def _validate_shuffle_split(n_samples, test_size, train_size):
    """
    Validation helper to check if the test/test sizes are meaningful wrt to the
    size of the data (n_samples)
    """
    if (test_size is not None and np.asarray(test_size).dtype.kind == 'i'
            and test_size >= n_samples):
        raise ValueError('test_size=%d should be smaller than the number of '
                         'samples %d' % (test_size, n_samples))

    if (train_size is not None and np.asarray(train_size).dtype.kind == 'i'
            and train_size >= n_samples):
        raise ValueError("train_size=%d should be smaller than the number of"
                         " samples %d" % (train_size, n_samples))

    if np.asarray(test_size).dtype.kind == 'f':
        n_test = ceil(test_size * n_samples)
    elif np.asarray(test_size).dtype.kind == 'i':
        n_test = float(test_size)

    if train_size is None:
        n_train = n_samples - n_test
    elif np.asarray(train_size).dtype.kind == 'f':
        n_train = floor(train_size * n_samples)
    else:
        n_train = float(train_size)

    if test_size is None:
        n_test = n_samples - n_train

    if n_train + n_test > n_samples:
        raise ValueError('The sum of train_size and test_size = %d, '
                         'should be smaller than the number of '
                         'samples %d. Reduce test_size and/or '
                         'train_size.' % (n_train + n_test, n_samples))

    return int(n_train), int(n_test)
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/model_selection/_split.py/_validate_shuffle_split/original