stackexchange-tutorial/tutorial/eval.py

from . import shared

def predict_test_set():
    print("Loading test data")
    X, y = shared.load_data_and_labels(shared.test_processed)
    print("Done")
    clf = shared.load(shared.classifier_pkl)
    preds = clf.predict(X.sparse.to_coo())
    return y, preds, clf, shared.compute_metrics(y, preds, "test")

def main():
    y, preds, clf, metrics = predict_test_set()
    from dagshub import dagshub_logger
    with dagshub_logger(metrics_path='test-metrics.csv', should_log_hparams=False) as logger:
        logger.log_metrics(metrics)
    
    # For possible interactive use
    return y, preds, clf, metrics

if __name__ == "__main__":
    main()