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\/"]
code: def __init__(self, gamma, num_elem, scale_type=0):
      super(OTEScore, self).__init__()
      self.gamma = gamma
      self.num_elem = num_elem
      self.scale_type = scale_type
  
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 1 to create a new OTEScore object from inherited base classes: ScoreFunc with example: obj = OTEScore(gamma, num_elem, scale_type)