def load_results(experiment_root):
# load the model (mlp_best.pkl)
model_file = os.path.join(experiment_root, 'mlp_best.pkl');
with log_timing(log, 'loading model from {}'.format(model_file)):
model = serial.load(model_file);
# load train
train_yaml_file = os.path.join(experiment_root, 'train.yaml');
train_yaml = load_yaml_template(train_yaml_file);
# fix dataset path
localizer = PathLocalizer();
train_yaml = localizer.localize_yaml(train_yaml);
with log_timing(log, 'loading train from {}'.format(train_yaml_file)):
train = load_yaml(train_yaml)[0];
return train, model;
def load_results(experiment_root):
# load the model (mlp_best.pkl)
model_file = os.path.join(experiment_root, 'mlp_best.pkl')
with log_timing(log, 'loading model from {}'.format(model_file)):
model = serial.load(model_file)
# load train
train_yaml_file = os.path.join(experiment_root, 'train.yaml')
train_yaml = load_yaml_template(train_yaml_file)
# fix dataset path
localizer = PathLocalizer()
train_yaml = localizer.localize_yaml(train_yaml)
with log_timing(log, 'loading train from {}'.format(train_yaml_file)):
train = load_yaml(train_yaml)[0]
return train, model
default='train.yaml',
help='path of the YAML file to run')
parser.add_argument(
"-c",
"--config", #type=str,
help="specify a config file")
parser.add_argument(
"-l",
"--localizer", #type=str,
help="specify a custom localizer")
args = parser.parse_args()
train_yaml = load_yaml_template(args.yaml)
# load optional settings
if args.config is not None:
config = load_config_file(args.config)
else:
config = empty_config()
if not hasattr(config, 'random_seed'):
random_seed = random.randint(0, 100)
config.random_seed = random_seed
log.debug('using random seed {}'.format(random_seed))
# load optional localizer
if args.localizer is not None:
localizer_class = args.localizer
# parse arguments using optparse or argparse or what have you
parser = argparse.ArgumentParser(prog='run_train',
description='run a train algorithm as specified by a YAML file');
# global options
parser.add_argument('yaml', default='train.yaml', help='path of the YAML file to run');
parser.add_argument("-c", "--config", #type=str,
help="specify a config file");
parser.add_argument("-l", "--localizer", #type=str,
help="specify a custom localizer");
args = parser.parse_args();
train_yaml = load_yaml_template(args.yaml);
# load optional settings
if args.config is not None:
config = load_config_file(args.config);
else:
config = empty_config();
if not hasattr(config, 'random_seed'):
random_seed = random.randint(0, 100);
config.random_seed = random_seed;
log.debug('using random seed {}'.format(random_seed))
# load optional localizer
if args.localizer is not None:
localizer_class = args.localizer;
