code: def compute_actions(
      self,
      obs_batch: Union[List[TensorStructType], TensorStructType],
      state_batches: Optional[List[TensorType]] = None,
      prev_action_batch: Union[
          List[TensorStructType], TensorStructType
      ] = None,
      prev_reward_batch: Union[
          List[TensorStructType], TensorStructType
      ] = None,
      info_batch: Optional[Dict[str, list]] = None,
      episodes: Optional[List["Episode"]] = None,
      explore: Optional[bool] = None,
      timestep: Optional[int] = None,
      **kwargs,
  ) -> Tuple[TensorType, List[TensorType], Dict[str, TensorType]]:
      return obs_batch.argmax(axis=1), [], {}
  
imports: import ray
  import unittest
  from typing import Dict, List, Optional, Union, Tuple
  import numpy
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig
  from ray.rllib.algorithms.callbacks import DefaultCallbacks
  from ray.rllib.env.multi_agent_env import MultiAgentEnv
  from ray.rllib.evaluation.rollout_worker import RolloutWorker
  from ray.rllib.evaluation.episode import Episode
  from ray.rllib.examples.env.mock_env import MockEnv3
  from ray.rllib.policy import Policy
  from ray.rllib.utils import override
  from ray.rllib.utils.typing import TensorStructType, TensorType
label_desc: Use image node_id 1 for calling the EchoPolicy obj's underlying member method code with example usage: obj.compute_actions(obs_batch, state_batches, prev_action_batch, prev_reward_batch, info_batch, episodes, explore, timestep) and returns: obs_batch,  list,  dict