





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			):
				SCREAMING_SNAKE_CASE__     :   Any		      =     LongformerTokenizer
				SCREAMING_SNAKE_CASE__     :   Optional[Any]		      =     True
				SCREAMING_SNAKE_CASE__     :   Optional[int]		      =     LongformerTokenizerFast
				SCREAMING_SNAKE_CASE__     :   Dict		      =     True






				def 			snake_case_    (  self					):

										"""simple docstring"""




										super().setUp()

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

										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   os.path.join(self.tmpdirname			, VOCAB_FILES_NAMES['''vocab_file''']					)
										__SCREAMING_SNAKE_CASE:				List[Any]           =   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 			snake_case_    (  self			, **_lowerCAmelCase					):

										"""simple docstring"""




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






				def 			snake_case_    (  self			, **_lowerCAmelCase					):

										"""simple docstring"""




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






				def 			snake_case_    (  self			, _lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				str           =   '''lower newer'''
										__SCREAMING_SNAKE_CASE:				Tuple           =   '''lower newer'''
										return input_text, output_text






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Dict           =   self.tokenizer_class(self.vocab_file			, self.merges_file			, **self.special_tokens_map					)
										__SCREAMING_SNAKE_CASE:				List[Any]           =   '''lower newer'''
										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   ['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
										__SCREAMING_SNAKE_CASE:				Tuple           =   tokenizer.tokenize(__a					)  # , add_prefix_space=True)
										self.assertListEqual(__a			, __a					)

										__SCREAMING_SNAKE_CASE:				Tuple           =   tokens + [tokenizer.unk_token]
										__SCREAMING_SNAKE_CASE:				List[str]           =   [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(__a					)			, __a					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Tuple           =   self.get_tokenizer()

										self.assertListEqual(tokenizer.encode('''Hello world!'''			, add_special_tokens=__a					)			, [0, 31414, 232, 328, 2]					)
										self.assertListEqual(
										    tokenizer.encode('''Hello world! cécé herlolip 418'''			, add_special_tokens=__a					)			, [0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]			, )






				@slow
				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Tuple           =   self.tokenizer_class.from_pretrained('''allenai/longformer-base-4096'''					)

										__SCREAMING_SNAKE_CASE:				int           =   tokenizer.encode('''sequence builders'''			, add_special_tokens=__a					)
										__SCREAMING_SNAKE_CASE:				str           =   tokenizer.encode('''multi-sequence build'''			, add_special_tokens=__a					)

										__SCREAMING_SNAKE_CASE:				Dict           =   tokenizer.encode(
										    '''sequence builders'''			, add_special_tokens=__a			, add_prefix_space=__a					)
										__SCREAMING_SNAKE_CASE:				Dict           =   tokenizer.encode(
										    '''sequence builders'''			, '''multi-sequence build'''			, add_special_tokens=__a			, add_prefix_space=__a					)

										__SCREAMING_SNAKE_CASE:				Optional[int]           =   tokenizer.build_inputs_with_special_tokens(__a					)
										__SCREAMING_SNAKE_CASE:				str           =   tokenizer.build_inputs_with_special_tokens(__a			, __a					)

										assert encoded_sentence == encoded_text_from_decode
										assert encoded_pair == encoded_pair_from_decode






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Any           =   self.get_tokenizer()

										__SCREAMING_SNAKE_CASE:				Optional[int]           =   '''Encode this sequence.'''
										__SCREAMING_SNAKE_CASE:				List[str]           =   tokenizer.byte_encoder[''' '''.encode('''utf-8'''					)[0]]

										# Testing encoder arguments
										__SCREAMING_SNAKE_CASE:				Dict           =   tokenizer.encode(__a			, add_special_tokens=__a			, add_prefix_space=__a					)
										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   tokenizer.convert_ids_to_tokens(encoded[0]					)[0]
										self.assertNotEqual(__a			, __a					)

										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   tokenizer.encode(__a			, add_special_tokens=__a			, add_prefix_space=__a					)
										__SCREAMING_SNAKE_CASE:				Tuple           =   tokenizer.convert_ids_to_tokens(encoded[0]					)[0]
										self.assertEqual(__a			, __a					)

										tokenizer.add_special_tokens({'''bos_token''': '''<s>'''}					)
										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   tokenizer.encode(__a			, add_special_tokens=__a					)
										__SCREAMING_SNAKE_CASE:				List[str]           =   tokenizer.convert_ids_to_tokens(encoded[1]					)[0]
										self.assertNotEqual(__a			, __a					)

										# Testing spaces after special tokens
										__SCREAMING_SNAKE_CASE:				Optional[int]           =   '''<mask>'''
										tokenizer.add_special_tokens(
										    {'''mask_token''': AddedToken(__a			, lstrip=__a			, rstrip=__a					)}					)  # mask token has a left space
										__SCREAMING_SNAKE_CASE:				Dict           =   tokenizer.convert_tokens_to_ids(__a					)

										__SCREAMING_SNAKE_CASE:				Optional[int]           =   '''Encode <mask> sequence'''
										__SCREAMING_SNAKE_CASE:				Tuple           =   '''Encode <mask>sequence'''

