code: def test_clip_reward_connector(self):
      ctx = ConnectorContext()
  
      c = ClipRewardAgentConnector(ctx, limit=2.0)
      name, params = c.to_state()
  
      self.assertEqual(name, "ClipRewardAgentConnector")
      self.assertAlmostEqual(params["limit"], 2.0)
  
      restored = get_connector(name, ctx, params)
      self.assertTrue(isinstance(restored, ClipRewardAgentConnector))
  
      d = AgentConnectorDataType(
          0,
          1,
          {
              SampleBatch.REWARDS: 5.8,
          },
      )
      clipped = restored([d])
  
      self.assertEqual(len(clipped), 1)
      self.assertEqual(clipped[0].data[SampleBatch.REWARDS], 2.0)
  
imports: import gymnasium
  from gymnasium.spaces import Box
  import numpy
  import tree
  import unittest
  from ray.rllib.algorithms.ppo.ppo import PPOConfig
  from ray.rllib.connectors.agent.clip_reward import ClipRewardAgentConnector
  from ray.rllib.connectors.agent.lambdas import FlattenDataAgentConnector
  from ray.rllib.connectors.agent.obs_preproc import ObsPreprocessorConnector
  from ray.rllib.connectors.agent.pipeline import AgentConnectorPipeline
  from ray.rllib.connectors.agent.state_buffer import StateBufferConnector
  from ray.rllib.connectors.agent.view_requirement import ViewRequirementAgentConnector
  from ray.rllib.connectors.connector import ConnectorContext
  from ray.rllib.connectors.registry import get_connector
  from ray.rllib.policy.view_requirement import ViewRequirement
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.test_utils import check
  from ray.rllib.utils.typing import ActionConnectorDataType, AgentConnectorDataType, AgentConnectorsOutput
  from ray.rllib.connectors.agent.mean_std_filter import MeanStdObservationFilterAgentConnector
label_desc: Use image node_id 3 for calling the TestAgentConnector obj's underlying member method code with example usage: obj.test_clip_reward_connector() without return types