docstr: Collect all of agent's network savers
  :param parent_path_suffix: path suffix of the parent of the agent
  (could be name of level manager or composite agent)
  :return: collection of all agent savers
docstr_tok: ["Collect","all","of","agent","'s","network","savers",":","param","parent_path_suffix",":","path","suffix","of","the","parent","of","the","agent","(","could","be","name","of","level","manager","or","composite","agent",")",":","return",":","collection","of","all","agent","savers"]
code: def collect_savers(self, parent_path_suffix: str) -> SaverCollection:
      """
      Collect all of agent's network savers
      :param parent_path_suffix: path suffix of the parent of the agent
      (could be name of level manager or composite agent)
      :return: collection of all agent savers
      """
      parent_path_suffix = "{}.{}".format(parent_path_suffix, self.name)
      savers = SaverCollection()
      for network in self.networks.values():
          savers.update(network.collect_savers(parent_path_suffix))
      return savers
  
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 41 for calling the Agent obj's underlying member method code with example usage: obj.collect_savers(parent_path_suffix) and returns: savers