code: def __call__(
      self, replay_buffer: ReplayBuffer, transition: Transition
  ):
      transition_dict = transition.asdict()
      obs = transition_dict.pop("observation")
      user = obs["user"]
  
      kwargs = {}
  
      if self.box_keys or self.discrete_keys:
          doc_obs = obs["doc"]
          for k in self.box_keys:
              kwargs[f"doc_{k}"] = np.stack(
                  [v[k] for v in doc_obs.values()]
              )
          for k in self.discrete_keys:
              kwargs[f"doc_{k}"] = np.array(
                  [v[k] for v in doc_obs.values()]
              )
      else:
          kwargs["doc"] = np.stack(list(obs["doc"].values()))
  
      # Augmentation
  
      if self.augmentation_box_keys or self.augmentation_discrete_keys:
          aug_obs = obs["augmentation"]
          for k in self.augmentation_box_keys:
              kwargs[f"augmentation_{k}"] = np.stack(
                  [v[k] for v in aug_obs.values()]
              )
          for k in self.augmentation_discrete_keys:
              kwargs[f"augmentation_{k}"] = np.array(
                  [v[k] for v in aug_obs.values()]
              )
  
      # Responses
  
      response = obs["response"]
      # We need to handle None below because the first state won't have response
      for k, d in self.response_box_keys:
          if response is not None:
              kwargs[f"response_{k}"] = np.stack(
                  [v[k] for v in response]
              )
          else:
              kwargs[f"response_{k}"] = np.zeros(
                  (self.num_responses, *d), dtype=np.float32
              )
      for k, _n in self.response_discrete_keys:
          if response is not None:
              kwargs[f"response_{k}"] = np.array(
                  [v[k] for v in response]
              )
          else:
              kwargs[f"response_{k}"] = np.zeros(
                  (self.num_responses,), dtype=np.int64
              )
  
      transition_dict.update(kwargs)
      replay_buffer.add(observation=user, **transition_dict)
  
file_path: ReAgent/reagent/gym/preprocessors/replay_buffer_inserters.py
imports: import logging
  from typing import Callable, List, Tuple
  import gym
  import numpy
  from reagent.gym.types import Transition
  from reagent.replay_memory.circular_replay_buffer import ReplayBuffer
label_desc: Use image node_id 3 for calling the RecSimReplayBufferInserter obj's underlying member method code with example usage: obj.__call__(replay_buffer, transition) without return types