class_docstr: Divide frame values by 255.0 and return them as np.float32.
  
  Especially, when the original env.observation_space is np.uint8,
  this wrapper converts frame values into [0.0, 1.0] of dtype np.float32.
class_docstr_tok: ["Divide","frame","values","by","255.0","and","return","them","as","np.float32",".","Especially",",","when","the","original","env.observation_space","is","np.uint8",",","this","wrapper","converts","frame","values","into","[","0.0",",","1.0","]","of","dtype","np.float32","."]
code: def observation(self, observation):
      # careful! This undoes the memory optimization, use
      # with smaller replay buffers only.
      return np.array(observation).astype(np.float32) / self.scale
  
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 2 for calling the ScaledFloatFrame obj's underlying member method code with example usage: obj.observation(observation) and returns: unknown