										__SCREAMING_SNAKE_CASE:				int           =   tokenizer.encode(__a					)
										__SCREAMING_SNAKE_CASE:				Tuple           =   encoded.index(__a					)
										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]					)[0]
										self.assertEqual(__a			, __a					)

										__SCREAMING_SNAKE_CASE:				List[str]           =   tokenizer.encode(__a					)
										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   encoded.index(__a					)
										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]					)[0]
										self.assertNotEqual(__a			, __a					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										pass






				def 			snake_case_    (  self					):

										"""simple docstring"""




										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""					):
																						__SCREAMING_SNAKE_CASE:				Dict           =   self.rust_tokenizer_class.from_pretrained(__a			, **__a					)
																						__SCREAMING_SNAKE_CASE:				Dict           =   self.tokenizer_class.from_pretrained(__a			, **__a					)
																						__SCREAMING_SNAKE_CASE:				Any           =   '''A, <mask> AllenNLP sentence.'''
																						__SCREAMING_SNAKE_CASE:				Optional[Any]           =   tokenizer_r.encode_plus(__a			, add_special_tokens=__a			, return_token_type_ids=__a					)
																						__SCREAMING_SNAKE_CASE:				Any           =   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''']					)			, )

																						__SCREAMING_SNAKE_CASE:				List[Any]           =   tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']					)
																						__SCREAMING_SNAKE_CASE:				Any           =   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, 50264, 3823, 487, 21992, 3645, 4, 2]					)
																						self.assertSequenceEqual(tokens_r['''input_ids''']			, [0, 250, 6, 50264, 3823, 487, 21992, 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 			snake_case_    (  self					):

										"""simple docstring"""




										for trim_offsets, add_prefix_space in itertools.product([True, False]			, repeat=2					):
																__SCREAMING_SNAKE_CASE:				Optional[Any]           =   self.rust_tokenizer_class.from_pretrained(
																    self.tmpdirname			, use_fast=__a			, add_prefix_space=__a			, trim_offsets=__a					)

																__SCREAMING_SNAKE_CASE:				List[str]           =   json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()					)
																__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   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 			snake_case_    (  self					):

										"""simple docstring"""




										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""					):
																						__SCREAMING_SNAKE_CASE:				Optional[int]           =   '''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
																						__SCREAMING_SNAKE_CASE:				Dict           =   f"""{text_of_1_token} {text_of_1_token}"""

																						__SCREAMING_SNAKE_CASE:				Dict           =   self.rust_tokenizer_class.from_pretrained(
																						    __a			, use_fast=__a			, add_prefix_space=__a			, trim_offsets=__a					)
																						__SCREAMING_SNAKE_CASE:				Tuple           =   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					))			, )

																						__SCREAMING_SNAKE_CASE:				Optional[int]           =   self.rust_tokenizer_class.from_pretrained(
																						    __a			, use_fast=__a			, add_prefix_space=__a			, trim_offsets=__a					)
																						__SCREAMING_SNAKE_CASE:				int           =   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					))			, )

																						__SCREAMING_SNAKE_CASE:				Any           =   self.rust_tokenizer_class.from_pretrained(
																						    __a			, use_fast=__a			, add_prefix_space=__a			, trim_offsets=__a					)
																						__SCREAMING_SNAKE_CASE:				Dict           =   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					))			, )

																						__SCREAMING_SNAKE_CASE:				List[Any]           =   self.rust_tokenizer_class.from_pretrained(
																						    __a			, use_fast=__a			, add_prefix_space=__a			, trim_offsets=__a					)
																						__SCREAMING_SNAKE_CASE:				Optional[Any]           =   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					))			, )

																						__SCREAMING_SNAKE_CASE:				List[Any]           =   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)),
																						# )

																						__SCREAMING_SNAKE_CASE:				List[Any]           =   self.rust_tokenizer_class.from_pretrained(
																						    __a			, use_fast=__a			, add_prefix_space=__a			, trim_offsets=__a					)
																						__SCREAMING_SNAKE_CASE:				str           =   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					))			, )

																						__SCREAMING_SNAKE_CASE:				Optional[Any]           =   self.rust_tokenizer_class.from_pretrained(
																						    __a			, use_fast=__a			, add_prefix_space=__a			, trim_offsets=__a					)
																						__SCREAMING_SNAKE_CASE:				Optional[Any]           =   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					))			, )

																						__SCREAMING_SNAKE_CASE:				Optional[Any]           =   self.rust_tokenizer_class.from_pretrained(
																						    __a			, use_fast=__a			, add_prefix_space=__a			, trim_offsets=__a					)
																						__SCREAMING_SNAKE_CASE:				Dict           =   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					))			, )








from __future__ import annotations

def      __lowercase(						UpperCAmelCase__			):


      """simple docstring"""



      lowerCamelCase             =		2
      lowerCamelCase             =		[]
      while i * i <= n:
            if n % i:
                  i += 1
            else:
                  n //= i
                  factors.append(UpperCAmelCase__			)
      if n > 1:
            factors.append(UpperCAmelCase__			)
      return factors


if __name__ == "__main__":
     import doctest

     doctest.testmod()