code: def test_step_size_changed(self):
      target_dist = mvn_diag.MultivariateNormalDiag(
          loc=[0.0, 0.0], scale_diag=[1.0, 10.0]
      )
      # `hmc_kernel`'s step size is far from optimal
      hmc_kernel = hmc.HamiltonianMonteCarlo(
          target_log_prob_fn=target_dist.log_prob,
          num_leapfrog_steps=27,
          step_size=10,
      )
      step_adaptation_kernel = sssa.SimpleStepSizeAdaptation(
          inner_kernel=hmc_kernel,
          adaptation_rate=0.8,
          num_adaptation_steps=9,
      )
      trans_kernel = transformed_kernel.TransformedTransitionKernel(
          inner_kernel=step_adaptation_kernel, bijector=exp.Exp()
      )
      kernel_results = trans_kernel.inner_kernel.bootstrap_results(
          tf.zeros(2)
      )
      stream = test_util.test_seed_stream()
      for _ in range(2):
          _, kernel_results = trans_kernel.inner_kernel.one_step(
              tf.zeros(2), kernel_results, seed=stream()
          )
      adapted_step_size = self.evaluate(
          kernel_results.inner_results.accepted_results.step_size
      )
      self.assertLess(adapted_step_size, 7)
  
imports: import collections
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import cholesky_lkj
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import uniform
  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 langevin
  from tensorflow_probability.python.mcmc import random_walk_metropolis
  from tensorflow_probability.python.mcmc import sample
  from tensorflow_probability.python.mcmc import simple_step_size_adaptation
  from tensorflow_probability.python.mcmc import transformed_kernel
label_desc: Use image node_id 12 for calling the TransformedTransitionKernelTest obj's underlying member method code with example usage: obj.test_step_size_changed() without return types