code: def testLargeTemperature(self):
      # With a very large temperature, the sampling probability will be uniform.
      policy = boltzmann_reward_policy.BoltzmannRewardPredictionPolicy(
          self._time_step_spec,
          self._action_spec,
          reward_network=DummyNet(self._obs_spec),
          temperature=10e8,
          emit_policy_info=(utils.InfoFields.LOG_PROBABILITY,),
      )
      batch_size = 3000
      observations = tf.constant(
          [[1, 2]] * batch_size, dtype=tf.float32
      )
      time_step = ts.restart(observations, batch_size=batch_size)
      action_step = policy.action(time_step, seed=1)
      # Initialize all variables
      self.evaluate(tf.compat.v1.global_variables_initializer())
      p_info = self.evaluate(action_step.info)
      # Check the log probabilities in the policy info are uniform.
      self.assertAllEqual(
          p_info.log_probability, tf.math.log([1.0 / 3] * batch_size)
      )
      # Check the empirical distribution of the chosen arms is uniform.
      actions = self.evaluate(action_step.action)
      self.assertAllInSet(actions, [0, 1, 2])
      # Set tolerance in the chosen count to be 4 std.
      tol = 4.0 * np.sqrt(batch_size * 1.0 / 3 * 2.0 / 3)
      for action in range(3):
          action_chosen_count = np.sum(actions == action)
          self.assertNear(
              action_chosen_count,
              1000,
              tol,
              msg=(
                  f"action: {action} is expected to be chosen between {1000 - tol} "
                  f"and {1000 + tol} times, but was actually chosen "
                  f"{action_chosen_count} times."
              ),
          )
  
imports: import numpy
  import tensorflow
  from tf_agents.bandits.policies import boltzmann_reward_prediction_policy
  from tf_agents.networks import network
  from tf_agents.policies import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 3 for calling the BoltzmannRewardPredictionPolicyTest obj's underlying member method code with example usage: obj.testLargeTemperature() without return types