






from typing import TYPE_CHECKING

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


a__       =     {'configuration_reformer': ['REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ReformerConfig']}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     ['ReformerTokenizer']

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     ['ReformerTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     [
	    'REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'ReformerAttention',
	    'ReformerForMaskedLM',
	    'ReformerForQuestionAnswering',
	    'ReformerForSequenceClassification',
	    'ReformerLayer',
	    'ReformerModel',
	    'ReformerModelWithLMHead',
	    'ReformerPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_reformer import ReformerTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_reformer_fast import ReformerTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_reformer import (
		    REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ReformerAttention,
		    ReformerForMaskedLM,
		    ReformerForQuestionAnswering,
		    ReformerForSequenceClassification,
		    ReformerLayer,
		    ReformerModel,
		    ReformerModelWithLMHead,
		    ReformerPreTrainedModel,
		)

else:
	import sys

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








def _UpperCAmelCase   (	a						:	int = 1000 ):
							snake_case__  , snake_case__	  =       1, 1
							snake_case__	  =       2
							while True:
														snake_case__	  =       0
														snake_case__	  =       fa + fa
														snake_case__  , snake_case__	  =       fa, f
														index += 1
														for _ in str(a ):
																					i += 1
														if i == n:
																					break
							return index


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