class_docstr: Abstract base class for all of RLlib's replay buffers.
  
  Mainly defines the `add()` and `sample()` methods that every buffer class
  must implement to be usable by an Algorithm.
  Buffers may determine on all the implementation details themselves, e.g.
  whether to store single timesteps, episodes, or episode fragments or whether
  to return fixed batch sizes or per-call defined ones.
class_docstr_tok: ["Abstract","base","class","for","all","of","RLlib","'s","replay","buffers",".","Mainly","defines","the","`","add","(",")","`","and","`","sample","(",")","`","methods","that","every","buffer","class","must","implement","to","be","usable","by","an","Algorithm",".","Buffers","may","determine","on","all","the","implementation","details","themselves",",","e.g",".","whether","to","store","single","timesteps",",","episodes",",","or","episode","fragments","or","whether","to","return","fixed","batch","sizes","or","per-call","defined","ones","."]
docstr: Returns all local state in a dict.
  
  Returns:
      The serializable local state.
docstr_tok: ["Returns","all","local","state","in","a","dict",".","Returns",":","The","serializable","local","state","."]
code: def get_state(self) -> Dict[str, Any]:
      """Returns all local state in a dict.
  
      Returns:
          The serializable local state.
      """
  
file_path: ray/python/ray/rllib/utils/replay_buffers/base.py
imports: from abc import ABCMeta, abstractmethod
  import platform
  from typing import Any, Dict, Optional
  from ray.util.annotations import DeveloperAPI
label_desc: Use image node_id 4 for calling the ReplayBufferInterface obj's underlying member method code with example usage: obj.get_state() without return types