code: def bootstrap_results(self, current_state):
      return FakeSteppedKernelResults(
          step_size=tf.nest.map_structure(
              tf.convert_to_tensor, self.parameters["step_size"]
          )
      )
  
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 3 for calling the FakeSteppedKernel obj's underlying member method code with example usage: obj.bootstrap_results(current_state) and returns: FakeSteppedKernelResults