code: def __init__(self, *args, **kwargs):
      super().__init__(
          target_log_prob_fn=lambda x: -x * x,
          step_size=0.1,
          num_leapfrog_steps=2,
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.experimental.distribute import sharded
  from tensorflow_probability.python.experimental.mcmc import diagonal_mass_matrix_adaptation
  from tensorflow_probability.python.experimental.mcmc import preconditioned_hmc
  from tensorflow_probability.python.experimental.stats import sample_stats
  from tensorflow_probability.python.internal import distribute_test_lib
  from tensorflow_probability.python.internal import loop_util
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 to create a new EchoKernel object from inherited base classes: phmc with example: obj = EchoKernel()