


'''simple docstring'''





import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class lowerCAmelCase_		(				lowerCamelCase__      ,		unittest.TestCase ):

 '''simple docstring'''

 __snake_case				=						LongformerTokenizer
 __snake_case				=						True
 __snake_case				=						LongformerTokenizerFast
 __snake_case				=						True



 def 		UpperCamelCase__  (			self      ):
       super().setUp()

       # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
       snake_case_ =   [
           """l""",
           """o""",
           """w""",
           """e""",
           """r""",
           """s""",
           """t""",
           """i""",
           """d""",
           """n""",
           """\u0120""",
           """\u0120l""",
           """\u0120n""",
           """\u0120lo""",
           """\u0120low""",
           """er""",
           """\u0120lowest""",
           """\u0120newer""",
           """\u0120wider""",
           """<unk>""",
       ]
       snake_case_ =   dict(zip(A__	,   range(len(A__      )      )      )      )
       snake_case_ =   ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
       snake_case_ =   {"""unk_token""": """<unk>"""}

       snake_case_ =   os.path.join(self.tmpdirname	,   VOCAB_FILES_NAMES['''vocab_file''']      )
       snake_case_ =   os.path.join(self.tmpdirname	,   VOCAB_FILES_NAMES['''merges_file''']      )
       with open(self.vocab_file	,   '''w'''	,   encoding='''utf-8'''      ) as fp:
             fp.write(json.dumps(A__      ) + '''\n'''      )
       with open(self.merges_file	,   '''w'''	,   encoding='''utf-8'''      ) as fp:
             fp.write('''\n'''.join(A__      )      )



 def 		UpperCamelCase__  (			self	,   **_UpperCAmelCase      ):
       kwargs.update(self.special_tokens_map      )
       return self.tokenizer_class.from_pretrained(self.tmpdirname	,   **A__      )



 def 		UpperCamelCase__  (			self	,   **_UpperCAmelCase      ):
       kwargs.update(self.special_tokens_map      )
       return self.rust_tokenizer_class.from_pretrained(self.tmpdirname	,   **A__      )



 def 		UpperCamelCase__  (			self	,   _UpperCAmelCase      ):
       snake_case_ =   """lower newer"""
       snake_case_ =   """lower newer"""
       return input_text, output_text



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.tokenizer_class(self.vocab_file	,   self.merges_file	,   **self.special_tokens_map      )
       snake_case_ =   """lower newer"""
       snake_case_ =   ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
       snake_case_ =   tokenizer.tokenize(A__      )  # , add_prefix_space=True)
       self.assertListEqual(A__	,   A__      )

       snake_case_ =   tokens + [tokenizer.unk_token]
       snake_case_ =   [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(A__      )	,   A__      )



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.get_tokenizer()

       self.assertListEqual(tokenizer.encode('''Hello world!'''	,   add_special_tokens=A__      )	,   [0, 3_14_14, 2_32, 3_28, 2]      )
       self.assertListEqual(
           tokenizer.encode('''Hello world! cécé herlolip 418'''	,   add_special_tokens=A__      )	,   [0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]	,   )



 @slow
 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.tokenizer_class.from_pretrained('''allenai/longformer-base-4096'''      )

       snake_case_ =   tokenizer.encode('''sequence builders'''	,   add_special_tokens=A__      )
       snake_case_ =   tokenizer.encode('''multi-sequence build'''	,   add_special_tokens=A__      )

       snake_case_ =   tokenizer.encode(
           '''sequence builders'''	,   add_special_tokens=A__	,   add_prefix_space=A__      )
       snake_case_ =   tokenizer.encode(
           '''sequence builders'''	,   '''multi-sequence build'''	,   add_special_tokens=A__	,   add_prefix_space=A__      )

       snake_case_ =   tokenizer.build_inputs_with_special_tokens(A__      )
       snake_case_ =   tokenizer.build_inputs_with_special_tokens(A__	,   A__      )

       assert encoded_sentence == encoded_text_from_decode
       assert encoded_pair == encoded_pair_from_decode



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.get_tokenizer()

       snake_case_ =   """Encode this sequence."""
       snake_case_ =   tokenizer.byte_encoder[""" """.encode('''utf-8'''      )[0]]

