code: def __init__(self, runner, model, buffer, log_interval):
      self.runner = runner
      self.model = model
      self.buffer = buffer
      self.log_interval = log_interval
      self.tstart = None
      self.episode_stats = EpisodeStats(runner.nsteps, runner.nenv)
      self.steps = None
  
imports: import time
  import functools
  import numpy
  import tensorflow
  from baselines import logger
  from baselines.common import set_global_seeds
  from baselines.common.policies import build_policy
  from baselines.common.tf_util import get_session, save_variables, load_variables
  from baselines.common.vec_env.vec_frame_stack import VecFrameStack
  from baselines.a2c.utils import batch_to_seq, seq_to_batch
  from baselines.a2c.utils import cat_entropy_softmax
  from baselines.a2c.utils import Scheduler, find_trainable_variables
  from baselines.a2c.utils import EpisodeStats
  from baselines.a2c.utils import get_by_index, check_shape, avg_norm, gradient_add, q_explained_variance
  from baselines.acer.buffer import Buffer
  from baselines.acer.runner import Runner
label_desc: Use image node_id 1 to create a new Acer object  with example: obj = Acer(runner, model, buffer, log_interval)