



"""simple docstring"""


from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class 			_a (					__A):
			"""simple docstring"""
			UpperCamelCase__			      =	["""image_processor""", """tokenizer"""]
			UpperCamelCase__			      =	"""AutoImageProcessor"""
			UpperCamelCase__			      =	"""AutoTokenizer"""



			def __init__(		self     :    Dict				,   __UpperCamelCase     :    int				,   __UpperCamelCase     :    List[str]   )->str:
							super().__init__(__UpperCamelCase				,   __UpperCamelCase   )
							_UpperCAmelCase					=    self.image_processor



			def __call__(		self     :    Dict				,   __UpperCamelCase     :    Union[str, Any]=None				,   __UpperCamelCase     :    int=None				,   __UpperCamelCase     :    str=None				,   **__UpperCamelCase     :    Dict   )->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:
											_UpperCAmelCase					=    self.tokenizer(__UpperCamelCase				,   return_tensors=__UpperCamelCase				,   **__UpperCamelCase   )

							if images is not None:
											_UpperCAmelCase					=    self.image_processor(__UpperCamelCase				,   return_tensors=__UpperCamelCase				,   **__UpperCamelCase   )

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



			def  lowercase__						(		self     :    Union[str, Any]				,   *__UpperCamelCase     :    List[str]				,   **__UpperCamelCase     :    int   )->List[str]:
							return self.tokenizer.batch_decode(*__UpperCamelCase				,   **__UpperCamelCase   )



			def  lowercase__						(		self     :    Union[str, Any]				,   *__UpperCamelCase     :    Any				,   **__UpperCamelCase     :    str   )->List[Any]:
							return self.tokenizer.decode(*__UpperCamelCase				,   **__UpperCamelCase   )



			@property
			def  lowercase__						(		self     :    Dict   )->Optional[int]:
							return ["input_ids", "attention_mask", "pixel_values"]








"""simple docstring"""


import operator







def  lowercase	(      _SCREAMING_SNAKE_CASE   :						list					,     _SCREAMING_SNAKE_CASE   :						bool = False					,     _SCREAMING_SNAKE_CASE   :						list | None = None				):






				'''simple docstring'''



				_UpperCAmelCase					=    operator.lt if reverse else operator.gt
				_UpperCAmelCase					=    solution or []

				if not arr:
								return solution

				_UpperCAmelCase					=    [arr.pop(0				)]
				for i, item in enumerate(_SCREAMING_SNAKE_CASE				):
								if _operator(_SCREAMING_SNAKE_CASE					,     sublist[-1]				):
												sublist.append(_SCREAMING_SNAKE_CASE				)
												arr.pop(_SCREAMING_SNAKE_CASE				)

    #  merging sublist into solution list
				if not solution:
								solution.extend(_SCREAMING_SNAKE_CASE				)
				else:
								while sublist:
												_UpperCAmelCase					=    sublist.pop(0				)
												for i, xx in enumerate(_SCREAMING_SNAKE_CASE				):
																if not _operator(_SCREAMING_SNAKE_CASE					,     _SCREAMING_SNAKE_CASE				):
																				solution.insert(_SCREAMING_SNAKE_CASE					,     _SCREAMING_SNAKE_CASE				)
																				break
												else:
																solution.append(_SCREAMING_SNAKE_CASE				)

				strand_sort(_SCREAMING_SNAKE_CASE					,     _SCREAMING_SNAKE_CASE					,     _SCREAMING_SNAKE_CASE				)
				return solution


if __name__ == "__main__":
					assert strand_sort([4, 3, 5, 1, 2]) == [1, 2, 3, 4, 5]
					assert strand_sort([4, 3, 5, 1, 2], reverse=True) == [5, 4, 3, 2, 1]



