class_docstr: Base model class for Euclidean embeddings.
code: def similarity_score(self, lhs, rhs, eval_mode):
      if self.sim == "dot":
          if eval_mode:
              score = tf.matmul(lhs, tf.transpose(rhs))
          else:
              score = tf.reduce_sum(lhs * rhs, axis=-1, keepdims=True)
      elif self.sim == "dist":
          score = -euc_utils.euc_sq_distance(lhs, rhs, eval_mode)
      else:
          raise AttributeError(
              "Similarity function {} not recognized".format(self.sim)
          )
      return score
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from kg_hyp_emb.models.base import KGModel
  from kg_hyp_emb.utils import euclidean
  import numpy
  import tensorflow
label_desc: Use image node_id 3 for calling the BaseE obj's underlying member method code with example usage: obj.similarity_score(lhs, rhs, eval_mode) and returns: score