docstr: Args:
      algorithm (`parl.Algorithm`): algorithm to be used in this agent.
      config (dict): config file describing the training hyper-parameters(see a2c_config.py)
docstr_tok: ["Args",":","algorithm","(","`","parl.Algorithm","`",")",":","algorithm","to","be","used","in","this","agent",".","config","(","dict",")",":","config","file","describing","the","training","hyper-parameters","(","see","a2c_config.py",")"]
code: def __init__(self, algorithm, config):
      """
  
      Args:
          algorithm (`parl.Algorithm`): algorithm to be used in this agent.
          config (dict): config file describing the training hyper-parameters(see a2c_config.py)
      """
  
      self.obs_shape = config["obs_shape"]
      super(AtariAgent, self).__init__(algorithm)
  
      self.lr_scheduler = LinearDecayScheduler(
          config["start_lr"], config["max_sample_steps"]
      )
  
      self.entropy_coeff_scheduler = PiecewiseScheduler(
          config["entropy_coeff_scheduler"]
      )
  
file_path: PARL/examples/A2C/atari_agent.py
imports: import numpy
  import parl
  from parl.utils import machine_info
  from parl.utils.scheduler import PiecewiseScheduler, LinearDecayScheduler
  import paddle
label_desc: Use image node_id 1 to create a new AtariAgent object from inherited base classes: parl with example: obj = AtariAgent(algorithm, config)