fix tests

    """Test that Conv1D can be invoked."""

    width = 5

    in_channels = 2

    out_channels = 3

    filters = 3

    kernel_size = 2

    batch_size = 10

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

    with self.test_session() as sess:

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

      out_tensor = Conv1D(width, out_channels)(in_tensor)

      out_tensor = Conv1D(filters, kernel_size)(in_tensor)

      sess.run(tf.global_variables_initializer())

      out_tensor = out_tensor.eval()

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

      self.assertEqual(out_tensor.shape[0], batch_size)

      self.assertEqual(out_tensor.shape[2], filters)

  def test_dense(self):

    """Test that Dense can be invoked."""

    value2 = np.random.uniform(size=(2, 3)).astype(np.float32)

    value3 = np.random.uniform(size=(2, 3)).astype(np.float32)

    with self.test_session() as sess:

      out_tensor = Add(weights=[1, 2, 1])(

          tf.constant(value1), tf.constant(value2), tf.constant(value3))

      out_tensor = Add(weights=[1, 2, 1])(tf.constant(value1),

                                          tf.constant(value2),

                                          tf.constant(value3))

      assert np.array_equal(value1 + 2 * value2 + value3, out_tensor.eval())

  def test_multiply(self):