code: def test_assigns_unique_names(self):
      init_fn, _ = trainable_state_util.as_stateless_builder(
          joint_normal_nested_generator
      )([[1], [2], [3]])
      params = init_fn(test_util.test_seed(sampler_type="stateless"))
      param_keys = (
          params._asdict().keys()
      )  # Params is a namedtuple / structuple.
      self.assertLen(param_keys, 6)
      self.assertIn("loc", param_keys)
      self.assertIn("scale", param_keys)
      self.assertIn("loc_0001", param_keys)
      self.assertIn("scale_0001", param_keys)
      self.assertIn("loc_0002", param_keys)
      self.assertIn("scale_0002", 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 4 for calling the TestWrapGeneratorAsStateless obj's underlying member method code with example usage: obj.test_assigns_unique_names() without return types