code: def test_summary(self):
      model = tfn.Sequential(
          [
              lambda x: tf.reshape(x, [-1, 3]),
              AffineMeanFieldNormal(output_size=5, input_size=3),
              AffineMeanFieldNormal(output_size=2, input_size=5),
          ]
      )
      self.assertEqual(
          "trainable size: 32  /  0.000 MiB  /  {float32: 32}",
          model.summary().split("\n")[-1],
      )
  
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 2 for calling the SequentialTest obj's underlying member method code with example usage: obj.test_summary() without return types