type=str, choices=CHEMPROP_METRICS, help=("Metric for which to evaluate " "the model performance"), default=None) parser.add_argument("--train_folder", type=str, help=("Folder in which you will store the " "ChemProp model."), default=None) parser.add_argument("--cp_folder", type=str, help=("Path to ChemProp folder.")) parser.add_argument("--max_hyp_specs", type=int, help=("Maximum number of species for hyperparameter " "optimization")) parser.add_argument("--seed", type=int, help=("Seed for sampling data for hyperparameter " "optimization")) parser.add_argument('--config_file', type=str, help=("Path to JSON file with arguments " "for this script. If given, any " "arguments in the file override the " "command line arguments.")) args = parse_args(parser) main(**args.__dict__)
"the model performance"), default=None) parser.add_argument("--train_feat_path", type=str, help=("Path to features file for training set"), default=None) parser.add_argument("--val_feat_path", type=str, help=("Path to features file for validation set"), default=None) parser.add_argument("--test_feat_path", type=str, help=("Path to features file for test set"), default=None) parser.add_argument("--train_folder", type=str, help=("Folder in which you will store the " "ChemProp model."), default=None) parser.add_argument("--features_only", action='store_true', help=("Train model with only the stored features")) parser.add_argument("--cp_folder", type=str, help=("Path to ChemProp folder.")) parser.add_argument("--no_features", action="store_true", help=("Don't use external features when training " "model.")) parser.add_argument('--this_config_file', type=str, help=("Path to JSON file with arguments " "for this script. If given, any " "arguments in the file override the " "command line arguments.")) args = parse_args(parser, config_flag="this_config_file") main(**args.__dict__)