

def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_ = 1_0			)->						str:



    """simple docstring"""






    if not isinstance(SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			) or n < 0:
        raise ValueError("Invalid input"			)
    UpperCamelCase_			  =						1_0**n
    UpperCamelCase_			  =						2_8_4_3_3 * (pow(2			,						7_8_3_0_4_5_7			,						SCREAMING_SNAKE_CASE_			)) + 1
    return str(number % modulus			)


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

 testmod()
 print(F'''{solution(10) = }''')



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 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:Dict										=      ["""image_processor""", """tokenizer"""]
     UpperCamelCase_	:str										=      """BridgeTowerImageProcessor"""
     UpperCamelCase_	:Tuple										=      ("""RobertaTokenizer""", """RobertaTokenizerFast""")






     def __init__(				self		,						_lowercase		,						_lowercase	)->     Any:
         super().__init__(_lowercase		,						_lowercase	)






     def __call__(				self		,						_lowercase		,						_lowercase = None		,						_lowercase = True		,						_lowercase = False		,						_lowercase = None		,						_lowercase = None		,						_lowercase = 0		,						_lowercase = None		,						_lowercase = None		,						_lowercase = None		,						_lowercase = False		,						_lowercase = False		,						_lowercase = False		,						_lowercase = False		,						_lowercase = True		,						_lowercase = None		,						**_lowercase		,						)->     BatchEncoding:
         UpperCamelCase_			  =						self.tokenizer(
             text=_lowercase		,						add_special_tokens=_lowercase		,						padding=_lowercase		,						truncation=_lowercase		,						max_length=_lowercase		,						stride=_lowercase		,						pad_to_multiple_of=_lowercase		,						return_token_type_ids=_lowercase		,						return_attention_mask=_lowercase		,						return_overflowing_tokens=_lowercase		,						return_special_tokens_mask=_lowercase		,						return_offsets_mapping=_lowercase		,						return_length=_lowercase		,						verbose=_lowercase		,						return_tensors=_lowercase		,						**_lowercase		,						)
         # add pixel_values + pixel_mask
         UpperCamelCase_			  =						self.image_processor(
             _lowercase		,						return_tensors=_lowercase		,						do_normalize=_lowercase		,						do_center_crop=_lowercase		,						**_lowercase	)
         encoding.update(_lowercase	)

         return encoding






     def 	UpperCAmelCase_				(				self		,						*_lowercase		,						**_lowercase	)->     Union[str, Any]:
         return self.tokenizer.batch_decode(*_lowercase		,						**_lowercase	)






     def 	UpperCAmelCase_				(				self		,						*_lowercase		,						**_lowercase	)->     List[Any]:
         return self.tokenizer.decode(*_lowercase		,						**_lowercase	)






     @property
     def 	UpperCAmelCase_				(				self	)->     Any:
         UpperCamelCase_			  =						self.tokenizer.model_input_names
         UpperCamelCase_			  =						self.image_processor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names	)	)
