class_docstr: Sample Runner class to generate visualizations.
class_docstr_tok: ["Sample","Runner","class","to","generate","visualizations","."]
code: def _initialize_checkpointer_and_maybe_resume(
      self, checkpoint_file_prefix
  ):
      self._agent.reload_checkpoint(
          self._trained_agent_ckpt_path, self._use_legacy_checkpoint
      )
      self._start_iteration = 0
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import logging
  from dopamine.agents.dqn import dqn_agent
  from dopamine.agents.rainbow import rainbow_agent
  from dopamine.discrete_domains import atari_lib
  from dopamine.discrete_domains import iteration_statistics
  from dopamine.discrete_domains import run_experiment
  from dopamine.utils import agent_visualizer
  from dopamine.utils import atari_plotter
  from dopamine.utils import bar_plotter
  from dopamine.utils import line_plotter
  import gin
  import numpy
  import tensorflow
  import tf_slim
label_desc: Use image node_id 2 for calling the MyRunner obj's underlying member method code with example usage: obj._initialize_checkpointer_and_maybe_resume(checkpoint_file_prefix) without return types