code: def testTupleShapedActionsMatchShapes(
      self, action_shape: Tuple[int, ...], eval_mode: bool
  ):
      agent = create_agent(
          action_shape=action_shape, eval_mode=eval_mode
      )
      observation = np.zeros(OBSERVATION_SHAPE)
  
      action1 = agent.begin_episode(observation)
      action2 = agent.step(reward=0.0, observation=observation)
  
      self.assertIsInstance(action1, np.ndarray)
      self.assertIsInstance(action2, np.ndarray)
      self.assertEqual(tuple(action1.shape), action_shape)
      self.assertEqual(tuple(action2.shape), action_shape)
  
imports: import copy
  import functools
  import operator
  import random
  from typing import Any, Tuple, Union
  from unittest import mock
  from absl.testing import absltest
  from absl.testing import parameterized
  from dopamine.jax.agents.sac import sac_agent
  import flax
  import gin
  import jax
  import numpy
label_desc: Use image node_id 5 for calling the SacAgentTest obj's underlying member method code with example usage: obj.testTupleShapedActionsMatchShapes(action_shape, eval_mode) without return types