class_docstr: ENMF is an efficient non-sampling model for general recommendation.
  In order to run non-sampling model, please set the neg_sampling parameter as None .
class_docstr_tok: ["ENMF","is","an","efficient","non-sampling","model","for","general","recommendation",".","In","order","to","run","non-sampling","model",",","please","set","the","neg_sampling","parameter","as","None","."]
code: def predict(self, interaction):
      user = interaction[self.USER_ID]
      item = interaction[self.ITEM_ID]
  
      u_e = self.user_embedding(user)
      i_e = self.item_embedding(item)
  
      score = torch.mul(u_e, i_e)  # shape: [B,embedding_dim]
      score = self.H_i(score)  # shape: [B,1]
  
      return score.squeeze(1)
  
file_path: RecBole/recbole/model/general_recommender/enmf.py
imports: import torch
  import torch.nn
  from recbole.model.init import xavier_normal_initialization
  from recbole.utils import InputType
  from recbole.model.abstract_recommender import GeneralRecommender
label_desc: Use image node_id 5 for calling the ENMF obj's underlying member method code with example usage: obj.predict(interaction) and returns: score