





import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
    from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCamelCase	:					Tuple			  =					get_tests_dir("""fixtures/test_sentencepiece.model""")

__lowerCamelCase	:					Tuple			  =					{"""target_lang""": """fi""", """source_lang""": """en"""}
__lowerCamelCase	:					Optional[Any]			  =					""">>zh<<"""
__lowerCamelCase	:					List[str]			  =					"""Helsinki-NLP/"""

if is_torch_available():
    __lowerCamelCase	:					Optional[Any]			  =					"""pt"""
elif is_tf_available():
    __lowerCamelCase	:					Any			  =					"""tf"""
else:
    __lowerCamelCase	:					Any			  =					"""jax"""



@require_sentencepiece
class  A__       (	__snake_case	,       unittest.TestCase      ):
      _UpperCAmelCase     :Optional[Any]						   =       MarianTokenizer
      _UpperCAmelCase     :List[Any]						   =       False
      _UpperCAmelCase     :str						   =       True





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       super().setUp()
       UpperCamelCase     : List[str]	     =       ["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
       UpperCamelCase     : Optional[Any]	     =       dict(zip(A_	,							range(len(A_       )       )       )       )
       UpperCamelCase     : Any	     =       Path(self.tmpdirname       )
       save_json(A_	,							save_dir / VOCAB_FILES_NAMES["vocab"]       )
       save_json(A_	,							save_dir / VOCAB_FILES_NAMES["tokenizer_config_file"]       )
       if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
        copyfile(A_	,							save_dir / VOCAB_FILES_NAMES["source_spm"]       )
        copyfile(A_	,							save_dir / VOCAB_FILES_NAMES["target_spm"]       )

       UpperCamelCase     : Tuple	     =       MarianTokenizer.from_pretrained(self.tmpdirname       )
       tokenizer.save_pretrained(self.tmpdirname       )





      def 	__UpperCamelCase(			self	,							**A_       ):
       '''simple docstring'''




       return MarianTokenizer.from_pretrained(self.tmpdirname	,							**A_       )





      def 	__UpperCamelCase(			self	,							A_       ):
       '''simple docstring'''




       return (
           "This is a test",
           "This is a test",
       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : int	     =       "</s>"
       UpperCamelCase     : int	     =       0

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(A_       )	,							A_       )
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(A_       )	,							A_       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Tuple	     =       list(self.get_tokenizer().get_vocab().keys()       )

       self.assertEqual(vocab_keys[0]	,							"</s>"       )
       self.assertEqual(vocab_keys[1]	,							"<unk>"       )
       self.assertEqual(vocab_keys[-1]	,							"<pad>"       )
       self.assertEqual(len(A_       )	,							9       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       self.assertEqual(self.get_tokenizer().vocab_size	,							9       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : int	     =       MarianTokenizer.from_pretrained(F"""{ORG_NAME}opus-mt-en-de"""       )
       UpperCamelCase     : Optional[int]	     =       en_de_tokenizer(["I am a small frog"]	,							return_tensors=A_       )
       self.assertIsInstance(A_	,							A_       )
       UpperCamelCase     : Tuple	     =       [38, 121, 14, 697, 3_8848, 0]
       self.assertListEqual(A_	,							batch.input_ids[0]       )

       UpperCamelCase     : Dict	     =       tempfile.mkdtemp()
       en_de_tokenizer.save_pretrained(A_       )
       UpperCamelCase     : Union[str, Any]	     =       [x.name for x in Path(A_       ).glob("*"       )]
       self.assertIn("source.spm"	,							A_       )
       MarianTokenizer.from_pretrained(A_       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Tuple	     =       self.get_tokenizer()

       UpperCamelCase     : Any	     =       tok(
           ["I am a small frog" * 1000, "I am a small frog"]	,							padding=A_	,							truncation=A_	,							return_tensors=A_       )
       self.assertIsInstance(A_	,							A_       )
       self.assertEqual(batch.input_ids.shape	,							(2, 512)       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Any	     =       self.get_tokenizer()
       UpperCamelCase     : Any	     =       tok(["I am a tiny frog", "I am a small frog"]	,							padding=A_	,							return_tensors=A_       )
       self.assertIsInstance(A_	,							A_       )
       self.assertEqual(batch_smaller.input_ids.shape	,							(2, 10)       )





      @slow
      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : List[Any]	     =       {"input_ids": [[4_3495, 462, 20, 4_2164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 3_8999, 6, 8, 464, 132, 1703, 492, 13, 4669, 3_7867, 13, 7525, 27, 1593, 988, 13, 3_3972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 1_2338, 2, 1_3958, 387, 2, 3629, 6953, 188, 2900, 2, 1_3958, 8011, 1_1501, 23, 8460, 4073, 3_4009, 20, 435, 1_1439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 3_7867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 2_6453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 1_0767, 6, 316, 304, 4239, 3, 0], [148, 1_5722, 19, 1839, 12, 1350, 13, 2_2327, 5082, 5418, 4_7567, 3_5938, 59, 318, 1_9552, 108, 2183, 54, 1_4976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 1_9088, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100], [36, 6395, 1_2570, 3_9147, 1_1597, 6, 266, 4, 4_5405, 7296, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=A_	,							model_name="Helsinki-NLP/opus-mt-en-de"	,							revision="1a8c2263da11e68e50938f97e10cd57820bd504c"	,							decode_kwargs={"use_source_tokenizer": True}	,							)





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Tuple	     =       MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs"       )

       UpperCamelCase     : Tuple	     =       "Tämä on testi"
       UpperCamelCase     : Union[str, Any]	     =       "This is a test"

       UpperCamelCase     : int	     =       [76, 7, 2047, 2]
       UpperCamelCase     : Optional[Any]	     =       [69, 12, 11, 940, 2]

       UpperCamelCase     : Dict	     =       tokenizer(A_       ).input_ids
       self.assertListEqual(A_	,							A_       )

       UpperCamelCase     : Any	     =       tokenizer(text_target=A_       ).input_ids
       self.assertListEqual(A_	,							A_       )

       UpperCamelCase     : List[Any]	     =       tokenizer.decode(A_	,							skip_special_tokens=A_       )
       self.assertEqual(A_	,							A_       )







def 		A_    (					_lowerCAmelCase					)						->			int:
 if n == 1 or not isinstance(_lowerCAmelCase							,       _lowerCAmelCase					):
  return 0
 elif n == 2:
  return 1
 else:
  UpperCamelCase     : Optional[Any]	     =       [0, 1]
  for i in range(2							,       n + 1					):
   sequence.append(sequence[i - 1] + sequence[i - 2]					)

  return sequence[n]



def 		A_    (					_lowerCAmelCase					)						->			int:
 UpperCamelCase     : Any	     =       0
 UpperCamelCase     : List[Any]	     =       2

 while digits < n:
  index += 1
  UpperCamelCase     : Union[str, Any]	     =       len(str(fibonacci(_lowerCAmelCase					)					)					)

 return index



def 		A_    (					_lowerCAmelCase = 1000					)						->			int:
 return fibonacci_digits_index(_lowerCAmelCase					)


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