class_docstr: Link prediction network for graphs / knowledge graphs
class_docstr_tok: ["Link","prediction","network","for","graphs","\/","knowledge","graphs"]
code: def forward(self, *indexes):
      assert len(indexes) == len(self.embeddings)
      vectors = []
      for index, embedding in zip(indexes, self.embeddings):
          vectors.append(embedding(index))
      return self.score_function(*vectors, **self.kwargs)
  
file_path: graphvite/python/graphvite/application/network.py
imports: from __future__ import absolute_import
  import types
  import numpy
  import torch
  from torch import nn
label_desc: Use image node_id 2 for calling the LinkPredictor obj's underlying member method code with example usage: obj.forward() and returns: self