class_docstr: DSSM respectively expresses user and item as low dimensional vectors with mlp layers,
  and uses cosine distance to calculate the distance between the two semantic vectors.
code: def predict(self, interaction):
      return self.sigmoid(self.forward(interaction))
  
file_path: RecBole/recbole/model/context_aware_recommender/dssm.py
imports: import torch
  import torch.nn
  from torch.nn.init import xavier_normal_, constant_
  from recbole.model.abstract_recommender import ContextRecommender
  from recbole.model.layers import MLPLayers
label_desc: Use image node_id 5 for calling the DSSM obj's underlying member method code with example usage: obj.predict(interaction) and returns: self