

import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE         =    logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE         =    {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

_SCREAMING_SNAKE_CASE         =    {
    '''vocab_file''': {
        '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json''',
        '''allenai/longformer-large-4096''': (
            '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-large-4096-finetuned-triviaqa''': (
            '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-base-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-large-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt''',
        '''allenai/longformer-large-4096''': (
            '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-large-4096-finetuned-triviaqa''': (
            '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-base-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-large-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'''
        ),
    },
}

_SCREAMING_SNAKE_CASE         =    {
    '''allenai/longformer-base-4096''': 4096,
    '''allenai/longformer-large-4096''': 4096,
    '''allenai/longformer-large-4096-finetuned-triviaqa''': 4096,
    '''allenai/longformer-base-4096-extra.pos.embd.only''': 4096,
    '''allenai/longformer-large-4096-extra.pos.embd.only''': 4096,
}
@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def        UpperCAmelCase_     (		):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					(
         list(range(ord('''!'''       )   ,	ord('''~'''       ) + 1       )       ) + list(range(ord('''¡'''       )   ,	ord('''¬'''       ) + 1       )       ) + list(range(ord('''®'''       )   ,	ord('''ÿ'''       ) + 1       )       )
     )
     SCREAMING_SNAKE_CASE__					=					bs[:]
     SCREAMING_SNAKE_CASE__					=					0
     for b in range(2**8       ):
          if b not in bs:
               bs.append(_A       )
               cs.append(2**8 + n       )
               n += 1
     SCREAMING_SNAKE_CASE__					=					[chr(_A       ) for n in cs]
     return dict(zip(_A   ,	_A       )       )
def        UpperCAmelCase_     (		_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					set()
     SCREAMING_SNAKE_CASE__					=					word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)       )
          SCREAMING_SNAKE_CASE__					=					char
     return pairs







class  UpperCAmelCase__	( A__ ):






  """simple docstring"""


  a     =      VOCAB_FILES_NAMES
  a     =      PRETRAINED_VOCAB_FILES_MAP
  a     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  a     =      ["input_ids", "attention_mask"]






  def __init__(							self		:	Any			,     __lowerCamelCase		:	int			,     __lowerCamelCase		:	Union[str, Any]			,     __lowerCamelCase		:	Optional[int]="replace"			,     __lowerCamelCase		:	str="<s>"			,     __lowerCamelCase		:	Dict="</s>"			,     __lowerCamelCase		:	Optional[int]="</s>"			,     __lowerCamelCase		:	Dict="<s>"			,     __lowerCamelCase		:	Any="<unk>"			,     __lowerCamelCase		:	Optional[int]="<pad>"			,     __lowerCamelCase		:	Union[str, Any]="<mask>"			,     __lowerCamelCase		:	int=False			,     **__lowerCamelCase		:	Dict			,     )	->							Tuple:
       SCREAMING_SNAKE_CASE__					=					AddedToken(__lowerCamelCase			,     lstrip=__lowerCamelCase			,     rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase			,     __lowerCamelCase      ) else bos_token
       SCREAMING_SNAKE_CASE__					=					AddedToken(__lowerCamelCase			,     lstrip=__lowerCamelCase			,     rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase			,     __lowerCamelCase      ) else eos_token
       SCREAMING_SNAKE_CASE__					=					AddedToken(__lowerCamelCase			,     lstrip=__lowerCamelCase			,     rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase			,     __lowerCamelCase      ) else sep_token
       SCREAMING_SNAKE_CASE__					=					AddedToken(__lowerCamelCase			,     lstrip=__lowerCamelCase			,     rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase			,     __lowerCamelCase      ) else cls_token
       SCREAMING_SNAKE_CASE__					=					AddedToken(__lowerCamelCase			,     lstrip=__lowerCamelCase			,     rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase			,     __lowerCamelCase      ) else unk_token
       SCREAMING_SNAKE_CASE__					=					AddedToken(__lowerCamelCase			,     lstrip=__lowerCamelCase			,     rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase			,     __lowerCamelCase      ) else pad_token

