


'''simple docstring'''
import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 			lowerCamelCase_   (	__a     ,       unittest.TestCase      ):
      lowerCAmelCase__		     =     RobertaTokenizer
      lowerCAmelCase__		     =     RobertaTokenizerFast
      lowerCAmelCase__		     =     True
      lowerCAmelCase__		     =     {'cls_token': '<s>'}






      def lowercase_							(					self				:    int ):


          '''simple docstring'''


          super().setUp()

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

          UpperCAmelCase__			:		Dict													=				os.path.join(self.tmpdirname						,						VOCAB_FILES_NAMES['''vocab_file'''] )
          UpperCAmelCase__			:		str													=				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 lowercase_							(					self				:    Optional[int]						,						**_A				:    Optional[int] ):


          '''simple docstring'''


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






      def lowercase_							(					self				:    List[Any]						,						**_A				:    List[Any] ):


          '''simple docstring'''


          kwargs.update(self.special_tokens_map )
          return RobertaTokenizerFast.from_pretrained(self.tmpdirname						,						**_A )






      def lowercase_							(					self				:    str						,						_A				:    Optional[int] ):


          '''simple docstring'''


          UpperCAmelCase__			:		int													=				'''lower newer'''
          UpperCAmelCase__			:		Tuple													=				'''lower newer'''
          return input_text, output_text






      def lowercase_							(					self				:    List[Any] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Tuple													=				self.tokenizer_class(self.vocab_file						,						self.merges_file						,						**self.special_tokens_map )
          UpperCAmelCase__			:		int													=				'''lower newer'''
          UpperCAmelCase__			:		List[str]													=				['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
          UpperCAmelCase__			:		int													=				tokenizer.tokenize(_A )  # , add_prefix_space=True)
          self.assertListEqual(_A						,						_A )

          UpperCAmelCase__			:		List[Any]													=				tokens + [tokenizer.unk_token]
          UpperCAmelCase__			:		int													=				[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_A )						,						_A )






      def lowercase_							(					self				:    Tuple ):


          '''simple docstring'''


          UpperCAmelCase__			:		Optional[Any]													=				self.get_tokenizer()

          self.assertListEqual(tokenizer.encode('''Hello world!'''						,						add_special_tokens=_A )						,						[0, 31_414, 232, 328, 2] )
          self.assertListEqual(
              tokenizer.encode('''Hello world! cécé herlolip 418'''						,						add_special_tokens=_A )						,						[0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]						,						)






      @slow
      def lowercase_							(					self				:    List[Any] ):


          '''simple docstring'''


          UpperCAmelCase__			:		List[Any]													=				self.tokenizer_class.from_pretrained('''roberta-base''' )

          UpperCAmelCase__			:		Tuple													=				tokenizer.encode('''sequence builders'''						,						add_special_tokens=_A )
          UpperCAmelCase__			:		int													=				tokenizer.encode('''multi-sequence build'''						,						add_special_tokens=_A )

          UpperCAmelCase__			:		Any													=				tokenizer.encode(
              '''sequence builders'''						,						add_special_tokens=_A						,						add_prefix_space=_A )
          UpperCAmelCase__			:		List[str]													=				tokenizer.encode(
              '''sequence builders'''						,						'''multi-sequence build'''						,						add_special_tokens=_A						,						add_prefix_space=_A )

          UpperCAmelCase__			:		List[Any]													=				tokenizer.build_inputs_with_special_tokens(_A )
          UpperCAmelCase__			:		Dict													=				tokenizer.build_inputs_with_special_tokens(_A						,						_A )

          assert encoded_sentence == encoded_text_from_decode
          assert encoded_pair == encoded_pair_from_decode






      def lowercase_							(					self				:    Optional[Any] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Optional[int]													=				self.get_tokenizer()

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

          # Testing encoder arguments
          UpperCAmelCase__			:		Optional[int]													=				tokenizer.encode(_A						,						add_special_tokens=_A						,						add_prefix_space=_A )
          UpperCAmelCase__			:		str													=				tokenizer.convert_ids_to_tokens(encoded[0] )[0]
          self.assertNotEqual(_A						,						_A )

          UpperCAmelCase__			:		Dict													=				tokenizer.encode(_A						,						add_special_tokens=_A						,						add_prefix_space=_A )
          UpperCAmelCase__			:		Dict													=				tokenizer.convert_ids_to_tokens(encoded[0] )[0]
          self.assertEqual(_A						,						_A )

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

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

          UpperCAmelCase__			:		Optional[Any]													=				'''Encode <mask> sequence'''
          UpperCAmelCase__			:		str													=				'''Encode <mask>sequence'''

