class_docstr: This replay buffer implements a FIFO queue.
  
  Sometimes, e.g. for offline use cases, it may be desirable to use
  off-policy algorithms without a Replay Buffer.
  This FifoReplayBuffer can be used in-place to achieve the same effect
  without having to introduce separate algorithm execution branches.
  
  For simplicity and efficiency reasons, this replay buffer stores incoming
  sample batches as-is, and returns them one at time.
  This is to avoid any additional load when this replay buffer is used.
docstr: Initializes a FifoReplayBuffer.
  
  Args:
      ``*args``   : Forward compatibility args.
      ``**kwargs``: Forward compatibility kwargs.
docstr_tok: ["Initializes","a","FifoReplayBuffer",".","Args",":","``","*","args","``",":","Forward","compatibility","args",".","``","*","*","kwargs","``",":","Forward","compatibility","kwargs","."]
code: def __init__(self, *args, **kwargs):
      """Initializes a FifoReplayBuffer.
  
      Args:
          ``*args``   : Forward compatibility args.
          ``**kwargs``: Forward compatibility kwargs.
      """
      # Completely by-passing underlying ReplayBuffer by setting its
      # capacity to 1 (lowest allowed capacity).
      ReplayBuffer.__init__(self, 1, StorageUnit.FRAGMENTS, **kwargs)
  
      self._queue = []
  
file_path: ray/rllib/utils/replay_buffers/fifo_replay_buffer.py
imports: import numpy
  from typing import Any, Dict, Optional
  from ray.rllib.policy.sample_batch import MultiAgentBatch
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.replay_buffers.replay_buffer import ReplayBuffer, StorageUnit
  from ray.rllib.utils.typing import SampleBatchType
  from ray.util.annotations import DeveloperAPI
label_desc: Use image node_id 1 to create a new FifoReplayBuffer object from inherited base classes: ReplayBuffer with example: obj = FifoReplayBuffer()