       # Mask token behave like a normal word, i.e. include the space before it
       SCREAMING_SNAKE_CASE__					=					AddedToken(__lowerCamelCase			,     lstrip=__lowerCamelCase			,     rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase			,     __lowerCamelCase      ) else mask_token

       super().__init__(
           errors=__lowerCamelCase			,     bos_token=__lowerCamelCase			,     eos_token=__lowerCamelCase			,     unk_token=__lowerCamelCase			,     sep_token=__lowerCamelCase			,     cls_token=__lowerCamelCase			,     pad_token=__lowerCamelCase			,     mask_token=__lowerCamelCase			,     add_prefix_space=__lowerCamelCase			,     **__lowerCamelCase			,     )

       with open(__lowerCamelCase			,     encoding='''utf-8'''      ) as vocab_handle:
            SCREAMING_SNAKE_CASE__					=					json.load(__lowerCamelCase      )
       SCREAMING_SNAKE_CASE__					=					{v: k for k, v in self.encoder.items()}
       SCREAMING_SNAKE_CASE__					=					errors  # how to handle errors in decoding
       SCREAMING_SNAKE_CASE__					=					bytes_to_unicode()
       SCREAMING_SNAKE_CASE__					=					{v: k for k, v in self.byte_encoder.items()}
       with open(__lowerCamelCase			,     encoding='''utf-8'''      ) as merges_handle:
            SCREAMING_SNAKE_CASE__					=					merges_handle.read().split('''\n'''      )[1:-1]
       SCREAMING_SNAKE_CASE__					=					[tuple(merge.split()      ) for merge in bpe_merges]
       SCREAMING_SNAKE_CASE__					=					dict(zip(__lowerCamelCase			,     range(len(__lowerCamelCase      )      )      )      )
       SCREAMING_SNAKE_CASE__					=					{}
       SCREAMING_SNAKE_CASE__					=					add_prefix_space

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       SCREAMING_SNAKE_CASE__					=					re.compile(r'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''      )






  @property
  def    lowercase_	(							self		:	Any      )	->							Union[str, Any]:
       return len(self.encoder      )






  def    lowercase_	(							self		:	Any      )	->							str:
       return dict(self.encoder			,     **self.added_tokens_encoder      )






  def    lowercase_	(							self		:	List[str]			,     __lowerCamelCase		:	int      )	->							Any:
       if token in self.cache:
            return self.cache[token]
       SCREAMING_SNAKE_CASE__					=					tuple(__lowerCamelCase      )
       SCREAMING_SNAKE_CASE__					=					get_pairs(__lowerCamelCase      )

       if not pairs:
            return token

       while True:
            SCREAMING_SNAKE_CASE__					=					min(__lowerCamelCase			,     key=lambda __lowerCamelCase      : self.bpe_ranks.get(__lowerCamelCase			,     float('''inf'''      )      )      )
            if bigram not in self.bpe_ranks:
                 break
            SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					bigram
            SCREAMING_SNAKE_CASE__					=					[]
            SCREAMING_SNAKE_CASE__					=					0
            while i < len(__lowerCamelCase      ):
                 try:
                      SCREAMING_SNAKE_CASE__					=					word.index(__lowerCamelCase			,     __lowerCamelCase      )
                 except ValueError:
                      new_word.extend(word[i:]      )
                      break
                 else:
                      new_word.extend(word[i:j]      )
                      SCREAMING_SNAKE_CASE__					=					j

                 if word[i] == first and i < len(__lowerCamelCase      ) - 1 and word[i + 1] == second:
                      new_word.append(first + second      )
                      i += 2
                 else:
                      new_word.append(word[i]      )
                      i += 1
            SCREAMING_SNAKE_CASE__					=					tuple(__lowerCamelCase      )
            SCREAMING_SNAKE_CASE__					=					new_word
            if len(__lowerCamelCase      ) == 1:
                 break
            else:
                 SCREAMING_SNAKE_CASE__					=					get_pairs(__lowerCamelCase      )
       SCREAMING_SNAKE_CASE__					=					''' '''.join(__lowerCamelCase      )
       SCREAMING_SNAKE_CASE__					=					word
       return word






