def run_everything(args=None, logger=None):
if args is None:
parser = argparse.ArgumentParser(
'Code to Natural Language Generation',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
add_test_args(parser)
config.add_model_args(parser)
#args = parser.parse_args()
args, unknown = parser.parse_known_args()
print(args.data_dir)
set_defaults(args)
# Set cuda
args.cuda = torch.cuda.is_available()
args.parallel = torch.cuda.device_count() > 1
# Set random state
np.random.seed(args.random_seed)
torch.manual_seed(args.random_seed)
if args.cuda:
torch.cuda.manual_seed(args.random_seed)
if logger is None:
fmt_list = [] #[('lr', "3.4e"),]
fmt = dict(fmt_list)
path = args.model_file[:args.model_file.rfind("/")+1]+\
"_".join(["test"]+([args.comment] if args.comment!="" else []))+"/"
logger = logger_module.Logger(args.comment,
fmt=fmt,
base=args.dir,
path=path)
logger.print(" ".join(sys.argv))
logger.print(args)
# Run!
main(args, logger)
model.save(args.model_file)
stats['best_valid'] = result[args.valid_metric]
stats['no_improvement'] = 0
else:
stats['no_improvement'] += 1
if stats['no_improvement'] >= args.early_stop:
break
if __name__ == '__main__':
# Parse cmdline args and setup environment
parser = argparse.ArgumentParser(
'Code to Natural Language Generation',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
add_train_args(parser)
config.add_model_args(parser)
args = parser.parse_args()
set_defaults(args)
# Set cuda
args.cuda = torch.cuda.is_available()
args.parallel = torch.cuda.device_count() > 1
# Set random state
np.random.seed(args.random_seed)
torch.manual_seed(args.random_seed)
if args.cuda:
torch.cuda.manual_seed(args.random_seed)
# Set logging
logger.setLevel(logging.INFO)