code: def testIsCalibrated(self):
      test_kernel = collections.namedtuple(
          "TestKernel", "is_calibrated"
      )
      self.assertTrue(
          sssa.SimpleStepSizeAdaptation(
              test_kernel(True), 1
          ).is_calibrated
      )
      self.assertFalse(
          sssa.SimpleStepSizeAdaptation(
              test_kernel(False), 1
          ).is_calibrated
      )
  
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 11 for calling the SimpleStepSizeAdaptationTest obj's underlying member method code with example usage: obj.testIsCalibrated() without return types