






def 					lowercase__				(					__snake_case   :							int = 1_000  ):


					'''simple docstring'''


					UpperCAmelCase_	,  UpperCAmelCase_   :				Dict						=						1, 1
					UpperCAmelCase_   :				List[str]						=						[]
					for i in range(1					,	n + 1  ):
										UpperCAmelCase_   :				Optional[int]						=						prev_numerator + 2 * prev_denominator
										UpperCAmelCase_   :				Any						=						prev_numerator + prev_denominator
										if len(str(__snake_case  )  ) > len(str(__snake_case  )  ):
															result.append(__snake_case  )
										UpperCAmelCase_   :				Dict						=						numerator
										UpperCAmelCase_   :				Optional[Any]						=						denominator

					return len(__snake_case  )


if __name__ == "__main__":
		print(F'{solution() = }')














from typing import TYPE_CHECKING

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


__UpperCAmelCase     							=						{
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		pass

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase     							=						[
		    'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'RoCBertForCausalLM',
		    'RoCBertForMaskedLM',
		    'RoCBertForMultipleChoice',
		    'RoCBertForPreTraining',
		    'RoCBertForQuestionAnswering',
		    'RoCBertForSequenceClassification',
		    'RoCBertForTokenClassification',
		    'RoCBertLayer',
		    'RoCBertModel',
		    'RoCBertPreTrainedModel',
		    'load_tf_weights_in_roc_bert',
		]

if TYPE_CHECKING:
		from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
		from .tokenization_roc_bert import RoCBertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				raise OptionalDependencyNotAvailable()

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_roc_bert import (
				    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RoCBertForCausalLM,
				    RoCBertForMaskedLM,
				    RoCBertForMultipleChoice,
				    RoCBertForPreTraining,
				    RoCBertForQuestionAnswering,
				    RoCBertForSequenceClassification,
				    RoCBertForTokenClassification,
				    RoCBertLayer,
				    RoCBertModel,
				    RoCBertPreTrainedModel,
				    load_tf_weights_in_roc_bert,
				)


else:
		import sys

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






