code: def v1_to_v2_action(
      actions: TensorStructType, states: StateBatches, fetches: Dict
  ) -> PolicyOutputType:
      return np.hstack((actions, [0])), states, fetches
  
imports: import gymnasium
  import numpy
  import os
  import tempfile
  from typing import Dict
  from ray.rllib.connectors.connector import ConnectorContext
  from ray.rllib.connectors.action.lambdas import register_lambda_action_connector
  from ray.rllib.connectors.agent.lambdas import register_lambda_agent_connector
  from ray.rllib.examples.connectors.prepare_checkpoint import create_appo_cartpole_checkpoint
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.policy import local_policy_inference
  from ray.rllib.utils.typing import PolicyOutputType, StateBatches, TensorStructType
label_desc: Use image node_id 2 for calling a global function with example usage: v1_to_v2_action(actions, states, fetches) and returns: np,  states,  fetches