code: def training(
      self,
      *,
      lr_schedule: Optional[
          List[List[Union[int, float]]]
      ] = NotProvided,
      use_critic: Optional[bool] = NotProvided,
      use_gae: Optional[bool] = NotProvided,
      lambda_: Optional[float] = NotProvided,
      grad_clip: Optional[float] = NotProvided,
      vf_loss_coeff: Optional[float] = NotProvided,
      entropy_coeff: Optional[float] = NotProvided,
      entropy_coeff_schedule: Optional[
          List[List[Union[int, float]]]
      ] = NotProvided,
      sample_async: Optional[bool] = NotProvided,
      **kwargs,
  ) -> "A3CConfig":
      super().training(**kwargs)
  
      if lr_schedule is not NotProvided:
          self.lr_schedule = lr_schedule
      if use_critic is not NotProvided:
          self.lr_schedule = use_critic
      if use_gae is not NotProvided:
          self.use_gae = use_gae
      if lambda_ is not NotProvided:
          self.lambda_ = lambda_
      if grad_clip is not NotProvided:
          self.grad_clip = grad_clip
      if vf_loss_coeff is not NotProvided:
          self.vf_loss_coeff = vf_loss_coeff
      if entropy_coeff is not NotProvided:
          self.entropy_coeff = entropy_coeff
      if entropy_coeff_schedule is not NotProvided:
          self.entropy_coeff_schedule = entropy_coeff_schedule
  
      # Deprecated settings.
      if sample_async is not False:
          deprecation_warning(
              old="A3CConfig.training(sample_async=True)",
              help="AsyncSampler is not supported anymore.",
              error=True,
          )
  
      return self
  
file_path: ray/rllib/algorithms/a3c/a3c.py
imports: from typing import List, Optional, Union
  from ray.rllib.algorithms.algorithm import Algorithm
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig, NotProvided
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.deprecation import ALGO_DEPRECATION_WARNING, Deprecated, deprecation_warning
label_desc: Use image node_id 2 for calling the A3CConfig obj's underlying member method code with example usage: obj.training() and returns: self