class_docstr: Facade around outputs of `step_kernel`.
  
  Processes results and extracts useful data for analysis and further sampling.
docstr: Return realized acceptance rate of the samples.
code: def realized_acceptance_rate(self):
      """Return realized acceptance rate of the samples."""
      try:
          is_accepted = unnest.get_outermost(self.trace, "is_accepted")
      except AttributeError:
          return
      return tf.math.reduce_mean(
          tf.cast(is_accepted, tf.float32), axis=0
      )
  
file_path: probability/tensorflow_probability/python/experimental/mcmc/kernel_outputs.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.mcmc import tracing_reducer
  from tensorflow_probability.python.internal import unnest
  from tensorflow.python.util import nest
label_desc: Use image node_id 4 for calling the KernelOutputs obj's underlying member method code with example usage: obj.realized_acceptance_rate() and returns: tf