class_docstr: Initializes parameters with the single value decomposition of a
  random gaussian matrix.
  
  Implementation taken from Lasagne. Reference: Saxe et al., http://arxiv.org/abs/1312.6120
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docstr: Class constructor.
  
  Args:
      scale (float, optional): Scaling factor of values. Defaults to 1.1.
      name (string, optional): Name to assign an instance of this class.
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code: def __init__(self, scale=1.1, name="orthonormal"):
      """
      Class constructor.
  
      Args:
          scale (float, optional): Scaling factor of values. Defaults to 1.1.
          name (string, optional): Name to assign an instance of this class.
      """
      super(Orthonormal, self).__init__(name=name)
      self.scale = scale
  
imports: import numpy
  from neon import NervanaObject
  from neon.backends.backend import Tensor
label_desc: Use image node_id 1 to create a new Orthonormal object from inherited base classes: Initializer with example: obj = Orthonormal(scale, name)