


def   lowerCamelCase_       (					UpperCAmelCase__ = 1_000      ):



						"""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_000:
																		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 // 1_000] + 8
						return count


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



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A_    :					Optional[Any]             ={
    """configuration_wav2vec2_conformer""": [
        """WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Wav2Vec2ConformerConfig""",
    ],
}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_    :					Union[str, Any]             =[
	    """WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """Wav2Vec2ConformerForAudioFrameClassification""",
	    """Wav2Vec2ConformerForCTC""",
	    """Wav2Vec2ConformerForPreTraining""",
	    """Wav2Vec2ConformerForSequenceClassification""",
	    """Wav2Vec2ConformerForXVector""",
	    """Wav2Vec2ConformerModel""",
	    """Wav2Vec2ConformerPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_wavaveca_conformer import (
	    WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    WavaVecaConformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_wavaveca_conformer import (
		    WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    WavaVecaConformerForAudioFrameClassification,
		    WavaVecaConformerForCTC,
		    WavaVecaConformerForPreTraining,
		    WavaVecaConformerForSequenceClassification,
		    WavaVecaConformerForXVector,
		    WavaVecaConformerModel,
		    WavaVecaConformerPreTrainedModel,
		)

else:
	import sys

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