40a9ecc684d2c5e7fdfc09f46d0912940b74ab63,keras/datasets/boston_housing.py,,load_data,#,11

Before Change

    path = get_file(path,
                    origin="https://s3.amazonaws.com/keras-datasets/boston_housing.npz",
                    file_hash="f553886a1f8d56431e820c5b82552d9d95cfcb96d1e678153f8839538947dff5")
    f = np.load(path)
    x = f["x"]
    y = f["y"]
    f.close()

    np.random.seed(seed)
    indices = np.arange(len(x))
    np.random.shuffle(indices)
    x = x[indices]
    y = y[indices]

    x_train = np.array(x[:int(len(x) * (1 - test_split))])
    y_train = np.array(y[:int(len(x) * (1 - test_split))])
    x_test = np.array(x[int(len(x) * (1 - test_split)):])
    y_test = np.array(y[int(len(x) * (1 - test_split)):])
    return (x_train, y_train), (x_test, y_test)

After Change

    path = get_file(path,
                    origin="https://s3.amazonaws.com/keras-datasets/boston_housing.npz",
                    file_hash="f553886a1f8d56431e820c5b82552d9d95cfcb96d1e678153f8839538947dff5")
    with np.load(path) as f:
        x = f["x"]
        y = f["y"]

    np.random.seed(seed)
    indices = np.arange(len(x))
    np.random.shuffle(indices)
    x = x[indices]
    y = y[indices]

    x_train = np.array(x[:int(len(x) * (1 - test_split))])
    y_train = np.array(y[:int(len(x) * (1 - test_split))])
    x_test = np.array(x[int(len(x) * (1 - test_split)):])
    y_test = np.array(y[int(len(x) * (1 - test_split)):])
    return (x_train, y_train), (x_test, y_test)

Instances