


"""simple docstring"""






def 	lowercase      (   __UpperCamelCase = 1000						) ->      int:
 __magic_name__   ,						__magic_name__     =      1, 1
 __magic_name__     =      2
 while True:
  __magic_name__     =      0
  __magic_name__     =      fa + fa
  __magic_name__   ,						__magic_name__     =      fa, f
  index += 1
  for _ in str(__UpperCamelCase						):
   i += 1
  if i == n:
   break
 return index


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




"""simple docstring"""






import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


__lowerCamelCase										=		[
    {"dataset": "wikipedia", "config_name": "20220301.de"},
    {"dataset": "wikipedia", "config_name": "20220301.en"},
    {"dataset": "wikipedia", "config_name": "20220301.fr"},
    {"dataset": "wikipedia", "config_name": "20220301.frr"},
    {"dataset": "wikipedia", "config_name": "20220301.it"},
    {"dataset": "wikipedia", "config_name": "20220301.simple"},
    {"dataset": "snli", "config_name": "plain_text"},
    {"dataset": "eli5", "config_name": "LFQA_reddit"},
    {"dataset": "wiki40b", "config_name": "en"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.compressed"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.no_index"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.multiset.no_index"},
    {"dataset": "natural_questions", "config_name": "default"},
]





def 	lowercase      (   __UpperCamelCase=True						) ->      List[Any]:
 if with_config:
  return [
      {
          "testcase_name": d["dataset"] + "/" + d["config_name"],
          "dataset": d["dataset"],
          "config_name": d["config_name"],
      }
      for d in DATASETS_ON_HF_GCP
  ]
 else:
  return [
      {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
  ]
@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=__UpperCAmelCase     )     )
class        _lowercase					(     __UpperCAmelCase     ):
     _lowerCamelCase     =       None
     _lowerCamelCase     =       None







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_ ,						UpperCamelCase_       ):
      with TemporaryDirectory() as tmp_dir:
       __magic_name__     =      dataset_module_factory(UpperCamelCase_ ,						cache_dir=UpperCamelCase_       )

       __magic_name__     =      import_main_class(dataset_module.module_path ,						dataset=UpperCamelCase_       )

       __magic_name__     =      builder_cls(
           cache_dir=UpperCamelCase_ ,						config_name=UpperCamelCase_ ,						hash=dataset_module.hash ,						)

       __magic_name__     =      '''/'''.join(
           [
               HF_GCP_BASE_URL,
               builder_instance._relative_data_dir(with_hash=UpperCamelCase_       ).replace(os.sep ,						'''/'''       ),
               config.DATASET_INFO_FILENAME,
           ]       )
       __magic_name__     =      cached_path(UpperCamelCase_ ,						cache_dir=UpperCamelCase_       )
       self.assertTrue(os.path.exists(UpperCamelCase_       )       )





@pytest.mark.integration
def 	lowercase      (   __UpperCamelCase						) ->      Tuple:
 __magic_name__     =      tmp_path_factory.mktemp('''test_hf_gcp'''						) / '''test_wikipedia_simple'''
 __magic_name__     =      dataset_module_factory('''wikipedia'''      ,   cache_dir=__UpperCamelCase						)
 __magic_name__     =      import_main_class(dataset_module.module_path						)
 __magic_name__     =      builder_cls(
     cache_dir=__UpperCamelCase      ,   config_name='''20220301.frr'''      ,   hash=dataset_module.hash      ,   )
 # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
 __magic_name__     =      None
 builder_instance.download_and_prepare()
 __magic_name__     =      builder_instance.as_dataset()
 assert ds





@pytest.mark.integration
def 	lowercase      (   __UpperCamelCase						) ->      Tuple:
 __magic_name__     =      dataset_module_factory('''wikipedia'''      ,   cache_dir=__UpperCamelCase						)
 __magic_name__     =      import_main_class(dataset_module.module_path      ,   dataset=__UpperCamelCase						)
 __magic_name__     =      builder_cls(
     cache_dir=__UpperCamelCase      ,   config_name='''20220301.frr'''      ,   hash=dataset_module.hash      ,   )
 __magic_name__     =      builder_instance.as_streaming_dataset()
 assert ds
 assert isinstance(__UpperCamelCase      ,   __UpperCamelCase						)
 assert "train" in ds
 assert isinstance(ds['''train''']      ,   __UpperCamelCase						)
 assert next(iter(ds['''train''']						)						)

