





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  __A(						__UpperCAmelCase						,			unittest.TestCase ):
     __A	  =       LongformerTokenizer
     __A	  =       True
     __A	  =       LongformerTokenizerFast
     __A	  =       True

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            super().setUp()

            # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
            _UpperCamelCase              =						[
                '''l''',
                '''o''',
                '''w''',
                '''e''',
                '''r''',
                '''s''',
                '''t''',
                '''i''',
                '''d''',
                '''n''',
                '''\u0120''',
                '''\u0120l''',
                '''\u0120n''',
                '''\u0120lo''',
                '''\u0120low''',
                '''er''',
                '''\u0120lowest''',
                '''\u0120newer''',
                '''\u0120wider''',
                '''<unk>''',
            ]
            _UpperCamelCase              =						dict(zip(A,       range(len(A      )      )      )      )
            _UpperCamelCase              =						['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
            _UpperCamelCase              =						{'''unk_token''': '''<unk>'''}

            _UpperCamelCase              =						os.path.join(self.tmpdirname,       VOCAB_FILES_NAMES['''vocab_file''']      )
            _UpperCamelCase              =						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,       **A      ):





            """simple docstring"""

            kwargs.update(self.special_tokens_map      )
            return self.tokenizer_class.from_pretrained(self.tmpdirname,       **A      )

     def 	_UpperCamelCase     (      self,       **A      ):





            """simple docstring"""

            kwargs.update(self.special_tokens_map      )
            return self.rust_tokenizer_class.from_pretrained(self.tmpdirname,       **A      )

     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						'''lower newer'''
            _UpperCamelCase              =						'''lower newer'''
            return input_text, output_text

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						self.tokenizer_class(self.vocab_file,       self.merges_file,       **self.special_tokens_map      )
            _UpperCamelCase              =						'''lower newer'''
            _UpperCamelCase              =						['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
            _UpperCamelCase              =						tokenizer.tokenize(A      )  # , add_prefix_space=True)
            self.assertListEqual(A,       A      )

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

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						self.get_tokenizer()

            self.assertListEqual(tokenizer.encode('''Hello world!''',       add_special_tokens=A      ),       [0, 3_1414, 232, 328, 2]      )
            self.assertListEqual(
                tokenizer.encode('''Hello world! cécé herlolip 418''',       add_special_tokens=A      ),       [0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2],       )

     @slow
     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						self.tokenizer_class.from_pretrained('''allenai/longformer-base-4096'''      )

            _UpperCamelCase              =						tokenizer.encode('''sequence builders''',       add_special_tokens=A      )
            _UpperCamelCase              =						tokenizer.encode('''multi-sequence build''',       add_special_tokens=A      )

            _UpperCamelCase              =						tokenizer.encode(
                '''sequence builders''',       add_special_tokens=A,       add_prefix_space=A      )
            _UpperCamelCase              =						tokenizer.encode(
                '''sequence builders''',       '''multi-sequence build''',       add_special_tokens=A,       add_prefix_space=A      )

            _UpperCamelCase              =						tokenizer.build_inputs_with_special_tokens(A      )
            _UpperCamelCase              =						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      ):





            """simple docstring"""

            _UpperCamelCase              =						self.get_tokenizer()

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

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

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

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

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

            _UpperCamelCase              =						'''Encode <mask> sequence'''
            _UpperCamelCase              =						'''Encode <mask>sequence'''

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

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

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            pass

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

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

                          _UpperCamelCase              =						tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']      )
                          _UpperCamelCase              =						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, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]      )
                          self.assertSequenceEqual(tokens_r['''input_ids'''],       [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 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      ):





            """simple docstring"""

            for trim_offsets, add_prefix_space in itertools.product([True, False],       repeat=2      ):
                   _UpperCamelCase              =						self.rust_tokenizer_class.from_pretrained(
                       self.tmpdirname,       use_fast=A,       add_prefix_space=A,       trim_offsets=A      )

                   _UpperCamelCase              =						json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()      )
                   _UpperCamelCase              =						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      ):





            """simple docstring"""

            for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                   with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                          _UpperCamelCase              =						'''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
                          _UpperCamelCase              =						F'''{text_of_1_token} {text_of_1_token}'''

                          _UpperCamelCase              =						self.rust_tokenizer_class.from_pretrained(
                              A,       use_fast=A,       add_prefix_space=A,       trim_offsets=A      )
                          _UpperCamelCase              =						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      )),       )

                          _UpperCamelCase              =						self.rust_tokenizer_class.from_pretrained(
                              A,       use_fast=A,       add_prefix_space=A,       trim_offsets=A      )
                          _UpperCamelCase              =						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      )),       )

                          _UpperCamelCase              =						self.rust_tokenizer_class.from_pretrained(
                              A,       use_fast=A,       add_prefix_space=A,       trim_offsets=A      )
                          _UpperCamelCase              =						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      )),       )

                          _UpperCamelCase              =						self.rust_tokenizer_class.from_pretrained(
                              A,       use_fast=A,       add_prefix_space=A,       trim_offsets=A      )
                          _UpperCamelCase              =						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      )),       )

                          _UpperCamelCase              =						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)),
                          # )

                          _UpperCamelCase              =						self.rust_tokenizer_class.from_pretrained(
                              A,       use_fast=A,       add_prefix_space=A,       trim_offsets=A      )
                          _UpperCamelCase              =						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      )),       )

                          _UpperCamelCase              =						self.rust_tokenizer_class.from_pretrained(
                              A,       use_fast=A,       add_prefix_space=A,       trim_offsets=A      )
                          _UpperCamelCase              =						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      )),       )

                          _UpperCamelCase              =						self.rust_tokenizer_class.from_pretrained(
                              A,       use_fast=A,       add_prefix_space=A,       trim_offsets=A      )
                          _UpperCamelCase              =						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     SCREAMING_SNAKE_CASE			(      lowerCAmelCase = 1_000					):
       _UpperCamelCase              =						3
       _UpperCamelCase              =						0
       while a < n:
              if a % 3 == 0 or a % 5 == 0:
                     result += a
              elif a % 15 == 0:
                     result -= a
              a += 1
       return result


if __name__ == "__main__":
       print(F'''{solution() = }''')






