class_docstr: Top-k Binarizer.
  Computes a binary mask M from a real value matrix S such that `M_{i,j} = 1` if and only if `S_{i,j}`
  is among the k% highest values of S.
  
  Implementation is inspired from:
      https://github.com/allenai/hidden-networks
      What's hidden in a randomly weighted neural network?
      Vivek Ramanujan*, Mitchell Wortsman*, Aniruddha Kembhavi, Ali Farhadi, Mohammad Rastegari
class_docstr_tok: ["Top-k","Binarizer",".","Computes","a","binary","mask","M","from","a","real","value","matrix","S","such","that","`","M_","{","i",",","j","}","=","1","`","if","and","only","if","`","S_","{","i",",","j","}","`","is","among","the","k","%","highest","values","of","S.","Implementation","is","inspired","from",":","https",":","\/\/github.com\/allenai\/hidden-networks","What","'s","hidden","in","a","randomly","weighted","neural","network","?","Vivek","Ramanujan","*",",","Mitchell","Wortsman","*",",","Aniruddha","Kembhavi",",","Ali","Farhadi",",","Mohammad","Rastegari"]
code: def backward(ctx, gradOutput):
      return gradOutput, None
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/movement-pruning/emmental/modules/binarizer.py
imports: import torch
  from torch import autograd
label_desc: Use image node_id 2 for calling the TopKBinarizer obj's underlying member method code with example usage: obj.backward(ctx, gradOutput) and returns: gradOutput,  None