Fixed test case

    batch_size = 10

    n_hidden = 7

    in_channels = 4

    out_channels = 5

    n_repeat = 2

    n_steps = 6

    in_tensor = np.random.rand(batch_size, n_steps, in_channels)

    with self.test_session() as sess:

      in_tensor = tf.convert_to_tensor(in_tensor, dtype=tf.float32)

      out_tensor = GRU(n_hidden, out_channels, batch_size)(in_tensor)

      out_tensor = GRU(n_hidden, batch_size)(in_tensor)

      sess.run(tf.global_variables_initializer())

      out_tensor = out_tensor.eval()

      assert out_tensor.shape == (batch_size, n_steps, out_channels)

      assert out_tensor.shape == (batch_size, n_steps, n_hidden)

  def test_time_series_dense(self):

    """Test that TimeSeriesDense can be invoked."""