class_docstr: BPR is a basic matrix factorization model that be trained in the pairwise way.
class_docstr_tok: ["BPR","is","a","basic","matrix","factorization","model","that","be","trained","in","the","pairwise","way","."]
code: def forward(self, user, item):
      user_e = self.get_user_embedding(user)
      item_e = self.get_item_embedding(item)
      return user_e, item_e
  
file_path: RecBole/recbole/model/general_recommender/bpr.py
imports: import torch
  import torch.nn
  from recbole.model.abstract_recommender import GeneralRecommender
  from recbole.model.init import xavier_normal_initialization
  from recbole.model.loss import BPRLoss
  from recbole.utils import InputType
label_desc: Use image node_id 4 for calling the BPR obj's underlying member method code with example usage: obj.forward(user, item) and returns: user_e,  item_e