class_docstr: Collaborative Denoising Auto-Encoder (RecVAE) is a recommendation model
  for top-N recommendation with implicit feedback.
  
  We implement the model following the original author
class_docstr_tok: ["Collaborative","Denoising","Auto-Encoder","(","RecVAE",")","is","a","recommendation","model","for","top-N","recommendation","with","implicit","feedback",".","We","implement","the","model","following","the","original","author"]
code: def update_prior(self):
      self.prior.encoder_old.load_state_dict(
          deepcopy(self.encoder.state_dict())
      )
  
imports: import numpy
  from copy import deepcopy
  import torch
  import torch.nn
  import torch.nn.functional
  from recbole.model.abstract_recommender import GeneralRecommender, AutoEncoderMixin
  from recbole.model.init import xavier_normal_initialization
  from recbole.utils import InputType
label_desc: Use image node_id 7 for calling the RecVAE obj's underlying member method code with example usage: obj.update_prior() without return types