class_docstr: LINE is a graph embedding model.
  
  We implement the model to train users and items embedding for recommendation.
code: def forward(self, h, t):
      h_embedding = self.user_embedding(h)
      t_embedding = self.item_embedding(t)
  
      return torch.sum(h_embedding.mul(t_embedding), dim=1)
  
imports: import random
  import numpy
  import torch
  import torch.nn
  from recbole.model.abstract_recommender import GeneralRecommender
  from recbole.model.init import xavier_normal_initialization
  from recbole.utils import InputType
label_desc: Use image node_id 6 for calling the LINE obj's underlying member method code with example usage: obj.forward(h, t) and returns: torch