


'''simple docstring'''






from collections.abc import Generator







def 							UpperCamelCase_     (       ):
  '''simple docstring'''





  lowerCAmelCase_,				lowerCAmelCase_     : Dict     =  0, 1
  while True:
    lowerCAmelCase_,				lowerCAmelCase_     : List[Any]     =  b, a + b
    yield b







def 							UpperCamelCase_     (       A__   :  int = 10_00   ):
  '''simple docstring'''





  lowerCAmelCase_     : List[Any]     =  1
  lowerCAmelCase_     : int     =  fibonacci_generator()
  while len(str(next(A__   )   )   ) < n:
    answer += 1
  return answer + 1


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







'''simple docstring'''






from typing import TYPE_CHECKING

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


__A   :    str											= {
    "configuration_audio_spectrogram_transformer": [
        "AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ASTConfig",
    ]
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A   :    List[str]											= [
      "AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "ASTForAudioClassification",
      "ASTModel",
      "ASTPreTrainedModel",
  ]

try:
  if not is_speech_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A   :    Union[str, Any]											= ["ASTFeatureExtractor"]

if TYPE_CHECKING:
  from .configuration_audio_spectrogram_transformer import (
      AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      ASTConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_audio_spectrogram_transformer import (
        AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        ASTForAudioClassification,
        ASTModel,
        ASTPreTrainedModel,
    )

  try:
    if not is_speech_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
  import sys

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



