

"""simple docstring"""





def   __SCREAMING_SNAKE_CASE  (      ):
	return 1

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	return 0 if x < 0 else two_pence(x - 2 ) + one_pence()

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	return 0 if x < 0 else five_pence(x - 5 ) + two_pence(A_ )

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	return 0 if x < 0 else ten_pence(x - 10 ) + five_pence(A_ )

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	return 0 if x < 0 else twenty_pence(x - 20 ) + ten_pence(A_ )

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	return 0 if x < 0 else fifty_pence(x - 50 ) + twenty_pence(A_ )

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	return 0 if x < 0 else one_pound(x - 1_00 ) + fifty_pence(A_ )

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	return 0 if x < 0 else two_pound(x - 2_00 ) + one_pound(A_ )

def   __SCREAMING_SNAKE_CASE  (      A_ = 2_00 ):
	return two_pound(A_ )


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







"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__UpperCamelCase  :      Optional[Any]							      =		{
    '''configuration_rag''': ['''RagConfig'''],
    '''retrieval_rag''': ['''RagRetriever'''],
    '''tokenization_rag''': ['''RagTokenizer'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase  :      Tuple							      =		[
							    '''RagModel''',
							    '''RagPreTrainedModel''',
							    '''RagSequenceForGeneration''',
							    '''RagTokenForGeneration''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase  :      Union[str, Any]							      =		[
							    '''TFRagModel''',
							    '''TFRagPreTrainedModel''',
							    '''TFRagSequenceForGeneration''',
							    '''TFRagTokenForGeneration''',
							]


if TYPE_CHECKING:
							from .configuration_rag import RagConfig
							from .retrieval_rag import RagRetriever
							from .tokenization_rag import RagTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_rag import (
														    TFRagModel,
														    TFRagPreTrainedModel,
														    TFRagSequenceForGeneration,
														    TFRagTokenForGeneration,
														)

else:
							import sys

							__UpperCamelCase  :      Dict							      =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




