code: def setUp(self):
      super(EpsilonGreedyPolicyTest, self).setUp()
      self._obs_spec = tensor_spec.TensorSpec([2], tf.float32)
      self._time_step_spec = ts.time_step_spec(self._obs_spec)
      self._num_actions = 3
      self._greedy_action = 1
      self._action_spec = tensor_spec.BoundedTensorSpec(
          (), tf.int32, 0, self._num_actions - 1
      )
      self._policy = fixed_policy.FixedPolicy(
          np.asarray(self._greedy_action, dtype=np.int32),
          self._time_step_spec,
          self._action_spec,
      )
      self._bandit_policy_type = tf.constant([1, 1])
      self._bandit_policy_type_spec = (
          policy_util.create_bandit_policy_type_tensor_spec(shape=())
      )
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      self._time_step = ts.restart(observations, batch_size=2)
  
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 1 for calling the EpsilonGreedyPolicyTest obj's underlying member method code with example usage: obj.setUp() without return types