






"""simple docstring"""


def 					a			(  UpperCamelCase_				:					float  ,						UpperCamelCase_				:					float  ,						UpperCamelCase_				:					float		)	->		list[int]:
 if hue < 0 or hue > 3_6_0:
  raise Exception('hue should be between 0 and 360'		)

 if saturation < 0 or saturation > 1:
  raise Exception('saturation should be between 0 and 1'		)

 if value < 0 or value > 1:
  raise Exception('value should be between 0 and 1'		)

 __A						:							str      =						value * saturation
 __A						:							List[Any]      =						hue / 6_0
 __A						:							List[str]      =						chroma * (1 - abs(hue_section % 2 - 1		))
 __A						:							Dict      =						value - chroma

 if hue_section >= 0 and hue_section <= 1:
  __A						:							Any      =						round(2_5_5 * (chroma + match_value)		)
  __A						:							str      =						round(2_5_5 * (second_largest_component + match_value)		)
  __A						:							Union[str, Any]      =						round(2_5_5 * (match_value)		)
 elif hue_section > 1 and hue_section <= 2:
  __A						:							Tuple      =						round(2_5_5 * (second_largest_component + match_value)		)
  __A						:							Dict      =						round(2_5_5 * (chroma + match_value)		)
  __A						:							Any      =						round(2_5_5 * (match_value)		)
 elif hue_section > 2 and hue_section <= 3:
  __A						:							Optional[Any]      =						round(2_5_5 * (match_value)		)
  __A						:							Tuple      =						round(2_5_5 * (chroma + match_value)		)
  __A						:							Any      =						round(2_5_5 * (second_largest_component + match_value)		)
 elif hue_section > 3 and hue_section <= 4:
  __A						:							List[Any]      =						round(2_5_5 * (match_value)		)
  __A						:							Dict      =						round(2_5_5 * (second_largest_component + match_value)		)
  __A						:							Dict      =						round(2_5_5 * (chroma + match_value)		)
 elif hue_section > 4 and hue_section <= 5:
  __A						:							Optional[int]      =						round(2_5_5 * (second_largest_component + match_value)		)
  __A						:							Dict      =						round(2_5_5 * (match_value)		)
  __A						:							int      =						round(2_5_5 * (chroma + match_value)		)
 else:
  __A						:							Optional[int]      =						round(2_5_5 * (chroma + match_value)		)
  __A						:							Any      =						round(2_5_5 * (match_value)		)
  __A						:							Optional[int]      =						round(2_5_5 * (second_largest_component + match_value)		)

 return [red, green, blue]




def 					a			(  UpperCamelCase_				:					int  ,						UpperCamelCase_				:					int  ,						UpperCamelCase_				:					int		)	->		list[float]:
 if red < 0 or red > 2_5_5:
  raise Exception('red should be between 0 and 255'		)

 if green < 0 or green > 2_5_5:
  raise Exception('green should be between 0 and 255'		)

 if blue < 0 or blue > 2_5_5:
  raise Exception('blue should be between 0 and 255'		)

 __A						:							int      =						red / 2_5_5
 __A						:							str      =						green / 2_5_5
 __A						:							str      =						blue / 2_5_5
 __A						:							int      =						max(UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_		)
 __A						:							Dict      =						value - min(UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_		)
 __A						:							Optional[Any]      =						0 if value == 0 else chroma / value

 if chroma == 0:
  __A						:							List[Any]      =						0.0
 elif value == float_red:
  __A						:							Union[str, Any]      =						6_0 * (0 + (float_green - float_blue) / chroma)
 elif value == float_green:
  __A						:							Tuple      =						6_0 * (2 + (float_blue - float_red) / chroma)
 else:
  __A						:							Union[str, Any]      =						6_0 * (4 + (float_red - float_green) / chroma)

 __A						:							Union[str, Any]      =						(hue + 3_6_0) % 3_6_0

 return [hue, saturation, value]




def 					a			(  UpperCamelCase_				:					list[float]  ,						UpperCamelCase_				:					list[float]		)	->		bool:
 __A						:							str      =						abs(hsv_a[0] - hsv_a[0]		) < 0.2
 __A						:							str      =						abs(hsv_a[1] - hsv_a[1]		) < 0.002
 __A						:							Union[str, Any]      =						abs(hsv_a[2] - hsv_a[2]		) < 0.002

 return check_hue and check_saturation and check_value













"""simple docstring"""


import torch
from torch import autograd






class __a ( autograd.Function					):



  @staticmethod
  def     A_					(lowercase_	:		Optional[Any]					,      lowercase_	:		torch.tensor					,      lowercase_	:		float					,      lowercase_	:		bool )		->				List[str]:
   __A						:							str      =						inputs.numel()
   __A						:							str      =						int(0.005 * nb_elems ) + 1
   if sigmoid:
    __A						:							Dict      =						(torch.sigmoid(lowercase_ ) > threshold).type(inputs.type() )
   else:
    __A						:							Tuple      =						(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
    __A						:							Any      =						inputs.flatten().kthvalue(max(nb_elems - nb_min					,      1 ) ).values
    __A						:							Union[str, Any]      =						(inputs > k_threshold).type(inputs.type() )
   return mask



  @staticmethod
  def     A_					(lowercase_	:		str					,      lowercase_	:		Any )		->				int:
   return gradOutput, None, None






class __a ( autograd.Function					):



  @staticmethod
  def     A_					(lowercase_	:		List[Any]					,      lowercase_	:		torch.tensor					,      lowercase_	:		float )		->				Dict:
   __A						:							List[Any]      =						inputs.clone()
   __A     ,       __A						:							Optional[int]      =						inputs.flatten().sort(descending=lowercase_ )
   __A						:							Tuple      =						int(threshold * inputs.numel() )

   # flat_out and mask access the same memory.
   __A						:							Optional[Any]      =						mask.flatten()
   __A						:							Dict      =						0
   __A						:							Any      =						1
   return mask



  @staticmethod
  def     A_					(lowercase_	:		Tuple					,      lowercase_	:		Optional[Any] )		->				str:
   return gradOutput, None






class __a ( snake_case_					):



  @staticmethod
  def     A_					(lowercase_	:		torch.tensor					,      lowercase_	:		float )		->				List[str]:
   __A						:							List[str]      =						inputs.clone()
   __A     ,       __A						:							List[Any]      =						inputs.abs().flatten().sort(descending=lowercase_ )
   __A						:							Dict      =						int(threshold * inputs.numel() )

   # flat_out and mask access the same memory.
   __A						:							List[Any]      =						mask.flatten()
   __A						:							Dict      =						0
   __A						:							Tuple      =						1
   return mask





