code: def testSeedReproducibility(self):
      first_fake_kernel = RandomTransitionKernel()
      second_fake_kernel = RandomTransitionKernel()
      seed = samplers.sanitize_seed(test_util.test_seed())
      first_final_state = sample_chain(
          num_results=5,
          current_state=0.0,
          kernel=first_fake_kernel,
          seed=seed,
      )
      second_final_state = sample_chain(
          num_results=5,
          current_state=1.0,  # difference should be irrelevant
          kernel=second_fake_kernel,
          seed=seed,
      )
      first_final_state, second_final_state = self.evaluate(
          [first_final_state, second_final_state]
      )
      self.assertAllCloseNested(
          first_final_state, second_final_state, rtol=1e-6
      )
  
imports: import collections
  import warnings
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import pad
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_auto_batched
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import multinomial
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.experimental.mcmc import diagonal_mass_matrix_adaptation
  from tensorflow_probability.python.experimental.mcmc import preconditioned_hmc
  from tensorflow_probability.python.experimental.stats import sample_stats
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import hmc
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.mcmc import nuts
  from tensorflow_probability.python.mcmc import random_walk_metropolis
  from tensorflow_probability.python.mcmc import simple_step_size_adaptation
  from tensorflow_probability.python.mcmc import transformed_kernel
  from tensorflow_probability.python.mcmc.sample import sample_chain
  from tensorflow_probability.python.random.random_ops import rayleigh
label_desc: Use image node_id 14 for calling the SampleChainTest obj's underlying member method code with example usage: obj.testSeedReproducibility() without return types