52e17e100e9fba324893b9b5ac50c46be7235eea,python/bonsai/compute.py,,main,#,385

Before Change

        if to_date is None:
            to_date = get_current_time()
 
        best_params, score, y_test, predicted = train(model, from_date, to_date)
        for j in range(len(model._features)):
            if (arg.plot == True):
                plot(y_test, predicted, j)

After Change

        type=int,
        default=0,
    )
    parser.add_argument(
        "--train_size",
        help="Train and test split",
        type=float,
        default=0.67,
    )
    parser.add_argument(
        "--batch_size",
        help="Batch size",
        type=int,
        default=64,
    )
    parser.add_argument(
        "--num_epochs",
        help="Epochs used in training",
        type=int,
        default=100,
    )
    parser.add_argument(
        "--max_evals",
        help="Maximum evals for Bayesian hyperparams optimization",
        type=int,
        default=10,
    )

    arg = parser.parse_args()
    _verbose = arg.verbose

Instances