code: def _maybe_validate_target_accept_prob(
      target_accept_prob, validate_args
  ):
      """Validates that target_accept_prob is in (0, 1)."""
      if not validate_args:
          return target_accept_prob
      with tf.control_dependencies(
          [
              assert_util.assert_positive(
                  target_accept_prob,
                  message="`target_accept_prob` must be > 0.",
              ),
              assert_util.assert_less(
                  target_accept_prob,
                  tf.ones_like(target_accept_prob),
                  message="`target_accept_prob` must be < 1.",
              ),
          ]
      ):
          return tf.identity(target_accept_prob)
  
imports: import collections
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import unnest
  from tensorflow_probability.python.math.generic import reduce_logmeanexp
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.mcmc.internal import util
label_desc: Use image node_id 5 for calling a global function with example usage: _maybe_validate_target_accept_prob(target_accept_prob, validate_args) and returns: target_accept_prob, tf