code: def test_assigns_default_names(self):
      init_fn, _ = trainable_state_util.as_stateless_builder(
          seed_generator
      )()
      params = init_fn(test_util.test_seed(sampler_type="stateless"))
      param_keys = (
          params._asdict().keys()
      )  # Params is a namedtuple / structuple.
      self.assertLen(param_keys, 5)
      self.assertIn("parameter", param_keys)
      for i in range(1, 5):
          self.assertIn("parameter_{:04d}".format(i), param_keys)
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import joint_distribution_auto_batched
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.internal import trainable_state_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.minimize import minimize
  from tensorflow_probability.python.math.minimize import minimize_stateless
label_desc: Use image node_id 5 for calling the TestWrapGeneratorAsStateless obj's underlying member method code with example usage: obj.test_assigns_default_names() without return types