385d547abb17e1cefa01d857dd4021ca99188f30,examples/custom_dataset/predict_custom_dataset.py,,main,#,77

Before Change

    // Scale the label values, if necessary.
    if args.scale == "standardize":
        ss = StandardScaler()
        labels = ss.fit_transform(dataset.get_datasets()[-1])
        dataset = NumpyTupleDataset(*(dataset.get_datasets()[:-1] + (labels,)))
    else:
        ss = None

    test = dataset

After Change

    // Load the standard scaler parameters, if necessary.
    if args.scale == "standardize":
        with open(os.path.join(args.in_dir, "scaler.pkl"), mode="rb") as f:
            scaler = pickle.load(f)
    else:
        scaler = None
    test = dataset

Instances