code: def _log_joint(current):
      """Log-joint probability given a state's log-probability and momentum."""
      with tf.name_scope("log_joint"):
          momentum_log_prob = -sum(
              [
                  _batchwise_reduce_sum(0.5 * (m**2))
                  for m in current.momentum
              ]
          )
          return current.target_log_prob + momentum_log_prob
  
imports: import collections
  import functools
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python import random
  from tensorflow_probability.python.experimental import auto_batching
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.util.seed_stream import SeedStream
label_desc: Use image node_id 9 for calling a global function with example usage: _log_joint(current) and returns: unknown