class_docstr: Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding.
  https://aclanthology.org/2020.acl-main.241/
class_docstr_tok: ["Orthogonal","Relation","Transforms","with","Graph","Context","Modeling","for","Knowledge","Graph","Embedding",".","https",":","\/\/aclanthology.org\/2020.acl-main.241\/"]
docstr: Calculate scores of negative samples.
          
docstr_tok: ["Calculate","scores","of","negative","samples","."]
code: def get_neg_score(self, head, rel, tail, neg_head=False):
      """Calculate scores of negative samples."""
      rel = self.orth_rel_embedding(rel)
      if neg_head:
          rel = self._orth_reverse_mat(rel)
          score = self._get_neg_score(tail, rel, head)
      else:
          score = self._get_neg_score(head, rel, tail)
      return self.gamma - score
  
imports: import math
  import numpy
  from numpy.random import RandomState
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.functional import log_sigmoid
label_desc: Use image node_id 7 for calling the OTEScore obj's underlying member method code with example usage: obj.get_neg_score(head, rel, tail, neg_head) and returns: unknown