





'''simple docstring'''

import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a   	=    "▁"

a   	=    get_tests_dir("fixtures/test_sentencepiece.model")







@require_sentencepiece
class __a			( _snake_case, unittest.TestCase      ):
   __UpperCamelCase :			str						   =						BertGenerationTokenizer
   __UpperCamelCase :			Tuple						   =						False
   __UpperCamelCase :			int						   =						True





   def   UpperCAmelCase__  (       self					:      Optional[Any]     ):

      '''simple docstring'''

      super().setUp()

      __SCREAMING_SNAKE_CASE   				=							BertGenerationTokenizer(lowerCamelCase					,keep_accents=lowerCamelCase     )
      tokenizer.save_pretrained(self.tmpdirname     )





   def   UpperCAmelCase__  (       self					:      List[Any]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							"""<s>"""
      __SCREAMING_SNAKE_CASE   				=							1

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





   def   UpperCAmelCase__  (       self					:      Tuple     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							list(self.get_tokenizer().get_vocab().keys()     )

      self.assertEqual(vocab_keys[0]					,"""<unk>"""     )
      self.assertEqual(vocab_keys[1]					,"""<s>"""     )
      self.assertEqual(vocab_keys[-1]					,"""<pad>"""     )
      self.assertEqual(len(lowerCamelCase     )					,1002     )





   def   UpperCAmelCase__  (       self					:      Optional[int]     ):

      '''simple docstring'''

      self.assertEqual(self.get_tokenizer().vocab_size					,1000     )





   def   UpperCAmelCase__  (       self					:      Dict     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							BertGenerationTokenizer(lowerCamelCase					,keep_accents=lowerCamelCase     )

      __SCREAMING_SNAKE_CASE   				=							tokenizer.tokenize("""This is a test"""     )
      self.assertListEqual(lowerCamelCase					,["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]     )

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(lowerCamelCase     )					,[285, 46, 10, 170, 382]					,)

      __SCREAMING_SNAKE_CASE   				=							tokenizer.tokenize("""I was born in 92000, and this is falsé."""     )
      self.assertListEqual(
          lowerCamelCase					,[
              SPIECE_UNDERLINE + """I""",
              SPIECE_UNDERLINE + """was""",
              SPIECE_UNDERLINE + """b""",
              """or""",
              """n""",
              SPIECE_UNDERLINE + """in""",
              SPIECE_UNDERLINE + """""",
              """9""",
              """2""",
              """0""",
              """0""",
              """0""",
              """,""",
              SPIECE_UNDERLINE + """and""",
              SPIECE_UNDERLINE + """this""",
              SPIECE_UNDERLINE + """is""",
              SPIECE_UNDERLINE + """f""",
              """al""",
              """s""",
              """é""",
              """.""",
          ]					,)
      __SCREAMING_SNAKE_CASE   				=							tokenizer.convert_tokens_to_ids(lowerCamelCase     )
      self.assertListEqual(
          lowerCamelCase					,[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]					,)

      __SCREAMING_SNAKE_CASE   				=							tokenizer.convert_ids_to_tokens(lowerCamelCase     )
      self.assertListEqual(
          lowerCamelCase					,[
              SPIECE_UNDERLINE + """I""",
              SPIECE_UNDERLINE + """was""",
              SPIECE_UNDERLINE + """b""",
              """or""",
              """n""",
              SPIECE_UNDERLINE + """in""",
              SPIECE_UNDERLINE + """""",
              """<unk>""",
              """2""",
              """0""",
              """0""",
              """0""",
              """,""",
              SPIECE_UNDERLINE + """and""",
              SPIECE_UNDERLINE + """this""",
              SPIECE_UNDERLINE + """is""",
              SPIECE_UNDERLINE + """f""",
              """al""",
              """s""",
              """<unk>""",
              """.""",
          ]					,)





   @cached_property
   def   UpperCAmelCase__  (       self					:      Optional[int]     ):

      '''simple docstring'''

      return BertGenerationTokenizer.from_pretrained("""google/bert_for_seq_generation_L-24_bbc_encoder"""     )





