class_docstr: Runner for evaluating using a fixed number of episodes rather than steps.
docstr: Specify the number of evaluation episodes.
code: def __init__(
      self,
      base_dir,
      create_agent_fn,
      num_eval_episodes=100,
      max_noops=30,
  ):
      """Specify the number of evaluation episodes."""
      super().__init__(base_dir, create_agent_fn)
      self._num_eval_episodes = num_eval_episodes
      logging.info("Num evaluation episodes: %d", num_eval_episodes)
      self._evaluation_steps = None
      self._max_noops = max_noops
  
file_path: dopamine/dopamine/labs/atari_100k/eval_run_experiment.py
imports: import sys
  from absl import logging
  from dopamine.discrete_domains import run_experiment
  import gin
  import jax
label_desc: Use image node_id 1 to create a new MaxEpisodeEvalRunner object from inherited base classes: run_experiment with example: obj = MaxEpisodeEvalRunner(base_dir, create_agent_fn, num_eval_episodes, max_noops)