class_docstr: Defines a common interface of replay buffer.
  
  You can append transitions to the replay buffer and later sample from it.
  Replay buffers are typically used in experience replay.
class_docstr_tok: ["Defines","a","common","interface","of","replay","buffer",".","You","can","append","transitions","to","the","replay","buffer","and","later","sample","from","it",".","Replay","buffers","are","typically","used","in","experience","replay","."]
docstr: Append a transition to this replay buffer.
  
  Args:
      state: s_t
      action: a_t
      reward: r_t
      next_state: s_{t+1} (can be None if terminal)
      next_action: a_{t+1} (can be None for off-policy algorithms)
      is_state_terminal (bool)
      env_id (object): Object that is unique to each env. It indicates
          which env a given transition came from in multi-env training.
      **kwargs: Any other information to store.
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code: def append(
      self,
      state,
      action,
      reward,
      next_state=None,
      next_action=None,
      is_state_terminal=False,
      env_id=0,
      **kwargs,
  ):
      """Append a transition to this replay buffer.
  
      Args:
          state: s_t
          action: a_t
          reward: r_t
          next_state: s_{t+1} (can be None if terminal)
          next_action: a_{t+1} (can be None for off-policy algorithms)
          is_state_terminal (bool)
          env_id (object): Object that is unique to each env. It indicates
              which env a given transition came from in multi-env training.
          **kwargs: Any other information to store.
      """
      raise NotImplementedError
  
imports: from abc import ABCMeta, abstractmethod, abstractproperty
  from typing import Optional
  import numpy
  import torch
  from pfrl.utils.batch_states import batch_states
  from pfrl.utils.recurrent import concatenate_recurrent_states, flatten_sequences_time_first, recurrent_state_from_numpy
label_desc: Use image node_id 1 for calling the AbstractReplayBuffer obj's underlying member method code with example usage: obj.append(state, action, reward, next_state, next_action, is_state_terminal, env_id) without return types