class_docstr: Reads input experiences from an existing sampler.
class_docstr_tok: ["Reads","input","experiences","from","an","existing","sampler","."]
docstr: Returns list of extra batches since the last call to this method.
  
  The list will contain all SampleBatches or
  MultiAgentBatches that the user has provided thus-far. Users can
  add these "extra batches" to an episode by calling the episode's
  `add_extra_batch([SampleBatchType])` method. This can be done from
  inside an overridden `Policy.compute_actions_from_input_dict(...,
  episodes)` or from a custom callback's `on_episode_[start|step|end]()`
  methods.
  
  Returns:
      List of SamplesBatches or MultiAgentBatches provided thus-far by
      the user since the last call to this method.
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code: def get_extra_batches(self) -> List[SampleBatchType]:
      """Returns list of extra batches since the last call to this method.
  
      The list will contain all SampleBatches or
      MultiAgentBatches that the user has provided thus-far. Users can
      add these "extra batches" to an episode by calling the episode's
      `add_extra_batch([SampleBatchType])` method. This can be done from
      inside an overridden `Policy.compute_actions_from_input_dict(...,
      episodes)` or from a custom callback's `on_episode_[start|step|end]()`
      methods.
  
      Returns:
          List of SamplesBatches or MultiAgentBatches provided thus-far by
          the user since the last call to this method.
      """
      raise NotImplementedError
  
imports: import logging
  import queue
  import time
  from abc import ABCMeta, abstractmethod
  from collections import defaultdict, namedtuple
  from typing import TYPE_CHECKING, Any, Callable, Dict, Iterator, List, Optional, Set, Tuple, Type, Union
  import numpy
  import tree
  from ray.rllib.env.base_env import ASYNC_RESET_RETURN, BaseEnv, convert_to_base_env
  from ray.rllib.evaluation.collectors.sample_collector import SampleCollector
  from ray.rllib.evaluation.collectors.simple_list_collector import SimpleListCollector
  from ray.rllib.evaluation.env_runner_v2 import EnvRunnerV2, _fetch_atari_metrics, _get_or_raise, _PerfStats
  from ray.rllib.evaluation.episode import Episode
  from ray.rllib.evaluation.metrics import RolloutMetrics
  from ray.rllib.offline import InputReader
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.policy_map import PolicyMap
  from ray.rllib.policy.sample_batch import SampleBatch, concat_samples
  from ray.rllib.utils.annotations import DeveloperAPI, override
  from ray.rllib.utils.debug import summarize
  from ray.rllib.utils.deprecation import deprecation_warning, DEPRECATED_VALUE
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.numpy import convert_to_numpy, make_action_immutable
  from ray.rllib.utils.spaces.space_utils import clip_action, unbatch, unsquash_action
  from ray.rllib.utils.typing import AgentID, EnvActionType, EnvID, EnvInfoDict, EnvObsType, MultiEnvDict, PolicyID, SampleBatchType, TensorStructType
  from ray.util.debug import log_once
label_desc: Use image node_id 4 for calling the SamplerInput obj's underlying member method code with example usage: obj.get_extra_batches() without return types