code: def _has_no_u_turn(state_one, state_two, momentum):
      """If two given states and momentum do not exhibit a U-turn pattern."""
      with tf.name_scope("has_no_u_turn"):
          batch_dot_product = sum(
              [
                  _batchwise_reduce_sum((s1 - s2) * m)
                  for s1, s2, m in zip(state_one, state_two, momentum)
              ]
          )
          return batch_dot_product > 0
  
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 5 for calling a global function with example usage: _has_no_u_turn(state_one, state_two, momentum) and returns: unknown