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: Return initial value of scales.
          
docstr_tok: ["Return","initial","value","of","scales","."]
code: def scale_init(self):
      """Return initial value of scales."""
      if self.scale_type == 1:
          return 1.0
      if self.scale_type == 2:
          return 0.0
      raise ValueError(
          "Scale Type %d is not supported!" % self.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 3 for calling the OTEScore obj's underlying member method code with example usage: obj.scale_init() and returns: int, int