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;