None
if len(args.run) > 0:
runs = args.run
config = process_config(args.config, runs)
return config
def init_config():
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=True)
parser.add_argument('--run', type=str, default='')
parser.add_argument('--init', type=str, default='kaiming_xavier')
parser.add_argument('--target_ratio', type=float, default=None)
parser.add_argument('--gpu', type=int, default=0)
parser.add_argument('--seed_tiny', type=int, default=0)
parser.add_argument('--scaled_init', action='store_true')
parser.add_argument('--bn', action='store_true')
parser.add_argument('--act', type=str, default='relu')
parser.add_argument('--sigma_w2', type=float, default=None, help='This is only for ordered init')
args = parser.parse_args()
runs = None
if len(args.run) > 0:
runs = args.run
config = process_config(args.config, runs)
#os.environ['CUDA_VISIBLE_DEVICES'] = "{}".format(args.gpu)
return config, args
stats[it] = stat
if prune_mode == 'one_pass':
del net
del pruner
net, bottleneck_net = init_network(config, logger, device)
pruner = init_pruner(net, bottleneck_net, config, writer, logger)
pruner.iter = it
with open(os.path.join(config.summary_dir, 'stats.json'), 'w') as f:
json.dump(stats, f)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--tmp_config', type=str, default='', required=False)
parser.add_argument('--config', type=str, default='', required=False)
args = parser.parse_args()
if len(args.tmp_config) > 1:
print('Using tmp config!')
config, _ = get_config_from_json(args.tmp_config)
makedirs(config.summary_dir)
sys.stdout = open(os.path.join(config.summary_dir, 'stdout.txt'), 'w+')
sys.stderr = open(os.path.join(config.summary_dir, 'stderr.txt'), 'w+')
main(config)
else:
print('Using config!')
config = process_config(args.config)
main(config)