
import torch
from torch import autograd
class      A__       (						autograd.Function    ):





							@staticmethod
							def       a__			(			_UpperCAmelCase  :       Optional[Any]					,			_UpperCAmelCase  :       torch.tensor					,			_UpperCAmelCase  :       float					,			_UpperCAmelCase  :       bool    )						->		List[str]:



											"""simple docstring"""


											__lowercase								= inputs.numel()
											__lowercase								= int(0.005 * nb_elems    ) + 1
											if sigmoid:
															__lowercase								= (torch.sigmoid(_UpperCAmelCase    ) > 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       a__			(			_UpperCAmelCase  :       Tuple					,			_UpperCAmelCase  :       Union[str, Any]    )						->		Dict:



											"""simple docstring"""


											return gradOutput, None, None






class      A__       (						autograd.Function    ):





							@staticmethod
							def       a__			(			_UpperCAmelCase  :       Dict					,			_UpperCAmelCase  :       torch.tensor					,			_UpperCAmelCase  :       float    )						->		Union[str, Any]:



											"""simple docstring"""


											__lowercase								= inputs.clone()
											__lowercase		, __lowercase								= inputs.flatten().sort(descending=_UpperCAmelCase    )
											__lowercase								= int(threshold * inputs.numel()    )

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





							@staticmethod
							def       a__			(			_UpperCAmelCase  :       Tuple					,			_UpperCAmelCase  :       Optional[int]    )						->		int:



											"""simple docstring"""


											return gradOutput, None






class      A__       (						SCREAMING_SNAKE_CASE__    ):





							@staticmethod
							def       a__			(			_UpperCAmelCase  :       torch.tensor					,			_UpperCAmelCase  :       float    )						->		int:



											"""simple docstring"""


											__lowercase								= inputs.clone()
											__lowercase		, __lowercase								= inputs.abs().flatten().sort(descending=_UpperCAmelCase    )
											__lowercase								= int(threshold * inputs.numel()    )

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







from __future__ import annotations

from enum import Enum
class      A__       (						lowerCAmelCase__    ):
							lowerCAmelCase__		:						Dict         =							24
							lowerCAmelCase__		:						Dict         =							21
							lowerCAmelCase__		:						Union[str, Any]         =							18
							lowerCAmelCase__		:						Dict         =							15
							lowerCAmelCase__		:						Any         =							12
							lowerCAmelCase__		:						Union[str, Any]         =							9
							lowerCAmelCase__		:						Any         =							6
							lowerCAmelCase__		:						Optional[Any]         =							3
							lowerCAmelCase__		:						Union[str, Any]         =							2
							lowerCAmelCase__		:						List[Any]         =							1
							lowerCAmelCase__		:						Optional[Any]         =							-1
							lowerCAmelCase__		:						Tuple         =							-2
							lowerCAmelCase__		:						Dict         =							-3
							lowerCAmelCase__		:						Union[str, Any]         =							-6
							lowerCAmelCase__		:						Any         =							-9
							lowerCAmelCase__		:						Union[str, Any]         =							-12
							lowerCAmelCase__		:						str         =							-15
							lowerCAmelCase__		:						Optional[int]         =							-18
							lowerCAmelCase__		:						Any         =							-21
							lowerCAmelCase__		:						Any         =							-24






class      A__       (						lowerCAmelCase__    ):
							lowerCAmelCase__		:						Tuple         =							8
							lowerCAmelCase__		:						Union[str, Any]         =							7
							lowerCAmelCase__		:						Optional[Any]         =							6
							lowerCAmelCase__		:						Tuple         =							5
							lowerCAmelCase__		:						Optional[int]         =							4
							lowerCAmelCase__		:						Optional[int]         =							3
							lowerCAmelCase__		:						Optional[int]         =							2
							lowerCAmelCase__		:						Any         =							1






def 							__SCREAMING_SNAKE_CASE       (		SCREAMING_SNAKE_CASE	:				float   ,							SCREAMING_SNAKE_CASE	:				str | SIUnit   ,							SCREAMING_SNAKE_CASE	:				str | SIUnit   ,							)					->						float:
				if isinstance(SCREAMING_SNAKE_CASE   ,							SCREAMING_SNAKE_CASE      ):
								__lowercase								= SIUnit[known_prefix.lower()]
				if isinstance(SCREAMING_SNAKE_CASE   ,							SCREAMING_SNAKE_CASE      ):
								__lowercase								= SIUnit[unknown_prefix.lower()]
				__lowercase								= known_amount * (
				    10 ** (known_prefix.value - unknown_prefix.value)
				)
				return unknown_amount




def 							__SCREAMING_SNAKE_CASE       (		SCREAMING_SNAKE_CASE	:				float   ,							SCREAMING_SNAKE_CASE	:				str | BinaryUnit   ,							SCREAMING_SNAKE_CASE	:				str | BinaryUnit   ,							)					->						float:
				if isinstance(SCREAMING_SNAKE_CASE   ,							SCREAMING_SNAKE_CASE      ):
								__lowercase								= BinaryUnit[known_prefix.lower()]
				if isinstance(SCREAMING_SNAKE_CASE   ,							SCREAMING_SNAKE_CASE      ):
								__lowercase								= BinaryUnit[unknown_prefix.lower()]
				__lowercase								= known_amount * (
				    2 ** ((known_prefix.value - unknown_prefix.value) * 10)
				)
				return unknown_amount


if __name__ == "__main__":
							import doctest

							doctest.testmod()





