class_docstr: DCNV2 improves the cross network by extending the original weight vector to a matrix,
  significantly improves the expressiveness of DCN. It also introduces the MoE and
  low rank techniques to reduce time cost.
class_docstr_tok: ["DCNV2","improves","the","cross","network","by","extending","the","original","weight","vector","to","a","matrix",",","significantly","improves","the","expressiveness","of","DCN",".","It","also","introduces","the","MoE","and","low","rank","techniques","to","reduce","time","cost","."]
code: def predict(self, interaction):
      return self.forward(interaction)
  
file_path: RecBole/recbole/model/context_aware_recommender/dcnv2.py
imports: import torch
  import torch.nn
  from recbole.model.abstract_recommender import ContextRecommender
  from recbole.model.init import xavier_normal_initialization
  from recbole.model.layers import MLPLayers
  from recbole.model.loss import RegLoss
label_desc: Use image node_id 6 for calling the DCNV2 obj's underlying member method code with example usage: obj.predict(interaction) and returns: self