   @slow
   def   UpperCAmelCase__  (       self					:      Dict     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							"""Hello World!"""
      __SCREAMING_SNAKE_CASE   				=							[1_8536, 2260, 101]

      self.assertListEqual(lowerCamelCase					,self.big_tokenizer.encode(lowerCamelCase     )     )





   @slow
   def   UpperCAmelCase__  (       self					:      List[str]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							(
          """This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"""
          """ add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"""
      )
      __SCREAMING_SNAKE_CASE   				=							[
          871,
          419,
          358,
          946,
          991,
          2521,
          452,
          358,
          1357,
          387,
          7751,
          3536,
          112,
          985,
          456,
          126,
          865,
          938,
          5400,
          5734,
          458,
          1368,
          467,
          786,
          2462,
          5246,
          1159,
          633,
          865,
          4519,
          457,
          582,
          852,
          2557,
          427,
          916,
          508,
          405,
          3_4324,
          497,
          391,
          408,
          1_1342,
          1244,
          385,
          100,
          938,
          985,
          456,
          574,
          362,
          1_2597,
          3200,
          3129,
          1172,
      ]

      self.assertListEqual(lowerCamelCase					,self.big_tokenizer.encode(lowerCamelCase     )     )





   @require_torch
   @slow
   def   UpperCAmelCase__  (       self					:      Optional[Any]     ):

      '''simple docstring'''

      import torch

      from transformers import BertGenerationConfig, BertGenerationEncoder

      # Build sequence
      __SCREAMING_SNAKE_CASE   				=							list(self.big_tokenizer.get_vocab().keys()     )[:10]
      __SCREAMING_SNAKE_CASE   				=							""" """.join(lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							self.big_tokenizer.encode_plus(lowerCamelCase					,return_tensors="""pt"""					,return_token_type_ids=lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							self.big_tokenizer.batch_encode_plus(
          [sequence + """ """ + sequence]					,return_tensors="""pt"""					,return_token_type_ids=lowerCamelCase     )

      __SCREAMING_SNAKE_CASE   				=							BertGenerationConfig()
      __SCREAMING_SNAKE_CASE   				=							BertGenerationEncoder(lowerCamelCase     )

      assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

      with torch.no_grad():
         model(**lowerCamelCase     )
         model(**lowerCamelCase     )





   @slow
   def   UpperCAmelCase__  (       self					:      List[str]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							{"""input_ids""": [[3_9286, 458, 3_6335, 2001, 456, 1_3073, 1_3266, 455, 113, 7746, 1741, 1_1157, 391, 1_3073, 1_3266, 455, 113, 3967, 3_5412, 113, 4936, 109, 3870, 2377, 113, 3_0084, 4_5720, 458, 134, 1_7496, 112, 503, 1_1672, 113, 118, 112, 5665, 1_3347, 3_8687, 112, 1496, 3_1389, 112, 3268, 4_7264, 134, 962, 112, 1_6377, 8035, 2_3130, 430, 1_2169, 1_5518, 2_8592, 458, 146, 4_1697, 109, 391, 1_2169, 1_5518, 1_6689, 458, 146, 4_1358, 109, 452, 726, 4034, 111, 763, 3_5412, 5082, 388, 1903, 111, 9051, 391, 2870, 4_8918, 1900, 1123, 550, 998, 112, 9586, 1_5985, 455, 391, 410, 2_2955, 3_7636, 114], [448, 1_7496, 419, 3663, 385, 763, 113, 2_7533, 2870, 3283, 1_3043, 1639, 2_4713, 523, 656, 2_4013, 1_8550, 2521, 517, 2_7014, 2_1244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 1_1786, 114, 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], [484, 2169, 7687, 2_1932, 1_8146, 726, 363, 1_7032, 3391, 114, 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]], """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, 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, 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=lowerCamelCase					,model_name="""google/bert_for_seq_generation_L-24_bbc_encoder"""					,revision="""c817d1fd1be2ffa69431227a1fe320544943d4db"""					,)








def    __lowerCamelCase      (					UpperCamelCase__ = 1000 ):







							'''simple docstring'''






							snake_case_     							=       2**power
							snake_case_     							=       0
							while n:
														snake_case_							,       snake_case_     							=       r + n % 10, n // 10
							return r


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




