class_docstr: Compute the L2-norm for each weight kernel.
  
  This initializer is specific to the weight normalization scale to keep the same magnitude of the originally initialized weights even after the application of the weight normalization at only initialization.
  
  Args:
      w (:obj:`Variable`): Weight the weight normalization is applied.
      dim (:obj:`int`): Output dimension of the weight normalization.
      eps (:obj:`float`): Eplision of the weight normalization.
code: def __init__(self, w, dim=0, eps=1e-12):
      self.w = w.get_unlinked_variable()
      self.dim = dim
      self.eps = eps
  
imports: import numpy
  from .None import random
label_desc: Use image node_id 1 to create a new WeightNormalizationScaleInitializer object from inherited base classes: BaseInitializer with example: obj = WeightNormalizationScaleInitializer(w, dim, eps)