code: def testAdaptationSteps(self):
      kernel = FakeMHKernel(
          FakeSteppedKernel(step_size=0.1), log_accept_ratio=0.0
      )
      kernel = sssa.SimpleStepSizeAdaptation(
          kernel,
          num_adaptation_steps=2,
          adaptation_rate=_RATE - 1.0,
          validate_args=True,
      )
  
      kernel_results = kernel.bootstrap_results(0.0)
      step_kernel_results = []
      for _ in range(4):
          _, kernel_results = kernel.one_step(0.0, kernel_results)
          step_kernel_results.append(kernel_results)
  
      step_sizes = self.evaluate(
          [
              kernel_results.inner_results.accepted_results.step_size
              for kernel_results in step_kernel_results
          ]
      )
  
      self.assertAllClose(0.1, step_sizes[0])
      self.assertAllClose(0.1 * _RATE, step_sizes[1])
      self.assertAllClose(0.1 * _RATE**2, step_sizes[2])
      self.assertAllClose(0.1 * _RATE**2, step_sizes[3])
  
imports: import collections
  import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.experimental.mcmc import sharded
  from tensorflow_probability.python.internal import distribute_lib
  from tensorflow_probability.python.internal import distribute_test_lib
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import generic
  from tensorflow_probability.python.mcmc import hmc
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.mcmc import sample
  from tensorflow_probability.python.mcmc import simple_step_size_adaptation
label_desc: Use image node_id 4 for calling the SimpleStepSizeAdaptationTest obj's underlying member method code with example usage: obj.testAdaptationSteps() without return types