          UpperCAmelCase__			:		Union[str, Any]													=				tokenizer.encode(_A )
          UpperCAmelCase__			:		Optional[int]													=				encoded.index(_A )
          UpperCAmelCase__			:		str													=				tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1] )[0]
          self.assertEqual(_A						,						_A )

          UpperCAmelCase__			:		List[Any]													=				tokenizer.encode(_A )
          UpperCAmelCase__			:		str													=				encoded.index(_A )
          UpperCAmelCase__			:		Tuple													=				tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1] )[0]
          self.assertNotEqual(_A						,						_A )






      def lowercase_							(					self				:    Any ):


          '''simple docstring'''


          pass






      def lowercase_							(					self				:    str ):


          '''simple docstring'''


          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
                  UpperCAmelCase__			:		Union[str, Any]													=				self.rust_tokenizer_class.from_pretrained(_A						,						**_A )
                  UpperCAmelCase__			:		int													=				self.tokenizer_class.from_pretrained(_A						,						**_A )
                  UpperCAmelCase__			:		int													=				'''A, <mask> AllenNLP sentence.'''
                  UpperCAmelCase__			:		Union[str, Any]													=				tokenizer_r.encode_plus(_A						,						add_special_tokens=_A						,						return_token_type_ids=_A )
                  UpperCAmelCase__			:		Dict													=				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__			:		Dict													=				tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids'''] )
                  UpperCAmelCase__			:		List[str]													=				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, 50_264, 3_823, 487, 21_992, 3_645, 4, 2] )
                  self.assertSequenceEqual(tokens_r['''input_ids''']						,						[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 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 lowercase_							(					self				:    Optional[Any] ):


          '''simple docstring'''


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

              UpperCAmelCase__			:		str													=				json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__() )
              UpperCAmelCase__			:		List[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 lowercase_							(					self				:    Dict ):


          '''simple docstring'''


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

                  UpperCAmelCase__			:		List[Any]													=				self.rust_tokenizer_class.from_pretrained(
                      _A						,						use_fast=_A						,						add_prefix_space=_A						,						trim_offsets=_A )
                  UpperCAmelCase__			:		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 ) + 1, len(_A ) + 1 + len(_A ))						,						)

                  UpperCAmelCase__			:		Optional[int]													=				self.rust_tokenizer_class.from_pretrained(
                      _A						,						use_fast=_A						,						add_prefix_space=_A						,						trim_offsets=_A )
                  UpperCAmelCase__			:		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 ) + 1, len(_A ) + 1 + len(_A ))						,						)

                  UpperCAmelCase__			:		Any													=				self.rust_tokenizer_class.from_pretrained(
                      _A						,						use_fast=_A						,						add_prefix_space=_A						,						trim_offsets=_A )
                  UpperCAmelCase__			:		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 ), len(_A ) + 1 + len(_A ))						,						)

                  UpperCAmelCase__			:		List[Any]													=				self.rust_tokenizer_class.from_pretrained(
                      _A						,						use_fast=_A						,						add_prefix_space=_A						,						trim_offsets=_A )
                  UpperCAmelCase__			:		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 ))						,						)

                  UpperCAmelCase__			:		Optional[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)),
                  # )

                  UpperCAmelCase__			:		Any													=				self.rust_tokenizer_class.from_pretrained(
                      _A						,						use_fast=_A						,						add_prefix_space=_A						,						trim_offsets=_A )
                  UpperCAmelCase__			:		Dict													=				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__			:		Union[str, Any]													=				self.rust_tokenizer_class.from_pretrained(
                      _A						,						use_fast=_A						,						add_prefix_space=_A						,						trim_offsets=_A )
                  UpperCAmelCase__			:		List[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 ))						,						)

                  UpperCAmelCase__			:		Union[str, Any]													=				self.rust_tokenizer_class.from_pretrained(
                      _A						,						use_fast=_A						,						add_prefix_space=_A						,						trim_offsets=_A )
                  UpperCAmelCase__			:		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 ))						,						)




'''simple docstring'''
import re

from filelock import FileLock


try:
  import nltk

  UpperCamelCase__    					=      True
except (ImportError, ModuleNotFoundError):
  UpperCamelCase__    					=      False

if NLTK_AVAILABLE:
  with FileLock('''.lock''') as lock:
    nltk.download('''punkt''', quiet=True)





def 					a__       (					lowerCAmelCase__						)    ->	str:
    re.sub('''<n>'''  ,					''''''  ,					lowerCAmelCase__						)  # remove pegasus newline char
    assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
    return "\n".join(nltk.sent_tokenize(lowerCAmelCase__						)						)