  def    lowercase_	(							self		:	str			,     __lowerCamelCase		:	Union[str, Any]      )	->							str:
       SCREAMING_SNAKE_CASE__					=					[]
       for token in re.findall(self.pat			,     __lowerCamelCase      ):
            SCREAMING_SNAKE_CASE__					=					''''''.join(
                self.byte_encoder[b] for b in token.encode('''utf-8'''      )      )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
            bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__lowerCamelCase      ).split(''' '''      )      )
       return bpe_tokens






  def    lowercase_	(							self		:	Optional[Any]			,     __lowerCamelCase		:	Optional[Any]      )	->							List[str]:
       return self.encoder.get(__lowerCamelCase			,     self.encoder.get(self.unk_token      )      )






  def    lowercase_	(							self		:	int			,     __lowerCamelCase		:	str      )	->							int:
       return self.decoder.get(__lowerCamelCase      )






  def    lowercase_	(							self		:	Union[str, Any]			,     __lowerCamelCase		:	Optional[Any]      )	->							Tuple:
       SCREAMING_SNAKE_CASE__					=					''''''.join(__lowerCamelCase      )
       SCREAMING_SNAKE_CASE__					=					bytearray([self.byte_decoder[c] for c in text]      ).decode('''utf-8'''			,     errors=self.errors      )
       return text






  def    lowercase_	(							self		:	List[Any]			,     __lowerCamelCase		:	str			,     __lowerCamelCase		:	Optional[str] = None      )	->							Tuple[str]:
       if not os.path.isdir(__lowerCamelCase      ):
            logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''      )
            return
       SCREAMING_SNAKE_CASE__					=					os.path.join(
           __lowerCamelCase			,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
       SCREAMING_SNAKE_CASE__					=					os.path.join(
           __lowerCamelCase			,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']      )

       with open(__lowerCamelCase			,     '''w'''			,     encoding='''utf-8'''      ) as f:
            f.write(json.dumps(self.encoder			,     indent=2			,     sort_keys=__lowerCamelCase			,     ensure_ascii=__lowerCamelCase      ) + '''\n'''      )

       SCREAMING_SNAKE_CASE__					=					0
       with open(__lowerCamelCase			,     '''w'''			,     encoding='''utf-8'''      ) as writer:
            writer.write('''#version: 0.2\n'''      )
            for bpe_tokens, token_index in sorted(self.bpe_ranks.items()			,     key=lambda __lowerCamelCase      : kv[1]      ):
                 if index != token_index:
                      logger.warning(
                          f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                          ''' Please check that the tokenizer is not corrupted!'''      )
                      SCREAMING_SNAKE_CASE__					=					token_index
                 writer.write(''' '''.join(__lowerCamelCase      ) + '''\n'''      )
                 index += 1

       return vocab_file, merge_file






  def    lowercase_	(							self		:	Optional[Any]			,     __lowerCamelCase		:	List[int]			,     __lowerCamelCase		:	Optional[List[int]] = None      )	->							List[int]:
       if token_ids_a is None:
            return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       SCREAMING_SNAKE_CASE__					=					[self.cls_token_id]
       SCREAMING_SNAKE_CASE__					=					[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep






  def    lowercase_	(							self		:	Any			,     __lowerCamelCase		:	List[int]			,     __lowerCamelCase		:	Optional[List[int]] = None			,     __lowerCamelCase		:	bool = False      )	->							List[int]:
       if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=__lowerCamelCase			,     token_ids_a=__lowerCamelCase			,     already_has_special_tokens=__lowerCamelCase      )

       if token_ids_a is None:
            return [1] + ([0] * len(__lowerCamelCase      )) + [1]
       return [1] + ([0] * len(__lowerCamelCase      )) + [1, 1] + ([0] * len(__lowerCamelCase      )) + [1]






