






def   SCREAMING_SNAKE_CASE__						(   snake_case_ = 1_0_0_0  )   ->  int:


	"""simple docstring"""



	a		=			[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)
	a		=			[0, 0, 6, 6, 5, 5, 5, 7, 6, 6]

	a		=			0

	for i in range(1,  n + 1  ):
		if i < 1_0_0_0:
			if i >= 1_0_0:
				# add number of letters for "n hundred"
				count += ones_counts[i // 1_0_0] + 7

				if i % 1_0_0 != 0:
					# add number of letters for "and" if number is not multiple
					# of 100
					count += 3

			if 0 < i % 1_0_0 < 2_0:
				# 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_0_0]
			else:
				# add number of letters for twenty, twenty one, ..., ninety
				# nine
				count += ones_counts[i % 1_0]
				count += tens_counts[(i % 1_0_0 - i % 1_0) // 1_0]
		else:
			count += ones_counts[i // 1_0_0_0] + 8
	return count


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













from typing import TYPE_CHECKING

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


UpperCamelCase__						:      Tuple								=					{
    """configuration_nystromformer""": ["""NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NystromformerConfig"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__						:      Any								=					[
				    """NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """NystromformerForMaskedLM""",
				    """NystromformerForMultipleChoice""",
				    """NystromformerForQuestionAnswering""",
				    """NystromformerForSequenceClassification""",
				    """NystromformerForTokenClassification""",
				    """NystromformerLayer""",
				    """NystromformerModel""",
				    """NystromformerPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_nystromformer import (
								    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    NystromformerForMaskedLM,
								    NystromformerForMultipleChoice,
								    NystromformerForQuestionAnswering,
								    NystromformerForSequenceClassification,
								    NystromformerForTokenClassification,
								    NystromformerLayer,
								    NystromformerModel,
								    NystromformerPreTrainedModel,
								)


else:
				import sys

				UpperCamelCase__						:      str								=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





