code: def test_initialization_is_deterministic_with_seed(self):
      seed = test_util.test_seed(sampler_type="stateless")
      make_trainable_jd = trainable_state_util.as_stateful_builder(
          seed_generator
      )
  
      trainable_jd1 = make_trainable_jd(seed=seed)
      variables1 = trainable_jd1.trainable_variables
      self.assertLen(variables1, 5)
  
      trainable_jd2 = make_trainable_jd(seed=seed)
      variables2 = trainable_jd2.trainable_variables
      self.evaluate([v.initializer for v in variables1 + variables2])
      vals1, vals2 = self.evaluate((variables1, variables2))
      self.assertAllCloseNested(vals1, vals2)
  
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 1 for calling the TestWrapGeneratorAsStateful obj's underlying member method code with example usage: obj.test_initialization_is_deterministic_with_seed() without return types