class_docstr: Class to build Reward Prediction Policies with Boltzmann exploration.
class_docstr_tok: ["Class","to","build","Reward","Prediction","Policies","with","Boltzmann","exploration","."]
code: def _get_temperature_value(self):
      return tf.math.maximum(
          _MIN_TEMPERATURE,
          self._temperature()
          if callable(self._temperature)
          else self._temperature,
      )
  
file_path: agents/tf_agents/bandits/policies/boltzmann_reward_prediction_policy.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Iterable, Optional, Sequence, Text, Tuple
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.policies import constraints
  from tf_agents.bandits.policies import reward_prediction_base_policy
  from tf_agents.distributions import shifted_categorical
  from tf_agents.policies import utils
  from tf_agents.typing import types
label_desc: Use image node_id 2 for calling the BoltzmannRewardPredictionPolicy obj's underlying member method code with example usage: obj._get_temperature_value() and returns: tf