






'''simple docstring'''






def 							_SCREAMING_SNAKE_CASE	(					A	:							int = 10_00	)     ->			int:







   """simple docstring"""
   __snake_case					:   Optional[Any]  				=			[0, 3, 3, 5, 4, 4, 3, 5, 5, 4, 3, 6, 6, 8, 8, 7, 7, 9, 8, 8]
   # number of letters in twenty, thirty, ..., ninety (0 for numbers less than
   # 20 due to inconsistency in teens)
   __snake_case					:   Any  				=			[0, 0, 6, 6, 5, 5, 5, 7, 6, 6]

   __snake_case					:   Tuple  				=			0

   for i in range(1	,		n + 1	):
      if i < 10_00:
         if i >= 1_00:
            # add number of letters for "n hundred"
            count += ones_counts[i // 1_00] + 7

            if i % 1_00 != 0:
               # add number of letters for "and" if number is not multiple
               # of 100
               count += 3

         if 0 < i % 1_00 < 20:
            # add number of letters for one, two, three, ..., nineteen
            # (could be combined with below if not for inconsistency in
            # teens)
            count += ones_counts[i % 1_00]
         else:
            # add number of letters for twenty, twenty one, ..., ninety
            # nine
            count += ones_counts[i % 10]
            count += tens_counts[(i % 1_00 - i % 10) // 10]
      else:
         count += ones_counts[i // 10_00] + 8
   return count


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







'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A     						= {
    '''configuration_prophetnet''': ['''PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ProphetNetConfig'''],
    '''tokenization_prophetnet''': ['''ProphetNetTokenizer'''],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __A     						= [
          '''PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''ProphetNetDecoder''',
          '''ProphetNetEncoder''',
          '''ProphetNetForCausalLM''',
          '''ProphetNetForConditionalGeneration''',
          '''ProphetNetModel''',
          '''ProphetNetPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_prophetnet import PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ProphetNetConfig
      from .tokenization_prophetnet import ProphetNetTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_prophetnet import (
                PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                ProphetNetDecoder,
                ProphetNetEncoder,
                ProphetNetForCausalLM,
                ProphetNetForConditionalGeneration,
                ProphetNetModel,
                ProphetNetPreTrainedModel,
            )

else:
      import sys

      __A     						= _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)