code: def test_is_calibrated(self):
      self.assertTrue(
          transformed_kernel.TransformedTransitionKernel(
              FakeInnerKernel(lambda x: -(x**2) / 2, True),
              identity.Identity(),
          ).is_calibrated
      )
      self.assertFalse(
          transformed_kernel.TransformedTransitionKernel(
              FakeInnerKernel(lambda x: -(x**2) / 2, False),
              identity.Identity(),
          ).is_calibrated
      )
  
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 9 for calling the TransformedTransitionKernelTest obj's underlying member method code with example usage: obj.test_is_calibrated() without return types