class_docstr: This wrapper will normalize observations s.t. each coordinate is centered with unit variance.
  
  Note:
      The normalization depends on past trajectories and observations will not be normalized correctly if the wrapper was
      newly instantiated or the policy was changed recently.
class_docstr_tok: ["This","wrapper","will","normalize","observations","s.t",".","each","coordinate","is","centered","with","unit","variance",".","Note",":","The","normalization","depends","on","past","trajectories","and","observations","will","not","be","normalized","correctly","if","the","wrapper","was","newly","instantiated","or","the","policy","was","changed","recently","."]
docstr: Steps through the environment and normalizes the observation.
docstr_tok: ["Steps","through","the","environment","and","normalizes","the","observation","."]
code: def step(self, action):
      """Steps through the environment and normalizes the observation."""
      obs, rews, terminateds, truncateds, infos = self.env.step(action)
      if self.is_vector_env:
          obs = self.normalize(obs)
      else:
          obs = self.normalize(np.array([obs]))[0]
      return obs, rews, terminateds, truncateds, infos
  
file_path: gym/gym/wrappers/normalize.py
imports: import numpy
  import gym
label_desc: Use image node_id 2 for calling the NormalizeObservation obj's underlying member method code with example usage: obj.step(action) and returns: obs,  rews,  terminateds,  truncateds,  infos