






import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class 							A_    (						unittest.TestCase			):






 '''simple docstring'''




 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     _UpperCAmelCase				:      Any			  =				[
         '''safety_checker/pytorch_model.bin''',
         '''safety_checker/model.safetensors''',
         '''vae/diffusion_pytorch_model.bin''',
         '''vae/diffusion_pytorch_model.safetensors''',
         '''text_encoder/pytorch_model.bin''',
         '''text_encoder/model.safetensors''',
         '''unet/diffusion_pytorch_model.bin''',
         '''unet/diffusion_pytorch_model.safetensors''',
     ]
     self.assertTrue(is_safetensors_compatible(_A))


 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      List[Any]			  =				[
         '''unet/diffusion_pytorch_model.bin''',
         '''unet/diffusion_pytorch_model.safetensors''',
     ]
     self.assertTrue(is_safetensors_compatible(_A))


 def  snake_case__				(	self) ->		List[str]:

     """simple docstring"""



     _UpperCAmelCase				:      List[Any]			  =				[
         '''safety_checker/pytorch_model.bin''',
         '''safety_checker/model.safetensors''',
         '''vae/diffusion_pytorch_model.bin''',
         '''vae/diffusion_pytorch_model.safetensors''',
         '''text_encoder/pytorch_model.bin''',
         '''text_encoder/model.safetensors''',
         '''unet/diffusion_pytorch_model.bin''',
         # Removed: 'unet/diffusion_pytorch_model.safetensors',
     ]
     self.assertFalse(is_safetensors_compatible(_A))


 def  snake_case__				(	self) ->		Optional[int]:

     """simple docstring"""



     _UpperCAmelCase				:      str			  =				[
         '''text_encoder/pytorch_model.bin''',
         '''text_encoder/model.safetensors''',
     ]
     self.assertTrue(is_safetensors_compatible(_A))


 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     _UpperCAmelCase				:      str			  =				[
         '''safety_checker/pytorch_model.bin''',
         '''safety_checker/model.safetensors''',
         '''vae/diffusion_pytorch_model.bin''',
         '''vae/diffusion_pytorch_model.safetensors''',
         '''text_encoder/pytorch_model.bin''',
         # Removed: 'text_encoder/model.safetensors',
         '''unet/diffusion_pytorch_model.bin''',
         '''unet/diffusion_pytorch_model.safetensors''',
     ]
     self.assertFalse(is_safetensors_compatible(_A))


 def  snake_case__				(	self) ->		List[Any]:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				[
         '''safety_checker/pytorch_model.fp16.bin''',
         '''safety_checker/model.fp16.safetensors''',
         '''vae/diffusion_pytorch_model.fp16.bin''',
         '''vae/diffusion_pytorch_model.fp16.safetensors''',
         '''text_encoder/pytorch_model.fp16.bin''',
         '''text_encoder/model.fp16.safetensors''',
         '''unet/diffusion_pytorch_model.fp16.bin''',
         '''unet/diffusion_pytorch_model.fp16.safetensors''',
     ]
     _UpperCAmelCase				:      Tuple			  =				'''fp16'''
     self.assertTrue(is_safetensors_compatible(_A							,  variant=_A))


 def  snake_case__				(	self) ->		str:

     """simple docstring"""



     _UpperCAmelCase				:      Union[str, Any]			  =				[
         '''unet/diffusion_pytorch_model.fp16.bin''',
         '''unet/diffusion_pytorch_model.fp16.safetensors''',
     ]
     _UpperCAmelCase				:      Dict			  =				'''fp16'''
     self.assertTrue(is_safetensors_compatible(_A							,  variant=_A))


 def  snake_case__				(	self) ->		str:

     """simple docstring"""



     _UpperCAmelCase				:      List[str]			  =				[
         '''unet/diffusion_pytorch_model.bin''',
         '''unet/diffusion_pytorch_model.safetensors''',
     ]
     _UpperCAmelCase				:      Any			  =				'''fp16'''
     self.assertTrue(is_safetensors_compatible(_A							,  variant=_A))


