def testFromSparseTensorSlicesInReverse(self, slices):
    """Test a dataset based on slices of a `tf.sparse.SparseTensor` in reverse order."""
    st = array_ops.sparse_placeholder(dtypes.float64)
    iterator = dataset_ops.make_initializable_iterator(
        dataset_ops.Dataset.from_sparse_tensor_slices(st))
    init_op = iterator.initializer

    with self.cached_session() as sess:
      # pylint: disable=g-complex-comprehension
      indices = np.array(
          [[i, j] for i in range(len(slices)) for j in range(len(slices[i]))])
      values = np.array([val for s in slices for val in s])
      # pylint: enable=g-complex-comprehension
      dense_shape = np.array([len(slices), max(len(s) for s in slices) + 1])
      # Test with sparse tensor in the reverse order, which is not
      # currently supported.
      reverse_order_indices = indices[::-1, :]
      reverse_order_values = values[::-1]
      sparse_feed = sparse_tensor.SparseTensorValue(
          reverse_order_indices, reverse_order_values, dense_shape)
      with self.assertRaises(errors.UnimplementedError):
        sess.run(init_op, feed_dict={st: sparse_feed})