class_docstr: Array-like object that lazily concat multiple frames.
  
  This object ensures that common frames between the observations are only
  stored once.  It exists purely to optimize memory usage which can be huge
  for DQN's 1M frames replay buffers.
  
  This object should only be converted to numpy array before being passed to
  the model.
  
  You'd not believe how complex the previous solution was.
class_docstr_tok: ["Array-like","object","that","lazily","concat","multiple","frames",".","This","object","ensures","that","common","frames","between","the","observations","are","only","stored","once",".","It","exists","purely","to","optimize","memory","usage","which","can","be","huge","for","DQN","'s","1M","frames","replay","buffers",".","This","object","should","only","be","converted","to","numpy","array","before","being","passed","to","the","model",".","You","'d","not","believe","how","complex","the","previous","solution","was","."]
code: def __init__(self, frames, stack_axis=2):
      self.stack_axis = stack_axis
      self._frames = frames
  
imports: from collections import deque
  import gym
  import numpy
  from gym import spaces
  from packaging import version
  import pfrl
label_desc: Use image node_id 1 to create a new LazyFrames object from inherited base classes: object with example: obj = LazyFrames(frames, stack_axis)