

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    _lowercase				(					__lowerCamelCase,unittest.TestCase			):
   _lowercase     :       str  					=    LongformerTokenizer
   _lowercase     :       Optional[Any]  					=    True
   _lowercase     :       List[Any]  					=    LongformerTokenizerFast
   _lowercase     :       Dict  					=    True

   def     UpperCamelCase					(				self	:    str       ) ->			Dict:
         """simple docstring"""





         super().setUp()

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

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

   def     UpperCamelCase					(				self	:    Dict			,						**lowerCamelCase__	:    Any       ) ->			Optional[int]:
         """simple docstring"""





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

   def     UpperCamelCase					(				self	:    Tuple			,						**lowerCamelCase__	:    str       ) ->			Dict:
         """simple docstring"""





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

   def     UpperCamelCase					(				self	:    Optional[Any]			,						lowerCamelCase__	:    int       ) ->			Optional[Any]:
         """simple docstring"""





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

   def     UpperCamelCase					(				self	:    Optional[int]       ) ->			Optional[int]:
         """simple docstring"""





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

         A_							       =		tokens + [tokenizer.unk_token]
         A_							       =		[0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase__       )			,						lowerCamelCase__       )

   def     UpperCamelCase					(				self	:    Dict       ) ->			Dict:
         """simple docstring"""





         A_							       =		self.get_tokenizer()

         self.assertListEqual(tokenizer.encode('''Hello world!'''			,						add_special_tokens=lowerCamelCase__       )			,						[0, 3_1_4_1_4, 2_3_2, 3_2_8, 2]       )
         self.assertListEqual(
             tokenizer.encode('''Hello world! cécé herlolip 418'''			,						add_special_tokens=lowerCamelCase__       )			,						[0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]			,						)

   @slow
   def     UpperCamelCase					(				self	:    Optional[int]       ) ->			Optional[Any]:
         """simple docstring"""





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

         A_							       =		tokenizer.encode('''sequence builders'''			,						add_special_tokens=lowerCamelCase__       )
         A_							       =		tokenizer.encode('''multi-sequence build'''			,						add_special_tokens=lowerCamelCase__       )

         A_							       =		tokenizer.encode(
             '''sequence builders'''			,						add_special_tokens=lowerCamelCase__			,						add_prefix_space=lowerCamelCase__       )
         A_							       =		tokenizer.encode(
             '''sequence builders'''			,						'''multi-sequence build'''			,						add_special_tokens=lowerCamelCase__			,						add_prefix_space=lowerCamelCase__       )

         A_							       =		tokenizer.build_inputs_with_special_tokens(lowerCamelCase__       )
         A_							       =		tokenizer.build_inputs_with_special_tokens(lowerCamelCase__			,						lowerCamelCase__       )

         assert encoded_sentence == encoded_text_from_decode
         assert encoded_pair == encoded_pair_from_decode

   def     UpperCamelCase					(				self	:    Optional[Any]       ) ->			Dict:
         """simple docstring"""





         A_							       =		self.get_tokenizer()

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

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

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

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

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

         A_							       =		'''Encode <mask> sequence'''
         A_							       =		'''Encode <mask>sequence'''

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

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

   def     UpperCamelCase					(				self	:    Tuple       ) ->			Any:
         """simple docstring"""





         pass

   def     UpperCamelCase					(				self	:    Tuple       ) ->			Optional[Any]:
         """simple docstring"""





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

                     # 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''']       )			,						)

                     A_							       =		tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']       )
                     A_							       =		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_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]       )
                     self.assertSequenceEqual(tokens_r['''input_ids''']			,						[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]       )

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

   def     UpperCamelCase					(				self	:    Optional[int]       ) ->			int:
         """simple docstring"""





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

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

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

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





   def     UpperCamelCase					(				self	:    Dict       ) ->			str:
         """simple docstring"""





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

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

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

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

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

                     A_							       =		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)),
                     # )

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

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

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








def 							_lowerCamelCase   (			SCREAMING_SNAKE_CASE = 100   ):
      '''simple docstring'''







      A_							       =		0
      A_							       =		0
      for i in range(1		,				n + 1   ):
            sum_of_squares += i**2
            sum_of_ints += i
      return sum_of_ints**2 - sum_of_squares


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





