code: def testEpsilon(self, float_epsilon, is_tensor):
      epsilon = (
          tf.constant(float_epsilon) if is_tensor else float_epsilon
      )
      policy = epsilon_greedy_policy.EpsilonGreedyPolicy(
          self._policy, epsilon=epsilon
      )
      self.assertEqual(policy.time_step_spec, self._time_step_spec)
      self.assertEqual(policy.action_spec, self._action_spec)
  
      policy_state = policy.get_initial_state(batch_size=2)
      time_step = tf.nest.map_structure(
          tf.convert_to_tensor, self._time_step
      )
  
      @common.function
      def action_step_fn(time_step=time_step):
          return policy.action(time_step, policy_state, seed=54)
  
      tf.nest.assert_same_structure(
          self._action_spec,
          self.evaluate(action_step_fn(time_step)).action,
      )
  
      if tf.executing_eagerly():
          action_step = action_step_fn
      else:
          action_step = action_step_fn()
  
      actions = []
      log_probs = []
  
      num_steps = 1000
      for _ in range(num_steps):
          step = self.evaluate(action_step)
          action_ = step.action[0]
          log_prob_ = step.info.log_probability[0]
          self.assertIn(action_, [0, 1, 2])
          actions.append(action_)
          log_probs.append(log_prob_)
  
      # Verify that action distribution changes as we vary epsilon.
      self.checkActionDistribution(
          actions, float_epsilon, num_steps, log_probs
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import math
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.policies import epsilon_greedy_policy
  from tf_agents.policies import fixed_policy
  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 common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 3 for calling the EpsilonGreedyPolicyTest obj's underlying member method code with example usage: obj.testEpsilon(float_epsilon, is_tensor) and returns: policy