docstr: Allows agents to store additional information when saving checkpoints.
  
  :param checkpoint_prefix: The prefix of the checkpoint file to save
  :return: None
docstr_tok: ["Allows","agents","to","store","additional","information","when","saving","checkpoints",".",":","param","checkpoint_prefix",":","The","prefix","of","the","checkpoint","file","to","save",":","return",":","None"]
code: def save_checkpoint(self, checkpoint_prefix: str) -> None:
      """
      Allows agents to store additional information when saving checkpoints.
  
      :param checkpoint_prefix: The prefix of the checkpoint file to save
      :return: None
      """
      checkpoint_dir = self.ap.task_parameters.checkpoint_save_dir
  
      checkpoint_prefix = ".".join(
          [checkpoint_prefix] + self.full_name_id.split("/")
      )  # adds both level name and agent name
  
      self.input_filter.save_state_to_checkpoint(
          checkpoint_dir, checkpoint_prefix
      )
      self.output_filter.save_state_to_checkpoint(
          checkpoint_dir, checkpoint_prefix
      )
      self.pre_network_filter.save_state_to_checkpoint(
          checkpoint_dir, checkpoint_prefix
      )
  
imports: import copy
  import random
  from collections import OrderedDict
  from typing import Dict, List, Union, Tuple
  import numpy
  from six.moves import range
  from rl_coach.agents.agent_interface import AgentInterface
  from rl_coach.architectures.network_wrapper import NetworkWrapper
  from rl_coach.base_parameters import AgentParameters, Device, DeviceType, DistributedTaskParameters, Frameworks
  from rl_coach.core_types import RunPhase, PredictionType, EnvironmentEpisodes, ActionType, Batch, Episode, StateType
  from rl_coach.core_types import Transition, ActionInfo, TrainingSteps, EnvironmentSteps, EnvResponse
  from rl_coach.logger import screen, Logger, EpisodeLogger
  from rl_coach.memories.episodic.episodic_experience_replay import EpisodicExperienceReplay
  from rl_coach.saver import SaverCollection
  from rl_coach.spaces import SpacesDefinition, VectorObservationSpace, GoalsSpace, AttentionActionSpace
  from rl_coach.utils import Signal, force_list
  from rl_coach.utils import dynamic_import_and_instantiate_module_from_params
  from rl_coach.memories.backend.memory_impl import get_memory_backend
  from rl_coach.core_types import TimeTypes
  from rl_coach.off_policy_evaluators.ope_manager import OpeManager
  from rl_coach.core_types import PickledReplayBuffer, CsvDataset
label_desc: Use image node_id 37 for calling the Agent obj's underlying member method code with example usage: obj.save_checkpoint(checkpoint_prefix) without return types