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: Return the number of transitions in the buffer.
  
  Returns:
      Number of transitions in the buffer.
docstr_tok: ["Return","the","number","of","transitions","in","the","buffer",".","Returns",":","Number","of","transitions","in","the","buffer","."]
code: def __len__(self):
      """Return the number of transitions in the buffer.
  
      Returns:
          Number of transitions in the buffer.
      """
      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 3 for calling the AbstractReplayBuffer obj's underlying member method code with example usage: obj.__len__() without return types