

"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCamelCase										=		{
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		["LxmertTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		[
     "LxmertEncoder",
     "LxmertForPreTraining",
     "LxmertForQuestionAnswering",
     "LxmertModel",
     "LxmertPreTrainedModel",
     "LxmertVisualFeatureEncoder",
     "LxmertXLayer",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		[
     "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFLxmertForPreTraining",
     "TFLxmertMainLayer",
     "TFLxmertModel",
     "TFLxmertPreTrainedModel",
     "TFLxmertVisualFeatureEncoder",
 ]


if TYPE_CHECKING:
 from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
 from .tokenization_lxmert import LxmertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_lxmert_fast import LxmertTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_lxmert import (
      LxmertEncoder,
      LxmertForPreTraining,
      LxmertForQuestionAnswering,
      LxmertModel,
      LxmertPreTrainedModel,
      LxmertVisualFeatureEncoder,
      LxmertXLayer,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_lxmert import (
      TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFLxmertForPreTraining,
      TFLxmertMainLayer,
      TFLxmertModel,
      TFLxmertPreTrainedModel,
      TFLxmertVisualFeatureEncoder,
  )

else:
 import sys

 __lowerCamelCase										=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




"""simple docstring"""






def 	lowercase      (   ) ->      int:
 return 1





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else two_pence(x - 2						) + one_pence()





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else five_pence(x - 5						) + two_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else ten_pence(x - 10						) + five_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else twenty_pence(x - 20						) + ten_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else fifty_pence(x - 50						) + twenty_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else one_pound(x - 100						) + fifty_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else two_pound(x - 200						) + one_pound(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase = 200						) ->      int:
 return two_pound(__UpperCamelCase						)


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

