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







class 							UpperCAmelCase	(   __lowerCamelCase					):
					a__: Tuple			  =				["""image_processor""", """tokenizer"""]
					a__: Tuple			  =				"""EfficientNetImageProcessor"""
					a__: Optional[int]			  =				("""BertTokenizer""", """BertTokenizerFast""")

					def __init__(			self      :					Optional[Any] ,      lowerCAmelCase      :					int ,      lowerCAmelCase      :					Any					):
											super().__init__(lowerCAmelCase ,      lowerCAmelCase					)

					def __call__(			self      :					int ,      lowerCAmelCase      :					Any=None ,      lowerCAmelCase      :					Union[str, Any]=None ,      lowerCAmelCase      :					Any="max_length" ,      lowerCAmelCase      :					str=64 ,      lowerCAmelCase      :					str=None ,      **lowerCAmelCase      :					str					):
											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       :    Any											=  self.tokenizer(
																	    lowerCAmelCase ,      padding=lowerCAmelCase ,      max_length=lowerCAmelCase ,      return_tensors=lowerCAmelCase ,      **lowerCAmelCase					)

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

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

					def        _lowerCAmelCase	(			self      :					str ,      *lowerCAmelCase      :					Any ,      **lowerCAmelCase      :					int					):
											return self.tokenizer.batch_decode(*lowerCAmelCase ,      **lowerCAmelCase					)

					def        _lowerCAmelCase	(			self      :					Dict ,      *lowerCAmelCase      :					List[str] ,      **lowerCAmelCase      :					Dict					):
											return self.tokenizer.decode(*lowerCAmelCase ,      **lowerCAmelCase					)




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




from itertools import combinations_with_replacement

def        lowerCamelCase_      (			UpperCAmelCase_							:				int = 1_00       ):
						lowercase       :    list[int]											=  [*list(range(1							,			21       )       ), 25]
						lowercase       :    list[int]											=  [2 * x for x in range(1							,			21       )] + [50]
						lowercase       :    list[int]											=  [3 * x for x in range(1							,			21       )]
						lowercase       :    list[int]											=  singles + doubles + triples + [0]

						lowercase       :    int											=  0
						lowercase       :    int
						lowercase       :    int
						lowercase       :    int
						lowercase       :    int

						for double in doubles:
												for throwa, throwa in combinations_with_replacement(UpperCAmelCase_							,			2       ):
																		lowercase       :    Union[str, Any]											=  double + throwa + throwa
																		if checkout_total < limit:
																								num_checkouts += 1

						return num_checkouts


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


