code: def training(
      self,
      *,
      sgd_minibatch_size: Optional[int] = NotProvided,
      shuffle_sequences: Optional[bool] = NotProvided,
      num_sgd_iter: Optional[int] = NotProvided,
      replay_buffer_config: Optional[dict] = NotProvided,
      lr: Optional[float] = NotProvided,
      lr_schedule: Optional[
          List[List[Union[int, float]]]
      ] = NotProvided,
      vf_share_layers: Optional[bool] = NotProvided,
      mcts_config: Optional[dict] = NotProvided,
      num_steps_sampled_before_learning_starts: Optional[
          int
      ] = NotProvided,
      model: Optional[dict] = NotProvided,
      **kwargs,
  ) -> "LeelaChessZeroConfig":
      super().training(**kwargs)
  
      if sgd_minibatch_size is not NotProvided:
          self.sgd_minibatch_size = sgd_minibatch_size
      if shuffle_sequences is not NotProvided:
          self.shuffle_sequences = shuffle_sequences
      if num_sgd_iter is not NotProvided:
          self.num_sgd_iter = num_sgd_iter
      if replay_buffer_config is not NotProvided:
          self.replay_buffer_config = replay_buffer_config
      if lr is not NotProvided:
          self.lr = lr
      if lr_schedule is not NotProvided:
          self.lr_schedule = lr_schedule
      if vf_share_layers is not NotProvided:
          self.vf_share_layers = vf_share_layers
      if mcts_config is not NotProvided:
          # only assign provided keys
          for k, v in mcts_config.items():
              self.mcts_config[k] = v
      if num_steps_sampled_before_learning_starts is not NotProvided:
          self.num_steps_sampled_before_learning_starts = (
              num_steps_sampled_before_learning_starts
          )
      if model is not NotProvided:
          self.model = model
  
      return self
  
file_path: ray/rllib/algorithms/leela_chess_zero/leela_chess_zero.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.replay_buffers import PrioritizedReplayBuffer
  from ray.rllib.utils.deprecation import DEPRECATED_VALUE, Deprecated, ALGO_DEPRECATION_WARNING
label_desc: Use image node_id 2 for calling the LeelaChessZeroConfig obj's underlying member method code with example usage: obj.training() and returns: self