def    lowerCAmelCase_ (     __A							)     ->				bool:







      '''simple docstring'''


      return credit_card_number.startswith(("34", "35", "37", "4", "5", "6")							)




def    lowerCAmelCase_ (     __A							)     ->				bool:







      '''simple docstring'''


      UpperCAmelCase__								=  credit_card_number
      UpperCAmelCase__								=  0
      UpperCAmelCase__								=  len(__A							) - 2
      for i in range(__A,  -1,  -2							):
            #  double the value of every second digit
            UpperCAmelCase__								=  int(cc_number[i]							)
            digit *= 2
            # If doubling of a number results in a two digit number
            # i.e greater than 9(e.g., 6 × 2 = 12),
            # then add the digits of the product (e.g., 12: 1 + 2 = 3, 15: 1 + 5 = 6),
            # to get a single digit number.
            if digit > 9:
                  digit %= 10
                  digit += 1
            UpperCAmelCase__								=  cc_number[:i] + str(__A							) + cc_number[i + 1 :]
            total += digit

      # Sum up the remaining digits
      for i in range(len(__A							) - 1,  -1,  -2							):
            total += int(cc_number[i]							)

      return total % 10 == 0




def    lowerCAmelCase_ (     __A							)     ->				bool:







      '''simple docstring'''


      UpperCAmelCase__								=  f"""{credit_card_number} is an invalid credit card number because"""
      if not credit_card_number.isdigit():
            print(f"""{error_message} it has nonnumerical characters."""							)
            return False

      if not 13 <= len(__A							) <= 16:
            print(f"""{error_message} of its length."""							)
            return False

      if not validate_initial_digits(__A							):
            print(f"""{error_message} of its first two digits."""							)
            return False

      if not luhn_validation(__A							):
            print(f"""{error_message} it fails the Luhn check."""							)
            return False

      print(f"""{credit_card_number} is a valid credit card number."""							)
      return True


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      validate_credit_card_number('4111111111111111')
      validate_credit_card_number('32323')






'''simple docstring'''






import warnings

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






class 			lowercase_	(lowerCamelCase__      ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE    :  Optional[Any]							=			['image_processor', 'tokenizer']
  SCREAMING_SNAKE_CASE    :  Union[str, Any]							=			'CLIPImageProcessor'
  SCREAMING_SNAKE_CASE    :  Union[str, Any]							=			('CLIPTokenizer', 'CLIPTokenizerFast')






  def __init__(      self   :     List[Any]					,lowercase__   :     Dict=None					,lowercase__   :     Union[str, Any]=None					,**lowercase__   :     Tuple			):
   __lowercase							  = None
   if "feature_extractor" in kwargs:
    warnings.warn(
        '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
        ''' instead.'''					,lowercase__					,)
    __lowercase							  = kwargs.pop('''feature_extractor'''			)

   __lowercase							  = 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__(lowercase__					,lowercase__			)






  def __call__(      self   :     List[Any]					,lowercase__   :     str=None					,lowercase__   :     List[Any]=None					,lowercase__   :     Optional[Any]=None					,**lowercase__   :     int			):

   if text is None and images is None:
    raise ValueError('''You have to specify either text or images. Both cannot be none.'''			)

   if text is not None:
    __lowercase							  = self.tokenizer(lowercase__					,return_tensors=lowercase__					,**lowercase__			)

   if images is not None:
    __lowercase							  = self.image_processor(lowercase__					,return_tensors=lowercase__					,**lowercase__			)

   if text is not None and images is not None:
    __lowercase							  = image_features.pixel_values
    return encoding
   elif text is not None:
    return encoding
   else:
    return BatchEncoding(data=dict(**lowercase__			)					,tensor_type=lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,*lowercase__   :     List[str]					,**lowercase__   :     int			):
   return self.tokenizer.batch_decode(*lowercase__					,**lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     List[Any]					,*lowercase__   :     Optional[int]					,**lowercase__   :     Union[str, Any]			):
   return self.tokenizer.decode(*lowercase__					,**lowercase__			)






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[Any]			):
   __lowercase							  = self.tokenizer.model_input_names
   __lowercase							  = self.image_processor.model_input_names
   return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     List[str]			):
   warnings.warn(
       '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''					,lowercase__					,)
   return self.image_processor_class






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]			):
   warnings.warn(
       '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''					,lowercase__					,)
   return self.image_processor

