class_docstr: Complex embeddings for simple link prediction.
class_docstr_tok: ["Complex","embeddings","for","simple","link","prediction","."]
code: def get_queries(self, input_tensor):
      lhs = self.entity(input_tensor[:, 0])
      rel = self.rel(input_tensor[:, 1])
      lhs = lhs[:, : self.half_rank], lhs[:, self.half_rank :]
      rel = rel[:, : self.half_rank], rel[:, self.half_rank :]
  
      return tf.concat(
          [
              lhs[0] * rel[0] - lhs[1] * rel[1],
              lhs[0] * rel[1] + lhs[1] * rel[0],
          ],
          axis=1,
      )
  
file_path: neural-structured-learning/research/kg_hyp_emb/models/complex.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from kg_hyp_emb.models.base import KGModel
  import tensorflow
label_desc: Use image node_id 1 for calling the Complex obj's underlying member method code with example usage: obj.get_queries(input_tensor) and returns: tf