






import warnings
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     A    (      SCREAMING_SNAKE_CASE__						):






 """simple docstring"""





 __a			:						Tuple      =						['''image_processor''', '''tokenizer''']
 __a			:						str      =						'''ViltImageProcessor'''
 __a			:						List[str]      =						('''BertTokenizer''', '''BertTokenizerFast''')
 def __init__(							self			,     __lowerCAmelCase=None			,     __lowerCAmelCase=None			,     **__lowerCAmelCase ):
       UpperCamelCase_				:   List[str]					    =							None
       if "feature_extractor" in kwargs:
             warnings.warn(
                 """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
                 """ instead."""			,     __lowerCAmelCase			,     )
             UpperCamelCase_				:   Optional[int]					    =							kwargs.pop("""feature_extractor""" )

       UpperCamelCase_				:   List[Any]					    =							image_processor if image_processor is not None else feature_extractor
       if image_processor is None:
             raise ValueError("""You need to specify an `image_processor`.""" )
       if tokenizer is None:
             raise ValueError("""You need to specify a `tokenizer`.""" )

       super().__init__(__lowerCAmelCase			,     __lowerCAmelCase )
       UpperCamelCase_				:   Any					    =							self.image_processor
 def __call__(							self			,     __lowerCAmelCase			,     __lowerCAmelCase = None			,     __lowerCAmelCase = True			,     __lowerCAmelCase = False			,     __lowerCAmelCase = None			,     __lowerCAmelCase = None			,     __lowerCAmelCase = 0			,     __lowerCAmelCase = None			,     __lowerCAmelCase = None			,     __lowerCAmelCase = None			,     __lowerCAmelCase = False			,     __lowerCAmelCase = False			,     __lowerCAmelCase = False			,     __lowerCAmelCase = False			,     __lowerCAmelCase = True			,     __lowerCAmelCase = None			,     **__lowerCAmelCase			,     ):
       UpperCamelCase_				:   Optional[int]					    =							self.tokenizer(
           text=__lowerCAmelCase			,     add_special_tokens=__lowerCAmelCase			,     padding=__lowerCAmelCase			,     truncation=__lowerCAmelCase			,     max_length=__lowerCAmelCase			,     stride=__lowerCAmelCase			,     pad_to_multiple_of=__lowerCAmelCase			,     return_token_type_ids=__lowerCAmelCase			,     return_attention_mask=__lowerCAmelCase			,     return_overflowing_tokens=__lowerCAmelCase			,     return_special_tokens_mask=__lowerCAmelCase			,     return_offsets_mapping=__lowerCAmelCase			,     return_length=__lowerCAmelCase			,     verbose=__lowerCAmelCase			,     return_tensors=__lowerCAmelCase			,     **__lowerCAmelCase			,     )
       # add pixel_values + pixel_mask
       UpperCamelCase_				:   int					    =							self.image_processor(__lowerCAmelCase			,     return_tensors=__lowerCAmelCase )
       encoding.update(__lowerCAmelCase )

       return encoding
 def   _UpperCAmelCase       (							self			,     *__lowerCAmelCase			,     **__lowerCAmelCase ):
       return self.tokenizer.batch_decode(*__lowerCAmelCase			,     **__lowerCAmelCase )
 def   _UpperCAmelCase       (							self			,     *__lowerCAmelCase			,     **__lowerCAmelCase ):
       return self.tokenizer.decode(*__lowerCAmelCase			,     **__lowerCAmelCase )
 @property
 def   _UpperCAmelCase       (							self ):
       UpperCamelCase_				:   List[Any]					    =							self.tokenizer.model_input_names
       UpperCamelCase_				:   Optional[int]					    =							self.image_processor.model_input_names
       return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names ) )
 @property
 def   _UpperCAmelCase       (							self ):
       warnings.warn(
           """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""			,     __lowerCAmelCase			,     )
       return self.image_processor_class





 @property
 def   _UpperCAmelCase       (							self ):
       warnings.warn(
           """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""			,     __lowerCAmelCase			,     )
       return self.image_processor














'''simple docstring'''

def 							snake_case					(     )       ->				int:





      """simple docstring"""

      return 1



def 							snake_case					(     a_							: int	)       ->				int:





      """simple docstring"""

      return 0 if x < 0 else two_pence(x - 2	) + one_pence()



def 							snake_case					(     a_							: int	)       ->				int:





      """simple docstring"""

      return 0 if x < 0 else five_pence(x - 5	) + two_pence(a_	)



def 							snake_case					(     a_							: int	)       ->				int:





      """simple docstring"""

      return 0 if x < 0 else ten_pence(x - 10	) + five_pence(a_	)



def 							snake_case					(     a_							: int	)       ->				int:





      """simple docstring"""

      return 0 if x < 0 else twenty_pence(x - 20	) + ten_pence(a_	)



def 							snake_case					(     a_							: int	)       ->				int:





      """simple docstring"""

      return 0 if x < 0 else fifty_pence(x - 50	) + twenty_pence(a_	)



def 							snake_case					(     a_							: int	)       ->				int:





      """simple docstring"""

      return 0 if x < 0 else one_pound(x - 100	) + fifty_pence(a_	)



def 							snake_case					(     a_							: int	)       ->				int:





      """simple docstring"""

      return 0 if x < 0 else two_pound(x - 200	) + one_pound(a_	)



def 							snake_case					(     a_							: int = 200	)       ->				int:





      """simple docstring"""

      return two_pound(a_	)


if __name__ == "__main__":
      print(solution(int(input().strip())))






