






"""simple docstring"""



def      SCREAMING_SNAKE_CASE__    (   snake_case    :      int = 1000							)->						int:






     '''simple docstring'''



     UpperCAmelCase__		:  List[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)
     UpperCAmelCase__		:  Dict				=				[0, 0, 6, 6, 5, 5, 5, 7, 6, 6]

     UpperCAmelCase__		:  int				=				0

     for i in range(1       , n + 1							):
          if i < 1000:
               if i >= 100:
                    # add number of letters for "n hundred"
                    count += ones_counts[i // 100] + 7

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

               if 0 < i % 100 < 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 % 100]
               else:
                    # add number of letters for twenty, twenty one, ..., ninety
                    # nine
                    count += ones_counts[i % 10]
                    count += tens_counts[(i % 100 - i % 10) // 10]
          else:
               count += ones_counts[i // 1000] + 8
     return count


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






"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


a_											=			logging.get_logger(__name__)
class snake_case					(     _UpperCamelCase):







		def __init__(    self					:				str			,      *a__					:				Union[str, Any]			,      **a__					:				Optional[Any]						)				->  None:





						'''simple docstring'''







						warnings.warn(
						    "The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
						    " Please use MobileNetV2ImageProcessor instead."			,      a__			,      )
						super().__init__(*a__			,      **a__						)