class_docstr: Implementation of "Weight Normalization: A Simple Reparameterization
  to Accelerate Training of Deep Neural Networks"
  :cite:`DBLP:journals/corr/SalimansK16`
  
  As a reparameterization method, weight normalization is same
  as BatchNormalization, but it doesn't depend on minibatch.
  
  NOTE: This is used nowhere in the code at this stage
        Vincent Nguyen 05/18/2018
class_docstr_tok: ["Implementation","of","``","Weight","Normalization",":","A","Simple","Reparameterization","to","Accelerate","Training","of","Deep","Neural","Networks","''",":","cite",":","`","DBLP",":","journals\/corr\/SalimansK16","`","As","a","reparameterization","method",",","weight","normalization","is","same","as","BatchNormalization",",","but","it","does","n't","depend","on","minibatch",".","NOTE",":","This","is","used","nowhere","in","the","code","at","this","stage","Vincent","Nguyen","05\/18\/2018"]
code: def reset_parameters(self):
      return
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import Parameter
label_desc: Use image node_id 2 for calling the WeightNormLinear obj's underlying member method code with example usage: obj.reset_parameters() without return types