docstr: Setup the logger for the agent
  
  :return: None
docstr_tok: ["Setup","the","logger","for","the","agent",":","return",":","None"]
code: def setup_logger(self) -> None:
      """
      Setup the logger for the agent
  
      :return: None
      """
      # dump documentation
      logger_prefix = "{graph_name}.{level_name}.{agent_full_id}".format(
          graph_name=self.parent_level_manager.parent_graph_manager.name,
          level_name=self.parent_level_manager.name,
          agent_full_id=".".join(self.full_name_id.split("/")),
      )
      self.agent_logger.set_index_name(
          self.parent_level_manager.parent_graph_manager.time_metric.value.name
      )
      self.agent_logger.set_logger_filenames(
          self.ap.task_parameters.experiment_path,
          logger_prefix=logger_prefix,
          add_timestamp=True,
          task_id=self.task_id,
      )
      if self.ap.visualization.dump_in_episode_signals:
          self.agent_episode_logger.set_logger_filenames(
              self.ap.task_parameters.experiment_path,
              logger_prefix=logger_prefix,
              add_timestamp=True,
              task_id=self.task_id,
          )
  
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 4 for calling the Agent obj's underlying member method code with example usage: obj.setup_logger() without return types