docstr: Collection of all checkpoints for the network (typically only one checkpoint)
  :param parent_path_suffix: path suffix of the parent of the network
      (e.g. could be name of level manager plus name of agent)
  :return: checkpoint collection for the network
code: def collect_savers(self, parent_path_suffix: str) -> SaverCollection:
      """
      Collection of all checkpoints for the network (typically only one checkpoint)
      :param parent_path_suffix: path suffix of the parent of the network
          (e.g. could be name of level manager plus name of agent)
      :return: checkpoint collection for the network
      """
      savers = SaverCollection()
      if not self.distributed_training:
          savers.add(GlobalVariableSaver(self.name))
      return savers
  
imports: import os
  import time
  from typing import Any, List, Tuple, Dict
  import numpy
  import tensorflow
  from rl_coach.architectures.architecture import Architecture
  from rl_coach.architectures.tensorflow_components.savers import GlobalVariableSaver
  from rl_coach.base_parameters import AgentParameters, DistributedTaskParameters
  from rl_coach.core_types import GradientClippingMethod
  from rl_coach.saver import SaverCollection
  from rl_coach.spaces import SpacesDefinition
  from rl_coach.utils import force_list, squeeze_list, start_shell_command_and_wait
label_desc: Use image node_id 26 for calling the TensorFlowArchitecture obj's underlying member method code with example usage: obj.collect_savers(parent_path_suffix) and returns: savers