class_docstr: Initialize matrix with orthogonal basis.
  
  Parameters
  ----------
  scale : int, float
      Scales output matrix by a specified factor.
      Defaults to ``1``.
  
  seed : None or int
      Random seed. Integer value will make results reproducible.
      Defaults to ``None``.
  
  Raises
  ------
  ValueError
      In case if tensor shape has more than 2
      dimensions.
  
  Methods
  -------
  {Initializer.Methods}
class_docstr_tok: ["Initialize","matrix","with","orthogonal","basis",".","Parameters","--","--","--","--","--","scale",":","int",",","float","Scales","output","matrix","by","a","specified","factor",".","Defaults","to","``","1","``",".","seed",":","None","or","int","Random","seed",".","Integer","value","will","make","results","reproducible",".","Defaults","to","``","None","``",".","Raises","--","--","--","ValueError","In","case","if","tensor","shape","has","more","than","2","dimensions",".","Methods","--","--","--","-","{","Initializer.Methods","}"]
code: def __repr__(self):
      return "{}(scale={})".format(classname(self), self.scale)
  
imports: import abc
  import six
  import numpy
  import tensorflow
  from neupy.core.docs import SharedDocsABCMeta
label_desc: Use image node_id 3 for calling the Orthogonal obj's underlying member method code with example usage: obj.__repr__() and returns: str