code: def _maybe_embed_inverse_temperature_validation(
      inverse_temperatures,
      validate_args,
      using_untempered_log_prob,
  ):
      """Return `inverse_temperatures`, possibly with embedded asserts."""
  
      if not validate_args:
          return inverse_temperatures
  
      if using_untempered_log_prob:
          check = tf.debugging.assert_non_negative(
              inverse_temperatures,
              message=(
                  "`inverse_temperatures` must be non-negative when using "
                  "untempered_log_prob_fn."
              ),
          )
      else:
          check = tf.debugging.assert_positive(
              inverse_temperatures,
              message=(
                  "`inverse_temperatures` must be positive when not using "
                  "untempered_log_prob_fn."
              ),
          )
  
      with tf.control_dependencies([check]):
          return tf.identity(inverse_temperatures)
  
imports: import collections
  import warnings
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import broadcast_util
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import unnest
  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_embed_inverse_temperature_validation(inverse_temperatures, validate_args, using_untempered_log_prob) and returns: inverse_temperatures, tf