






"""simple docstring"""



import torch
from torch import autograd

class 	a					(       autograd.Function     ):







    @staticmethod
    def       UpperCamelCase_				(      _lowerCamelCase							,		_lowerCamelCase							,		_lowerCamelCase							,		_lowerCamelCase	):
         lowercase							   =	inputs.numel()
         lowercase							   =	int(0.0_0_5 * nb_elems	) + 1
         if sigmoid:
              lowercase							   =	(torch.sigmoid(_lowerCamelCase	) > threshold).type(inputs.type()	)
         else:
              lowercase							   =	(inputs > threshold).type(inputs.type()	)
         if mask.sum() < nb_min:
              # We limit the pruning so that at least 0.5% (half a percent) of the weights are remaining
              lowercase							   =	inputs.flatten().kthvalue(max(nb_elems - nb_min							,		1	)	).values
              lowercase							   =	(inputs > k_threshold).type(inputs.type()	)
         return mask







    @staticmethod
    def       UpperCamelCase_				(      _lowerCamelCase							,		_lowerCamelCase	):
         return gradOutput, None, None


class 	a					(       autograd.Function     ):







    @staticmethod
    def       UpperCamelCase_				(      _lowerCamelCase							,		_lowerCamelCase							,		_lowerCamelCase	):
         lowercase							   =	inputs.clone()
         lowercase   ,					lowercase							   =	inputs.flatten().sort(descending=_lowerCamelCase	)
         lowercase							   =	int(threshold * inputs.numel()	)

         # flat_out and mask access the same memory.
         lowercase							   =	mask.flatten()
         lowercase							   =	0
         lowercase							   =	1
         return mask







    @staticmethod
    def       UpperCamelCase_				(      _lowerCamelCase							,		_lowerCamelCase	):
         return gradOutput, None


class 	a					(       a_     ):







    @staticmethod
    def       UpperCamelCase_				(      _lowerCamelCase							,		_lowerCamelCase	):
         lowercase							   =	inputs.clone()
         lowercase   ,					lowercase							   =	inputs.abs().flatten().sort(descending=_lowerCamelCase	)
         lowercase							   =	int(threshold * inputs.numel()	)

         # flat_out and mask access the same memory.
         lowercase							   =	mask.flatten()
         lowercase							   =	0
         lowercase							   =	1
         return mask










"""simple docstring"""



def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Dict		, __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	1
  while b > 0:
    if b & 1:
      res *= a

    a *= a
    b >>= 1

  return res
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  int		, __snake_case      :  List[str]		, __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	1
  while b > 0:
    if b & 1:
      lowercase							   =	((res % c) * (a % c)) % c

    a *= a
    b >>= 1

  return res


