def A__	(      lowercase:  Optional[Any]       )					->		int:
       if n == 1 or not isinstance(lowerCamelCase_,		lowerCamelCase_       ):
              return 0
       elif n == 2:
              return 1
       else:
              A    :  List[str]								=[0, 1]
              for i in range(2,		n + 1       ):
                     sequence.append(sequence[i - 1] + sequence[i - 2]       )

              return sequence[n]



def A__	(      lowercase:  str       )					->		int:
       A    :  Tuple								=0
       A    :  List[str]								=2

       while digits < n:
              index += 1
              A    :  Optional[int]								=len(str(fibonacci(lowerCamelCase_       )       )       )

       return index



def A__	(      lowercase:  Union[str, Any] = 1_000       )					->		int:
       return fibonacci_digits_index(lowerCamelCase_       )


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










from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE			: str				   =					{
    "configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE			: int				   =					[
     "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST",
     "GPTBigCodeForSequenceClassification",
     "GPTBigCodeForTokenClassification",
     "GPTBigCodeForCausalLM",
     "GPTBigCodeModel",
     "GPTBigCodePreTrainedModel",
 ]

if TYPE_CHECKING:
 from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_bigcode import (
      GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTBigCodeForCausalLM,
      GPTBigCodeForSequenceClassification,
      GPTBigCodeForTokenClassification,
      GPTBigCodeModel,
      GPTBigCodePreTrainedModel,
  )


else:
 import sys

 SCREAMING_SNAKE_CASE			: List[Any]				   =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


