code: def training(
      self,
      *,
      replay_buffer_capacity: Optional[int] = NotProvided,
      replay_buffer_replay_ratio: Optional[float] = NotProvided,
      max_requests_in_flight_per_sampler_worker: Optional[
          int
      ] = NotProvided,
      max_requests_in_flight_per_learner_worker: Optional[
          int
      ] = NotProvided,
      timeout_s_sampler_manager: Optional[float] = NotProvided,
      timeout_s_learner_manager: Optional[float] = NotProvided,
      league_builder_config: Optional[Dict[str, Any]] = NotProvided,
      max_num_policies_to_train: Optional[int] = NotProvided,
      **kwargs,
  ) -> "AlphaStarConfig":
      super().training(**kwargs)
  
      # TODO: Unify the buffer API, then clean up our existing
      #  implementations of different buffers.
      if replay_buffer_capacity is not NotProvided:
          self.replay_buffer_capacity = replay_buffer_capacity
      if replay_buffer_replay_ratio is not NotProvided:
          self.replay_buffer_replay_ratio = replay_buffer_replay_ratio
      if timeout_s_sampler_manager is not NotProvided:
          self.timeout_s_sampler_manager = timeout_s_sampler_manager
      if timeout_s_learner_manager is not NotProvided:
          self.timeout_s_learner_manager = timeout_s_learner_manager
      if league_builder_config is not NotProvided:
          # Override entire `league_builder_config` if `type` key changes.
          # Update, if `type` key remains the same or is not specified.
          new_league_builder_config = deep_update(
              {"league_builder_config": self.league_builder_config},
              {"league_builder_config": league_builder_config},
              False,
              ["league_builder_config"],
              ["league_builder_config"],
          )
          self.league_builder_config = new_league_builder_config[
              "league_builder_config"
          ]
      if max_num_policies_to_train is not NotProvided:
          self.max_num_policies_to_train = max_num_policies_to_train
      if max_requests_in_flight_per_sampler_worker is not NotProvided:
          self.max_requests_in_flight_per_sampler_worker = (
              max_requests_in_flight_per_sampler_worker
          )
      if max_requests_in_flight_per_learner_worker is not NotProvided:
          self.max_requests_in_flight_per_learner_worker = (
              max_requests_in_flight_per_learner_worker
          )
  
      return self
  
file_path: ray/python/ray/rllib/algorithms/alpha_star/alpha_star.py
imports: from typing import Any, Dict, Optional
  import ray.rllib.algorithms.appo.appo
  from ray.rllib.algorithms.algorithm_config import NotProvided
  from ray.rllib.utils import deep_update
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.deprecation import Deprecated, ALGO_DEPRECATION_WARNING
label_desc: Use image node_id 2 for calling the AlphaStarConfig obj's underlying member method code with example usage: obj.training() and returns: self