       # Testing encoder arguments
       snake_case_ =   tokenizer.encode(A__	,   add_special_tokens=A__	,   add_prefix_space=A__      )
       snake_case_ =   tokenizer.convert_ids_to_tokens(encoded[0]      )[0]
       self.assertNotEqual(A__	,   A__      )

       snake_case_ =   tokenizer.encode(A__	,   add_special_tokens=A__	,   add_prefix_space=A__      )
       snake_case_ =   tokenizer.convert_ids_to_tokens(encoded[0]      )[0]
       self.assertEqual(A__	,   A__      )

       tokenizer.add_special_tokens({'''bos_token''': '''<s>'''}      )
       snake_case_ =   tokenizer.encode(A__	,   add_special_tokens=A__      )
       snake_case_ =   tokenizer.convert_ids_to_tokens(encoded[1]      )[0]
       self.assertNotEqual(A__	,   A__      )

       # Testing spaces after special tokens
       snake_case_ =   """<mask>"""
       tokenizer.add_special_tokens(
           {'''mask_token''': AddedToken(A__	,   lstrip=A__	,   rstrip=A__      )}      )  # mask token has a left space
       snake_case_ =   tokenizer.convert_tokens_to_ids(A__      )

       snake_case_ =   """Encode <mask> sequence"""
       snake_case_ =   """Encode <mask>sequence"""

       snake_case_ =   tokenizer.encode(A__      )
       snake_case_ =   encoded.index(A__      )
       snake_case_ =   tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]      )[0]
       self.assertEqual(A__	,   A__      )

       snake_case_ =   tokenizer.encode(A__      )
       snake_case_ =   encoded.index(A__      )
       snake_case_ =   tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]      )[0]
       self.assertNotEqual(A__	,   A__      )



 def 		UpperCamelCase__  (			self      ):
       pass



 def 		UpperCamelCase__  (			self      ):
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                   snake_case_ =   self.rust_tokenizer_class.from_pretrained(A__	,   **A__      )
                   snake_case_ =   self.tokenizer_class.from_pretrained(A__	,   **A__      )
                   snake_case_ =   """A, <mask> AllenNLP sentence."""
                   snake_case_ =   tokenizer_r.encode_plus(A__	,   add_special_tokens=A__	,   return_token_type_ids=A__      )
                   snake_case_ =   tokenizer_p.encode_plus(A__	,   add_special_tokens=A__	,   return_token_type_ids=A__      )

                   # token_type_ids should put 0 everywhere
                   self.assertEqual(sum(tokens_r['''token_type_ids''']      )	,   sum(tokens_p['''token_type_ids''']      )      )

                   # attention_mask should put 1 everywhere, so sum over length should be 1
                   self.assertEqual(
                       sum(tokens_r['''attention_mask''']      ) / len(tokens_r['''attention_mask''']      )	,   sum(tokens_p['''attention_mask''']      ) / len(tokens_p['''attention_mask''']      )	,   )

                   snake_case_ =   tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']      )
                   snake_case_ =   tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']      )

                   # Rust correctly handles the space before the mask while python doesnt
                   self.assertSequenceEqual(tokens_p['''input_ids''']	,   [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]      )
                   self.assertSequenceEqual(tokens_r['''input_ids''']	,   [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]      )

                   self.assertSequenceEqual(
                       A__	,   ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']      )
                   self.assertSequenceEqual(
                       A__	,   ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']      )



 def 		UpperCamelCase__  (			self      ):
       for trim_offsets, add_prefix_space in itertools.product([True, False]	,   repeat=2      ):
             snake_case_ =   self.rust_tokenizer_class.from_pretrained(
                 self.tmpdirname	,   use_fast=A__	,   add_prefix_space=A__	,   trim_offsets=A__      )

             snake_case_ =   json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()      )
             snake_case_ =   json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()      )

             self.assertEqual(pre_tokenizer_state['''add_prefix_space''']	,   A__      )

             self.assertEqual(post_processor_state['''add_prefix_space''']	,   A__      )
             self.assertEqual(post_processor_state['''trim_offsets''']	,   A__      )





 def 		UpperCamelCase__  (			self      ):
       # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
       # `trim_offsets`
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                   snake_case_ =   """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
                   snake_case_ =   F'''{text_of_1_token} {text_of_1_token}'''

                   snake_case_ =   self.rust_tokenizer_class.from_pretrained(
                       A__	,   use_fast=A__	,   add_prefix_space=A__	,   trim_offsets=A__      )
                   snake_case_ =   tokenizer_r(A__	,   return_offsets_mapping=A__	,   add_special_tokens=A__      )
                   self.assertEqual(encoding.offset_mapping[0]	,   (0, len(A__      ))      )
                   self.assertEqual(
                       encoding.offset_mapping[1]	,   (len(A__      ) + 1, len(A__      ) + 1 + len(A__      ))	,   )

