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: Resets the environment and normalizes the observation.
docstr_tok: ["Resets","the","environment","and","normalizes","the","observation","."]
code: def reset(self, **kwargs):
      """Resets the environment and normalizes the observation."""
      obs, info = self.env.reset(**kwargs)
  
      if self.is_vector_env:
          return self.normalize(obs), info
      else:
          return self.normalize(np.array([obs]))[0], info
  
file_path: gym/gym/wrappers/normalize.py
imports: import numpy
  import gym
label_desc: Use image node_id 3 for calling the NormalizeObservation obj's underlying member method code with example usage: obj.reset() and returns: self,  info, self,  info