

from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType

class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE			):
	_lowercase  :   Tuple       				=  ["image_processor", "tokenizer"]
	_lowercase  :   Any       				=  "BridgeTowerImageProcessor"
	_lowercase  :   int       				=  ("RobertaTokenizer", "RobertaTokenizerFast")







	def __init__(   self: int  , __UpperCamelCase: Dict  , __UpperCamelCase: int      ):

						'''simple docstring'''





						super().__init__(__UpperCamelCase  , __UpperCamelCase      )







	def __call__(   self: Tuple  , __UpperCamelCase: str  , __UpperCamelCase: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None  , __UpperCamelCase: bool = True  , __UpperCamelCase: Union[bool, str, PaddingStrategy] = False  , __UpperCamelCase: Union[bool, str, TruncationStrategy] = None  , __UpperCamelCase: Optional[int] = None  , __UpperCamelCase: int = 0  , __UpperCamelCase: Optional[int] = None  , __UpperCamelCase: Optional[bool] = None  , __UpperCamelCase: Optional[bool] = None  , __UpperCamelCase: bool = False  , __UpperCamelCase: bool = False  , __UpperCamelCase: bool = False  , __UpperCamelCase: bool = False  , __UpperCamelCase: bool = True  , __UpperCamelCase: Optional[Union[str, TensorType]] = None  , **__UpperCamelCase: Union[str, Any]  , ):

						'''simple docstring'''





						__magic_name__							=    self.tokenizer(
						    text=__UpperCamelCase  , add_special_tokens=__UpperCamelCase  , padding=__UpperCamelCase  , truncation=__UpperCamelCase  , max_length=__UpperCamelCase  , stride=__UpperCamelCase  , pad_to_multiple_of=__UpperCamelCase  , return_token_type_ids=__UpperCamelCase  , return_attention_mask=__UpperCamelCase  , return_overflowing_tokens=__UpperCamelCase  , return_special_tokens_mask=__UpperCamelCase  , return_offsets_mapping=__UpperCamelCase  , return_length=__UpperCamelCase  , verbose=__UpperCamelCase  , return_tensors=__UpperCamelCase  , **__UpperCamelCase  , )
						# add pixel_values + pixel_mask
						__magic_name__							=    self.image_processor(
						    __UpperCamelCase  , return_tensors=__UpperCamelCase  , do_normalize=__UpperCamelCase  , do_center_crop=__UpperCamelCase  , **__UpperCamelCase      )
						encoding.update(__UpperCamelCase      )

						return encoding







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]  , *__UpperCamelCase: Any  , **__UpperCamelCase: List[str]      ):

						'''simple docstring'''





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







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]  , *__UpperCamelCase: Optional[int]  , **__UpperCamelCase: List[Any]      ):

						'''simple docstring'''





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







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						__magic_name__							=    self.tokenizer.model_input_names
						__magic_name__							=    self.image_processor.model_input_names
						return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names      )      )







from __future__ import annotations




def 					_lowercase     (				a_				:					int				)				->	bool:




					'''simple docstring'''







					__magic_name__							=    str(a_				)
					return len(a_				) == 9 and set(a_				) == set('123456789'				)




def 					_lowercase     (				)				->	int | None:




					'''simple docstring'''







					for base_num in range(9_9_9_9					,4_9_9_9					,-1				):
										__magic_name__							=    1_0_0_0_0_2 * base_num
										if is_9_pandigital(a_				):
															return candidate

					for base_num in range(3_3_3					,9_9					,-1				):
										__magic_name__							=    1_0_0_2_0_0_3 * base_num
										if is_9_pandigital(a_				):
															return candidate

					return None


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