                   snake_case_ =   self.rust_tokenizer_class.from_pretrained(
                       A__	,   use_fast=A__	,   add_prefix_space=A__	,   trim_offsets=A__      )
                   snake_case_ =   tokenizer_r(A__	,   return_offsets_mapping=A__	,   add_special_tokens=A__      )
                   self.assertEqual(encoding.offset_mapping[0]	,   (0, len(A__      ))      )
                   self.assertEqual(
                       encoding.offset_mapping[1]	,   (len(A__      ) + 1, len(A__      ) + 1 + len(A__      ))	,   )

                   snake_case_ =   self.rust_tokenizer_class.from_pretrained(
                       A__	,   use_fast=A__	,   add_prefix_space=A__	,   trim_offsets=A__      )
                   snake_case_ =   tokenizer_r(A__	,   return_offsets_mapping=A__	,   add_special_tokens=A__      )
                   self.assertEqual(encoding.offset_mapping[0]	,   (0, len(A__      ))      )
                   self.assertEqual(
                       encoding.offset_mapping[1]	,   (len(A__      ), len(A__      ) + 1 + len(A__      ))	,   )

                   snake_case_ =   self.rust_tokenizer_class.from_pretrained(
                       A__	,   use_fast=A__	,   add_prefix_space=A__	,   trim_offsets=A__      )
                   snake_case_ =   tokenizer_r(A__	,   return_offsets_mapping=A__	,   add_special_tokens=A__      )
                   self.assertEqual(encoding.offset_mapping[0]	,   (0, len(A__      ))      )
                   self.assertEqual(
                       encoding.offset_mapping[1]	,   (len(A__      ), len(A__      ) + 1 + len(A__      ))	,   )

                   snake_case_ =   F''' {text}'''

                   # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                   #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
                   # )
                   # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
                   # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
                   # self.assertEqual(
                   #     encoding.offset_mapping[1],
                   #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
                   # )

                   snake_case_ =   self.rust_tokenizer_class.from_pretrained(
                       A__	,   use_fast=A__	,   add_prefix_space=A__	,   trim_offsets=A__      )
                   snake_case_ =   tokenizer_r(A__	,   return_offsets_mapping=A__	,   add_special_tokens=A__      )
                   self.assertEqual(encoding.offset_mapping[0]	,   (1, 1 + len(A__      ))      )
                   self.assertEqual(
                       encoding.offset_mapping[1]	,   (1 + len(A__      ) + 1, 1 + len(A__      ) + 1 + len(A__      ))	,   )

                   snake_case_ =   self.rust_tokenizer_class.from_pretrained(
                       A__	,   use_fast=A__	,   add_prefix_space=A__	,   trim_offsets=A__      )
                   snake_case_ =   tokenizer_r(A__	,   return_offsets_mapping=A__	,   add_special_tokens=A__      )
                   self.assertEqual(encoding.offset_mapping[0]	,   (0, 1 + len(A__      ))      )
                   self.assertEqual(
                       encoding.offset_mapping[1]	,   (1 + len(A__      ), 1 + len(A__      ) + 1 + len(A__      ))	,   )

                   snake_case_ =   self.rust_tokenizer_class.from_pretrained(
                       A__	,   use_fast=A__	,   add_prefix_space=A__	,   trim_offsets=A__      )
                   snake_case_ =   tokenizer_r(A__	,   return_offsets_mapping=A__	,   add_special_tokens=A__      )
                   self.assertEqual(encoding.offset_mapping[0]	,   (0, 1 + len(A__      ))      )
                   self.assertEqual(
                       encoding.offset_mapping[1]	,   (1 + len(A__      ), 1 + len(A__      ) + 1 + len(A__      ))	,   )



def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE = 3      ,      SCREAMING_SNAKE_CASE = 7      ,      SCREAMING_SNAKE_CASE = 100_0000      )->						int:




      """simple docstring"""

      snake_case_ =   0
      snake_case_ =   1

      for current_denominator in range(1      ,      limit + 1      ):
            snake_case_ =   current_denominator * numerator // denominator
            if current_denominator % denominator == 0:
                  current_numerator -= 1
            if current_numerator * max_denominator > current_denominator * max_numerator:
                  snake_case_ =   current_numerator
                  snake_case_ =   current_denominator
      return max_numerator


if __name__ == "__main__":
   print(solution(numerator=3, denominator=7, limit=100_0000))