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 calculate_loss(self, interaction):
      label = interaction[self.LABEL]
      output = self.forward(interaction)
      return self.loss(output, label)
  
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 4 for calling the DSSM obj's underlying member method code with example usage: obj.calculate_loss(interaction) and returns: self