 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				[
         '''safety_checker/pytorch_model.fp16.bin''',
         '''safety_checker/model.fp16.safetensors''',
         '''vae/diffusion_pytorch_model.fp16.bin''',
         '''vae/diffusion_pytorch_model.fp16.safetensors''',
         '''text_encoder/pytorch_model.fp16.bin''',
         '''text_encoder/model.fp16.safetensors''',
         '''unet/diffusion_pytorch_model.fp16.bin''',
         # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
     ]
     _UpperCAmelCase				:      Optional[int]			  =				'''fp16'''
     self.assertFalse(is_safetensors_compatible(_A							,  variant=_A))


 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      Dict			  =				[
         '''text_encoder/pytorch_model.fp16.bin''',
         '''text_encoder/model.fp16.safetensors''',
     ]
     _UpperCAmelCase				:      Tuple			  =				'''fp16'''
     self.assertTrue(is_safetensors_compatible(_A							,  variant=_A))


 def  snake_case__				(	self) ->		Optional[int]:

     """simple docstring"""



     _UpperCAmelCase				:      Dict			  =				[
         '''text_encoder/pytorch_model.bin''',
         '''text_encoder/model.safetensors''',
     ]
     _UpperCAmelCase				:      Any			  =				'''fp16'''
     self.assertTrue(is_safetensors_compatible(_A							,  variant=_A))


 def  snake_case__				(	self) ->		Optional[int]:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				[
         '''safety_checker/pytorch_model.fp16.bin''',
         '''safety_checker/model.fp16.safetensors''',
         '''vae/diffusion_pytorch_model.fp16.bin''',
         '''vae/diffusion_pytorch_model.fp16.safetensors''',
         '''text_encoder/pytorch_model.fp16.bin''',
         # 'text_encoder/model.fp16.safetensors',
         '''unet/diffusion_pytorch_model.fp16.bin''',
         '''unet/diffusion_pytorch_model.fp16.safetensors''',
     ]
     _UpperCAmelCase				:      Union[str, Any]			  =				'''fp16'''
     self.assertFalse(is_safetensors_compatible(_A							,  variant=_A))












from __future__ import annotations

def      _lowerCamelCase	(						__A    :							int )      ->					list[int]:
    _UpperCAmelCase				:      List[str]			  =				[True] * limit
    _UpperCAmelCase				:      Optional[int]			  =				False
    _UpperCAmelCase				:      Dict			  =				False
    _UpperCAmelCase				:      List[str]			  =				True

    for i in range(3		,		int(limit**0.5 + 1 )		,		2 ):
        _UpperCAmelCase				:      List[str]			  =				i * 2
        while index < limit:
            _UpperCAmelCase				:      Union[str, Any]			  =				False
            _UpperCAmelCase				:      int			  =				index + i

    _UpperCAmelCase				:      Optional[int]			  =				[2]

    for i in range(3		,		__A		,		2 ):
        if is_prime[i]:
            primes.append(__A )

    return primes

def      _lowerCamelCase	(						__A    :							int = 1_000_000 )      ->					int:
    _UpperCAmelCase				:      Any			  =				prime_sieve(__A )
    _UpperCAmelCase				:      Optional[Any]			  =				0
    _UpperCAmelCase				:      Tuple			  =				0

    for i in range(len(__A ) ):
        for j in range(i + length		,		len(__A ) ):
            _UpperCAmelCase				:      List[Any]			  =				sum(primes[i:j] )
            if sol >= ceiling:
                break

            if sol in primes:
                _UpperCAmelCase				:      List[str]			  =				j - i
                _UpperCAmelCase				:      Optional[Any]			  =				sol

    return largest


if __name__ == "__main__":
  print(F'{solution() = }')




