


"""simple docstring"""






def 			A__		(					_UpperCAmelCase    :      int	)							->	int:

	'''simple docstring'''


	barcode //= 10  # exclude the last digit
	snake_case__  :						str		=      False
	snake_case__  :						Optional[Any]		=      0

	# extract and check each digit
	while barcode != 0:
		snake_case__  :						Tuple		=      1 if checker else 3
		s += mult * (barcode % 10)
		barcode //= 10
		snake_case__  :						int		=      not checker

	return (10 - (s % 10)) % 10



def 			A__		(					_UpperCAmelCase    :      int	)							->	bool:

	'''simple docstring'''


	return len(str(_UpperCAmelCase	)	) == 13 and get_check_digit(_UpperCAmelCase	) == barcode % 10



def 			A__		(					_UpperCAmelCase    :      str	)							->	int:

	'''simple docstring'''


	if str(_UpperCAmelCase	).isalpha():
		snake_case__  :						List[str]		=      F"""Barcode '{barcode}' has alphabetic characters."""
		raise ValueError(_UpperCAmelCase	)
	elif int(_UpperCAmelCase	) < 0:
		raise ValueError("The entered barcode has a negative value. Try again."	)
	else:
		return int(_UpperCAmelCase	)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					lowercase  		=			get_barcode(input("""Barcode: """).strip())

					if is_valid(barcode):
										print(f"'{barcode}' is a valid barcode.")
					else:
										print(f"'{barcode}' is NOT a valid barcode.")









"""simple docstring"""






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


class 			SCREAMING_SNAKE_CASE_  (   _lowercase):




							'''simple docstring'''





							__magic_name__					:     Union[str, Any]				  =  ['''image_processor''', '''tokenizer''']
							__magic_name__					:     Optional[int]				  =  '''EfficientNetImageProcessor'''
							__magic_name__					:     Optional[Any]				  =  ('''BertTokenizer''', '''BertTokenizerFast''')




							def __init__(						self	,					lowerCamelCase__	,					lowerCamelCase__)   ->	str:







								'''simple docstring'''




								super().__init__(lowerCamelCase__	,					lowerCamelCase__)




							def __call__(						self	,					lowerCamelCase__=None	,					lowerCamelCase__=None	,					lowerCamelCase__="max_length"	,					lowerCamelCase__=64	,					lowerCamelCase__=None	,					**lowerCamelCase__)   ->	List[str]:







								'''simple docstring'''




								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:
									snake_case__  :						int		=      self.tokenizer(
									    lowerCamelCase__	,					padding=lowerCamelCase__	,					max_length=lowerCamelCase__	,					return_tensors=lowerCamelCase__	,					**lowerCamelCase__)

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

								if text is not None and images is not None:
									snake_case__  :						List[str]		=      image_features.pixel_values
									return encoding
								elif text is not None:
									return encoding
								else:
									return BatchEncoding(data=dict(**lowerCamelCase__)	,					tensor_type=lowerCamelCase__)




							def        UpperCAmelCase (						self	,					*lowerCamelCase__	,					**lowerCamelCase__)   ->	int:







								'''simple docstring'''




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




							def        UpperCAmelCase (						self	,					*lowerCamelCase__	,					**lowerCamelCase__)   ->	Optional[Any]:







								'''simple docstring'''




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







							@property
							def        UpperCAmelCase (						self)   ->	Tuple:







								'''simple docstring'''




								snake_case__  :						Dict		=      self.tokenizer.model_input_names
								snake_case__  :						Optional[int]		=      self.image_processor.model_input_names
								return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))





