docstr: Load memory transitions from a file.
  
  :return: None
docstr_tok: ["Load","memory","transitions","from","a","file",".",":","return",":","None"]
code: def load_memory_from_file(self):
      """
      Load memory transitions from a file.
  
      :return: None
      """
  
      if isinstance(
          self.ap.memory.load_memory_from_file_path, PickledReplayBuffer
      ):
          screen.log_title(
              "Loading a pickled replay buffer. Pickled file path: {}".format(
                  self.ap.memory.load_memory_from_file_path.filepath
              )
          )
          self.memory.load_pickled(
              self.ap.memory.load_memory_from_file_path.filepath
          )
      elif isinstance(
          self.ap.memory.load_memory_from_file_path, CsvDataset
      ):
          screen.log_title(
              "Loading a replay buffer from a CSV file. CSV file path: {}".format(
                  self.ap.memory.load_memory_from_file_path.filepath
              )
          )
          self.memory.load_csv(
              self.ap.memory.load_memory_from_file_path,
              self.input_filter,
          )
      else:
          raise ValueError(
              "Trying to load a replay buffer using an unsupported method - {}. ".format(
                  self.ap.memory.load_memory_from_file_path
              )
          )
  
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 7 for calling the Agent obj's underlying member method code with example usage: obj.load_memory_from_file() without return types