def _validate_shuffle_split_init(test_size, train_size):
    """Validation helper to check the test_size and train_size at init

    NOTE This does not take into account the number of samples which is known
    only at split
    """
    if test_size is None and train_size is None:
        raise ValueError('test_size and train_size can not both be None')

    if test_size is not None:
        if np.asarray(test_size).dtype.kind == 'f':
            if test_size >= 1.:
                raise ValueError(
                    'test_size=%f should be smaller '
                    'than 1.0 or be an integer' % test_size)
        elif np.asarray(test_size).dtype.kind != 'i':
            # int values are checked during split based on the input
            raise ValueError("Invalid value for test_size: %r" % test_size)

    if train_size is not None:
        if np.asarray(train_size).dtype.kind == 'f':
            if train_size >= 1.:
                raise ValueError("train_size=%f should be smaller "
                                 "than 1.0 or be an integer" % train_size)
            elif (np.asarray(test_size).dtype.kind == 'f' and
                    (train_size + test_size) > 1.):
                raise ValueError('The sum of test_size and train_size = %f, '
                                 'should be smaller than 1.0. Reduce '
                                 'test_size and/or train_size.' %
                                 (train_size + test_size))
        elif np.asarray(train_size).dtype.kind != 'i':
            # int values are checked during split based on the input
            raise ValueError("Invalid value for train_size: %r" % train_size)
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/model_selection/_split.py/_validate_shuffle_split_init/original