'''simple docstring'''


def  _lowerCamelCase   (				lowerCamelCase_ :							int     ,					lowerCamelCase_ :							bool = False       ):



     """simple docstring"""





     if n == 2:
          return True
     if not n % 2 or n < 2:
          return False
     if n > 5 and n % 10 not in (1, 3, 7, 9):  # can quickly check last digit
          return False
     if n > 3317044064679887385961981 and not allow_probable:
          raise ValueError(
              'Warning: upper bound of deterministic test is exceeded. '
              'Pass allow_probable=True to allow probabilistic test. '
              'A return value of True indicates a probable prime.'       )
     # array bounds provided by analysis
     UpperCAmelCase_							:       str       =				[
         2047,
         1373653,
         25326001,
         3215031751,
         2152302898747,
         3474749660383,
         341550071728321,
         1,
         3825123056546413051,
         1,
         1,
         318665857834031151167461,
         3317044064679887385961981,
     ]

     UpperCAmelCase_							:       Tuple       =				[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
     for idx, _p in enumerate(lowerCamelCase_     ,					1       ):
          if n < _p:
               # then we have our last prime to check
               UpperCAmelCase_							:       Union[str, Any]       =				primes[:idx]
               break
     UpperCAmelCase_       ,      UpperCAmelCase_							:       Optional[Any]       =				n - 1, 0
     # break up n -1 into a power of 2 (s) and
     # remaining odd component
     # essentially, solve for d * 2 ** s == n - 1
     while d % 2 == 0:
          d //= 2
          s += 1
     for prime in plist:
          UpperCAmelCase_							:       Any       =				False
          for r in range(lowerCamelCase_       ):
               UpperCAmelCase_							:       Optional[Any]       =				pow(lowerCamelCase_     ,					d * 2**r     ,					lowerCamelCase_       )
               # see article for analysis explanation for m
               if (r == 0 and m == 1) or ((m + 1) % n == 0):
                    UpperCAmelCase_							:       str       =				True
                    # this loop will not determine compositeness
                    break
          if pr:
               continue
          # if pr is False, then the above loop never evaluated to true,
          # and the n MUST be composite
          return False
     return True


def  _lowerCamelCase   (				):



     """simple docstring"""





     assert not miller_rabin(561       )
     assert miller_rabin(563       )
     # 2047

     assert not miller_rabin(838201       )
     assert miller_rabin(838207       )
     # 1_373_653

     assert not miller_rabin(17316001       )
     assert miller_rabin(17316017       )
     # 25_326_001

     assert not miller_rabin(3078386641       )
     assert miller_rabin(3078386653       )
     # 3_215_031_751

     assert not miller_rabin(1713045574801       )
     assert miller_rabin(1713045574819       )
     # 2_152_302_898_747

     assert not miller_rabin(2779799728307       )
     assert miller_rabin(2779799728327       )
     # 3_474_749_660_383

     assert not miller_rabin(113850023909441       )
     assert miller_rabin(113850023909527       )
     # 341_550_071_728_321

     assert not miller_rabin(1275041018848804351       )
     assert miller_rabin(1275041018848804391       )
     # 3_825_123_056_546_413_051

     assert not miller_rabin(79666464458507787791867       )
     assert miller_rabin(79666464458507787791951       )
     # 318_665_857_834_031_151_167_461

     assert not miller_rabin(552840677446647897660333       )
     assert miller_rabin(552840677446647897660359       )
     # 3_317_044_064_679_887_385_961_981
     # upper limit for probabilistic test


if __name__ == "__main__":
 test_miller_rabin()







'''simple docstring'''


import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_	):







  '''simple docstring'''






  lowerCamelCase_		:Tuple						   =		['''image_processor''', '''tokenizer''']
  lowerCamelCase_		:Optional[Any]						   =		'''ViTImageProcessor'''
  lowerCamelCase_		:int						   =		('''CLIPTokenizer''', '''CLIPTokenizerFast''')


  def __init__(			self				,		snake_case_=None				,		snake_case_=None				,		**snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       Dict       =				None
       if "feature_extractor" in kwargs:
            warnings.warn(
                'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
                ' instead.'				,		snake_case_				,		)
            UpperCAmelCase_							:       int       =				kwargs.pop('feature_extractor'						)

       UpperCAmelCase_							:       str       =				image_processor if image_processor is not None else feature_extractor
       if image_processor is None:
            raise ValueError('You need to specify an `image_processor`.'						)
       if tokenizer is None:
            raise ValueError('You need to specify a `tokenizer`.'						)

       super().__init__(snake_case_				,		snake_case_						)


  def __call__(			self				,		snake_case_=None				,		snake_case_=None				,		snake_case_=None				,		snake_case_=None				,		**snake_case_						):




       '''simple docstring'''

       if text is None and visual_prompt is None and images is None:
            raise ValueError('You have to specify either text, visual prompt or images.'						)

       if text is not None and visual_prompt is not None:
            raise ValueError('You have to specify exactly one type of prompt. Either text or visual prompt.'						)

       if text is not None:
            UpperCAmelCase_							:       Optional[int]       =				self.tokenizer(snake_case_				,		return_tensors=snake_case_				,		**snake_case_						)

       if visual_prompt is not None:
            UpperCAmelCase_							:       Optional[Any]       =				self.image_processor(snake_case_				,		return_tensors=snake_case_				,		**snake_case_						)

       if images is not None:
            UpperCAmelCase_							:       int       =				self.image_processor(snake_case_				,		return_tensors=snake_case_				,		**snake_case_						)

       if visual_prompt is not None and images is not None:
            UpperCAmelCase_							:       Tuple       =				{
                'pixel_values': image_features.pixel_values,
                'conditional_pixel_values': prompt_features.pixel_values,
            }
            return encoding
       elif text is not None and images is not None:
            UpperCAmelCase_							:       Optional[int]       =				image_features.pixel_values
            return encoding
       elif text is not None:
            return encoding
       elif visual_prompt is not None:
            UpperCAmelCase_							:       Dict       =				{
                'conditional_pixel_values': prompt_features.pixel_values,
            }
            return encoding
       else:
            return BatchEncoding(data=dict(**snake_case_						)				,		tensor_type=snake_case_						)


  def _UpperCamelCase					(			self				,		*snake_case_				,		**snake_case_						):




       '''simple docstring'''

       return self.tokenizer.batch_decode(*snake_case_				,		**snake_case_						)


  def _UpperCamelCase					(			self				,		*snake_case_				,		**snake_case_						):




       '''simple docstring'''

       return self.tokenizer.decode(*snake_case_				,		**snake_case_						)


  @property
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       warnings.warn(
           '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'				,		snake_case_				,		)
       return self.image_processor_class






  @property
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       warnings.warn(
           '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'				,		snake_case_				,		)
       return self.image_processor






