class_docstr: models a user’s click to an item in two terms: the personal preference of the user for the item,
  and the relationships between this item and other items clicked by the user
class_docstr_tok: ["models","a","user","\u2019","s","click","to","an","item","in","two","terms",":","the","personal","preference","of","the","user","for","the","item",",","and","the","relationships","between","this","item","and","other","items","clicked","by","the","user"]
code: def _init_weights(self, module):
      if isinstance(module, nn.Embedding):
          xavier_normal_(module.weight.data)
  
file_path: RecBole/recbole/model/sequential_recommender/npe.py
imports: import torch
  import torch.nn
  from torch.nn.init import xavier_normal_
  from recbole.model.abstract_recommender import SequentialRecommender
  from recbole.model.loss import BPRLoss
label_desc: Use image node_id 2 for calling the NPE obj's underlying member method code with example usage: obj._init_weights(module) without return types