




from __future__ import annotations

from collections.abc import Iterator
from typing import Generic, TypeVar

lowerCamelCase__            = TypeVar('''T''')






class 		_lowerCAmelCase       (							Generic[T]	):
			"""simple docstring"""
			def __init__(					self     ,		__SCREAMING_SNAKE_CASE       )		->							Dict:





				"""simple docstring"""







				snake_case__						:     Union[str, Any]		=data
				snake_case__						:     Any		=None


			def __str__(					self       )		->							str:





				"""simple docstring"""







				return f'''{self.data}'''






class 		_lowerCAmelCase       (							Generic[T]	):
			"""simple docstring"""
			def __init__(					self       )		->							None:





				"""simple docstring"""







				snake_case__						:     str		=None
			def __iter__(					self       )		->							Iterator[T]:





				"""simple docstring"""







				snake_case__						:     List[Any]		=self.top
				while node:
					yield node.data
					snake_case__						:     Tuple		=node.next
			def __str__(					self       )		->							str:





				"""simple docstring"""







				return "->".join([str(__A       ) for item in self]       )
			def __len__(					self       )		->							int:





				"""simple docstring"""







				return len(tuple(iter(self       )       )       )
			def 					UpperCAmelCase     (					self       )		->							bool:





				"""simple docstring"""







				return self.top is None
			def 					UpperCAmelCase     (					self     ,		__SCREAMING_SNAKE_CASE       )		->							None:





				"""simple docstring"""







				snake_case__						:     Tuple		=Node(__A       )
				if not self.is_empty():
					snake_case__						:     Union[str, Any]		=self.top
				snake_case__						:     str		=node
			def 					UpperCAmelCase     (					self       )		->							T:





				"""simple docstring"""







				if self.is_empty():
					raise IndexError('''pop from empty stack'''       )
				assert isinstance(self.top     ,		__A       )
				snake_case__						:     Union[str, Any]		=self.top
				snake_case__						:     List[str]		=self.top.next
				return pop_node.data
			def 					UpperCAmelCase     (					self       )		->							T:





				"""simple docstring"""







				if self.is_empty():
					raise IndexError('''peek from empty stack'''       )

				assert self.top is not None
				return self.top.data


			def 					UpperCAmelCase     (					self       )		->							None:





				"""simple docstring"""







				snake_case__						:     Optional[int]		=None


if __name__ == "__main__":
		from doctest import testmod

		testmod()











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




class 	UpperCamelCase_							(  UpperCamelCase__     ):
							lowerCamelCase_							     =       ["image_processor", "tokenizer"]
							lowerCamelCase_							     =       "AutoImageProcessor"
							lowerCamelCase_							     =       "AutoTokenizer"


							def __init__(				self     :Optional[int]				,					__A     :Optional[Any]				,					__A     :Dict		) -> Dict:



									"""simple docstring"""



									super().__init__(__A				,					__A		)
									SCREAMING_SNAKE_CASE__								=   self.image_processor


							def __call__(				self     :int				,					__A     :str=None				,					__A     :int=None				,					__A     :Union[str, Any]=None				,					**__A     :str		) -> Optional[Any]:



									"""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:
											SCREAMING_SNAKE_CASE__								=   self.tokenizer(__A				,					return_tensors=__A				,					**__A		)

									if images is not None:
											SCREAMING_SNAKE_CASE__								=   self.image_processor(__A				,					return_tensors=__A				,					**__A		)

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


							def   _snake_case	(				self     :str				,					*__A     :List[str]				,					**__A     :List[str]		) -> List[Any]:



									"""simple docstring"""



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


							def   _snake_case	(				self     :List[str]				,					*__A     :Any				,					**__A     :Any		) -> Tuple:



									"""simple docstring"""



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


							@property
							def   _snake_case	(				self     :Dict		) -> List[Any]:



									"""simple docstring"""



									return ["input_ids", "attention_mask", "pixel_values"]