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 forward(self, seq_item, user):
      user_embedding = self.dropout(
          self.relu(self.user_embedding(user))
      )
      # batch_size * embedding_size
      seq_item_embedding = self.item_embedding(seq_item).sum(dim=1)
      seq_item_embedding = self.dropout(self.relu(seq_item_embedding))
      # batch_size * embedding_size
  
      return user_embedding + seq_item_embedding
  
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 3 for calling the NPE obj's underlying member method code with example usage: obj.forward(seq_item, user) and returns: unknown