  def    lowercase_	(							self		:	Any			,     __lowerCamelCase		:	List[int]			,     __lowerCamelCase		:	Optional[List[int]] = None      )	->							List[int]:
       SCREAMING_SNAKE_CASE__					=					[self.sep_token_id]
       SCREAMING_SNAKE_CASE__					=					[self.cls_token_id]

       if token_ids_a is None:
            return len(cls + token_ids_a + sep      ) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep      ) * [0]







  def    lowercase_	(							self		:	List[str]			,     __lowerCamelCase		:	int			,     __lowerCamelCase		:	Dict=False			,     **__lowerCamelCase		:	Optional[Any]      )	->							int:
       SCREAMING_SNAKE_CASE__					=					kwargs.pop('''add_prefix_space'''			,     self.add_prefix_space      )
       if (is_split_into_words or add_prefix_space) and (len(__lowerCamelCase      ) > 0 and not text[0].isspace()):
            SCREAMING_SNAKE_CASE__					=					''' ''' + text
       return (text, kwargs)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE  :						List[Any]         =    {
    '''configuration_roberta''': ['''ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RobertaConfig''', '''RobertaOnnxConfig'''],
    '''tokenization_roberta''': ['''RobertaTokenizer'''],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _SCREAMING_SNAKE_CASE  :						Optional[int]         =    ['''RobertaTokenizerFast''']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _SCREAMING_SNAKE_CASE  :						Tuple         =    [
           '''ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''RobertaForCausalLM''',
           '''RobertaForMaskedLM''',
           '''RobertaForMultipleChoice''',
           '''RobertaForQuestionAnswering''',
           '''RobertaForSequenceClassification''',
           '''RobertaForTokenClassification''',
           '''RobertaModel''',
           '''RobertaPreTrainedModel''',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _SCREAMING_SNAKE_CASE  :						List[Any]         =    [
           '''TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''TFRobertaForCausalLM''',
           '''TFRobertaForMaskedLM''',
           '''TFRobertaForMultipleChoice''',
           '''TFRobertaForQuestionAnswering''',
           '''TFRobertaForSequenceClassification''',
           '''TFRobertaForTokenClassification''',
           '''TFRobertaMainLayer''',
           '''TFRobertaModel''',
           '''TFRobertaPreTrainedModel''',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _SCREAMING_SNAKE_CASE  :						Optional[Any]         =    [
           '''FlaxRobertaForCausalLM''',
           '''FlaxRobertaForMaskedLM''',
           '''FlaxRobertaForMultipleChoice''',
           '''FlaxRobertaForQuestionAnswering''',
           '''FlaxRobertaForSequenceClassification''',
           '''FlaxRobertaForTokenClassification''',
           '''FlaxRobertaModel''',
           '''FlaxRobertaPreTrainedModel''',
       ]


if TYPE_CHECKING:
       from .configuration_roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig, RobertaOnnxConfig
       from .tokenization_roberta import RobertaTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_roberta_fast import RobertaTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_roberta import (
                  ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
                  RobertaForCausalLM,
                  RobertaForMaskedLM,
                  RobertaForMultipleChoice,
                  RobertaForQuestionAnswering,
                  RobertaForSequenceClassification,
                  RobertaForTokenClassification,
                  RobertaModel,
                  RobertaPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_roberta import (
                  TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFRobertaForCausalLM,
                  TFRobertaForMaskedLM,
                  TFRobertaForMultipleChoice,
                  TFRobertaForQuestionAnswering,
                  TFRobertaForSequenceClassification,
                  TFRobertaForTokenClassification,
                  TFRobertaMainLayer,
                  TFRobertaModel,
                  TFRobertaPreTrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_roberta import (
                  FlaxRobertaForCausalLM,
                  FlaxRobertaForMaskedLM,
                  FlaxRobertaForMultipleChoice,
                  FlaxRobertaForQuestionAnswering,
                  FlaxRobertaForSequenceClassification,
                  FlaxRobertaForTokenClassification,
                  FlaxRobertaModel,
                  FlaxRobertaPreTrainedModel,
              )

else:
       import sys

       _SCREAMING_SNAKE_CASE  :						str         =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


