code: def training(
      self,
      *,
      microbatch_size: Optional[int] = NotProvided,
      **kwargs,
  ) -> "A2CConfig":
      super().training(**kwargs)
  
      if microbatch_size is not NotProvided:
          self.microbatch_size = microbatch_size
  
      return self
  
file_path: ray/rllib/algorithms/a2c/a2c.py
imports: from typing import Optional
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig, NotProvided
  from ray.rllib.algorithms.a3c.a3c import A3CConfig, A3C
  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 A2CConfig obj's underlying member method code with example usage: obj.training() and returns: self