
'''simple docstring'''
import warnings

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







class  __A				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       =['''image_processor''', '''tokenizer''']
 lowerCamelCase				       ='''ViTImageProcessor'''
 lowerCamelCase				       =('''CLIPTokenizer''', '''CLIPTokenizerFast''')
 def __init__(   self			:    Any				,   lowerCamelCase			:    Any=None				,   lowerCamelCase			:    Optional[int]=None				,   **lowerCamelCase			:    Any       ):



   """simple docstring"""





   __A		:     Union[str, Any]												=		None
   if "feature_extractor" in kwargs:
     warnings.warn(
         """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
         """ instead."""				,   lowerCamelCase				,   )
     __A		:     List[str]												=		kwargs.pop("""feature_extractor"""       )

   __A		:     Dict												=		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__(lowerCamelCase				,   lowerCamelCase       )
 def __call__(   self			:    Optional[Any]				,   lowerCamelCase			:    Optional[Any]=None				,   lowerCamelCase			:    Tuple=None				,   lowerCamelCase			:    int=None				,   lowerCamelCase			:    Tuple=None				,   **lowerCamelCase			:    str       ):



   """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:
     __A		:     Optional[int]												=		self.tokenizer(lowerCamelCase				,   return_tensors=lowerCamelCase				,   **lowerCamelCase       )

   if visual_prompt is not None:
     __A		:     List[str]												=		self.image_processor(lowerCamelCase				,   return_tensors=lowerCamelCase				,   **lowerCamelCase       )

   if images is not None:
     __A		:     List[str]												=		self.image_processor(lowerCamelCase				,   return_tensors=lowerCamelCase				,   **lowerCamelCase       )

   if visual_prompt is not None and images is not None:
     __A		:     str												=		{
         """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:
     __A		:     List[str]												=		image_features.pixel_values
     return encoding
   elif text is not None:
     return encoding
   elif visual_prompt is not None:
     __A		:     Union[str, Any]												=		{
         """conditional_pixel_values""": prompt_features.pixel_values,
     }
     return encoding
   else:
     return BatchEncoding(data=dict(**lowerCamelCase       )				,   tensor_type=lowerCamelCase       )
 def 		lowercase_(   self			:    List[Any]				,   *lowerCamelCase			:    List[str]				,   **lowerCamelCase			:    Any       ):



   """simple docstring"""





   return self.tokenizer.batch_decode(*lowerCamelCase				,   **lowerCamelCase       )
 def 		lowercase_(   self			:    int				,   *lowerCamelCase			:    List[str]				,   **lowerCamelCase			:    Tuple       ):



   """simple docstring"""





   return self.tokenizer.decode(*lowerCamelCase				,   **lowerCamelCase       )
 @property
 def 		lowercase_(   self			:    Optional[Any]       ):



   """simple docstring"""





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






 @property
 def 		lowercase_(   self			:    int       ):



   """simple docstring"""





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





'''simple docstring'''
def        A_     (						__SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  bool = False )				->       bool:





  """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 > 3_3170_4406_4679_8873_8596_1981 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
  __A		:     Optional[int]												=		[
      2047,
      137_3653,
      2532_6001,
      32_1503_1751,
      2_1523_0289_8747,
      3_4747_4966_0383,
      341_5500_7172_8321,
      1,
      382_5123_0565_4641_3051,
      1,
      1,
      3186_6585_7834_0311_5116_7461,
      3_3170_4406_4679_8873_8596_1981,
  ]

  __A		:     Optional[int]												=		[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
  for idx, _p in enumerate(__SCREAMING_SNAKE_CASE			,     1 ):
    if n < _p:
      # then we have our last prime to check
      __A		:     Union[str, Any]												=		primes[:idx]
      break
  __A							,					__A		:     int												=		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:
    __A		:     int												=		False
    for r in range(__SCREAMING_SNAKE_CASE ):
      __A		:     Optional[Any]												=		pow(__SCREAMING_SNAKE_CASE			,     d * 2**r			,     __SCREAMING_SNAKE_CASE )
      # see article for analysis explanation for m
      if (r == 0 and m == 1) or ((m + 1) % n == 0):
        __A		:     Optional[int]												=		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        A_     (						)				->       None:





  """simple docstring"""

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

  assert not miller_rabin(83_8201 )
  assert miller_rabin(83_8207 )
  # 1_373_653

  assert not miller_rabin(1731_6001 )
  assert miller_rabin(1731_6017 )
  # 25_326_001

  assert not miller_rabin(30_7838_6641 )
  assert miller_rabin(30_7838_6653 )
  # 3_215_031_751

  assert not miller_rabin(1_7130_4557_4801 )
  assert miller_rabin(1_7130_4557_4819 )
  # 2_152_302_898_747

  assert not miller_rabin(2_7797_9972_8307 )
  assert miller_rabin(2_7797_9972_8327 )
  # 3_474_749_660_383

  assert not miller_rabin(113_8500_2390_9441 )
  assert miller_rabin(113_8500_2390_9527 )
  # 341_550_071_728_321

  assert not miller_rabin(127_5041_0188_4880_4351 )
  assert miller_rabin(127_5041_0188_4880_4391 )
  # 3_825_123_056_546_413_051

  assert not miller_rabin(796_6646_4458_5077_8779_1867 )
  assert miller_rabin(796_6646_4458_5077_8779_1951 )
  # 318_665_857_834_031_151_167_461

  assert not miller_rabin(5528_4067_7446_6478_9766_0333 )
  assert miller_rabin(5528_4067_7446_6478_9766_0359 )
  # 3_317_044_064_679_887_385_961_981
  # upper limit for probabilistic test


if __name__ == "__main__":
     test_miller_rabin()



