code: def test_works_correctly(self):
      input_size = 3
      output_size = 5
      model = tfn.Sequential(
          [
              lambda x: tf.reshape(x, [-1, input_size]),
              AffineMeanFieldNormal(
                  output_size=5, input_size=input_size
              ),
              AffineMeanFieldNormal(
                  output_size=output_size, input_size=5
              ),
          ]
      )
      self.assertLen(model.trainable_variables, 4)
      self.evaluate([v.initializer for v in model.trainable_variables])
      self.assertLen(model.layers, 3)
      self.assertEqual(
          "<Sequential: name=lambda__AffineMeanFieldNormal_AffineMeanFieldNormal>",
          str(model),
      )
  
      x = tf.zeros([2, 1, input_size])
      y = model(x)
      self.assertIsInstance(y, independent.Independent)
      self.assertAllEqual((2, output_size), y.distribution.loc.shape)
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental import nn
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the SequentialTest obj's underlying member method code with example usage: obj.test_works_correctly() without return types