class_docstr: CORE is a simple and effective framewor, which unifies the representation spac
  for both the encoding and decoding processes in session-based recommendation.
class_docstr_tok: ["CORE","is","a","simple","and","effective","framewor",",","which","unifies","the","representation","spac","for","both","the","encoding","and","decoding","processes","in","session-based","recommendation","."]
code: def _reset_parameters(self):
      stdv = 1.0 / np.sqrt(self.embedding_size)
      for weight in self.parameters():
          weight.data.uniform_(-stdv, stdv)
  
imports: import numpy
  import torch
  from torch import nn
  import torch.nn.functional
  from recbole.model.abstract_recommender import SequentialRecommender
  from recbole.model.layers import TransformerEncoder
label_desc: Use image node_id 2 for calling the CORE obj's underlying member method code with example usage: obj._reset_parameters() without return types