



"""simple docstring"""





import os
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


if TYPE_CHECKING:
  from transformers.pipelines.conversational import Conversation

SCREAMING_SNAKE_CASE				:     Optional[int]          =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE				:     List[str]          =	{'''vocab_file''': '''tokenizer.model'''}

SCREAMING_SNAKE_CASE				:     str          =	{
    '''vocab_file''': {
        '''hf-internal-testing/llama-tokenizer''': '''https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer.model''',
    },
    '''tokenizer_file''': {
        '''hf-internal-testing/llama-tokenizer''': '''https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer_config.json''',
    },
}
SCREAMING_SNAKE_CASE				:     Tuple          =	{
    '''hf-internal-testing/llama-tokenizer''': 2_0_4_8,
}
SCREAMING_SNAKE_CASE				:     Tuple          =	'''▁'''

SCREAMING_SNAKE_CASE				:     Optional[int]          =	'''[INST]''', '''[/INST]'''
SCREAMING_SNAKE_CASE				:     Union[str, Any]          =	'''<<SYS>>\n''', '''\n<</SYS>>\n\n'''

# fmt: off
SCREAMING_SNAKE_CASE				:     Optional[Any]          =	'''You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\
answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\
that your responses are socially unbiased and positive in nature.

If a question does not make any sense, or is not factually coherent, explain why instead of answering something not\
correct. If you don\'t know the answer to a question, please don\'t share false information.'''


class       __lowerCamelCase	(   __lowercase    ):

   '''simple docstring'''





   __UpperCamelCase									=   VOCAB_FILES_NAMES
   __UpperCamelCase									=   PRETRAINED_VOCAB_FILES_MAP
   __UpperCamelCase									=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCamelCase									=   ['input_ids', 'attention_mask']







   def __init__(self       ,	lowerCamelCase       ,	lowerCamelCase="<unk>"       ,	lowerCamelCase="<s>"       ,	lowerCamelCase="</s>"       ,	lowerCamelCase=None       ,	lowerCamelCase = None       ,	lowerCamelCase=True       ,	lowerCamelCase=False       ,	lowerCamelCase=False       ,	lowerCamelCase=True       ,	**lowerCamelCase       ,	):




      '''simple docstring'''




      _lowerCAmelCase					     =		{} if sp_model_kwargs is None else sp_model_kwargs
      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else bos_token
      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else eos_token
      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else unk_token
      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else pad_token
      super().__init__(
          bos_token=lowerCamelCase       ,	eos_token=lowerCamelCase       ,	unk_token=lowerCamelCase       ,	pad_token=lowerCamelCase       ,	add_bos_token=lowerCamelCase       ,	add_eos_token=lowerCamelCase       ,	sp_model_kwargs=self.sp_model_kwargs       ,	clean_up_tokenization_spaces=lowerCamelCase       ,	legacy=lowerCamelCase       ,	**lowerCamelCase       ,	)
      if legacy:
         logger.warning_once(
             f"""You are using the legacy behaviour of the {self.__class__}. This means that tokens that come after special tokens will not be properly handled. We recommend you to"""
             """ read the related pull request available at https://github.com/huggingface/transformers/pull/24565"""				)
      _lowerCAmelCase					     =		legacy
      _lowerCAmelCase					     =		vocab_file
      _lowerCAmelCase					     =		add_bos_token
      _lowerCAmelCase					     =		add_eos_token
      _lowerCAmelCase					     =		spm.SentencePieceProcessor(**self.sp_model_kwargs				)
      self.sp_model.Load(lowerCamelCase				)







   def __getstate__(self				):




      '''simple docstring'''




      _lowerCAmelCase					     =		self.__dict__.copy()
      _lowerCAmelCase					     =		None
      _lowerCAmelCase					     =		self.sp_model.serialized_model_proto()
      return state







   def __setstate__(self       ,	lowerCamelCase				):




      '''simple docstring'''




      _lowerCAmelCase					     =		d
      _lowerCAmelCase					     =		spm.SentencePieceProcessor(**self.sp_model_kwargs				)
      self.sp_model.LoadFromSerializedProto(self.sp_model_proto				)







   @property
   def 							A__						(self				):




      '''simple docstring'''




      return self.sp_model.get_piece_size()







   def 							A__						(self				):




      '''simple docstring'''




      _lowerCAmelCase					     =		{self.convert_ids_to_tokens(lowerCamelCase				): i for i in range(self.vocab_size				)}
      vocab.update(self.added_tokens_encoder				)
      return vocab







   def 							A__						(self       ,	lowerCamelCase       ,	**lowerCamelCase				):




      '''simple docstring'''




      if not self.legacy:
         _lowerCAmelCase					     =		SPIECE_UNDERLINE + text.replace(lowerCamelCase       ,	""" """				)
      return super().tokenize(lowerCamelCase       ,	**lowerCamelCase				)







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      if not self.legacy:
         _lowerCAmelCase					     =		text.startswith(lowerCamelCase				)
         if is_first:
            _lowerCAmelCase					     =		text[1:]

      _lowerCAmelCase					     =		self.sp_model.encode(lowerCamelCase       ,	out_type=lowerCamelCase				)

      if not self.legacy and not is_first and not text.startswith(""" """				) and tokens[0].startswith(lowerCamelCase				):
         _lowerCAmelCase					     =		([tokens[0][1:]] if len(tokens[0]				) > 1 else []) + tokens[1:]
      return tokens







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      return self.sp_model.piece_to_id(lowerCamelCase				)







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      _lowerCAmelCase					     =		self.sp_model.IdToPiece(lowerCamelCase				)
      return token







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      _lowerCAmelCase					     =		[]
      _lowerCAmelCase					     =		""""""
      _lowerCAmelCase					     =		False
      for i, token in enumerate(lowerCamelCase				):
         # make sure that special tokens are not decoded using sentencepiece model
         if token in self.all_special_tokens:
            if not prev_is_special and i != 0:
               out_string += " "
            out_string += self.sp_model.decode(lowerCamelCase				) + token
            _lowerCAmelCase					     =		True
            _lowerCAmelCase					     =		[]
         else:
            current_sub_tokens.append(lowerCamelCase				)
            _lowerCAmelCase					     =		False
      out_string += self.sp_model.decode(lowerCamelCase				)
      return out_string







   def 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase = None				):




      '''simple docstring'''




      if not os.path.isdir(lowerCamelCase				):
         logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
         return
      _lowerCAmelCase					     =		os.path.join(
          lowerCamelCase       ,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

      if os.path.abspath(self.vocab_file				) != os.path.abspath(lowerCamelCase				) and os.path.isfile(self.vocab_file				):
         copyfile(self.vocab_file       ,	lowerCamelCase				)
      elif not os.path.isfile(self.vocab_file				):
         with open(lowerCamelCase       ,	"""wb"""				) as fi:
            _lowerCAmelCase					     =		self.sp_model.serialized_model_proto()
            fi.write(lowerCamelCase				)

      return (out_vocab_file,)







   def 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase=None				):




      '''simple docstring'''




      _lowerCAmelCase					     =		[self.bos_token_id] if self.add_bos_token else []
      _lowerCAmelCase					     =		[self.eos_token_id] if self.add_eos_token else []

      _lowerCAmelCase					     =		bos_token_id + token_ids_a + eos_token_id

      if token_ids_a is not None:
         _lowerCAmelCase					     =		output + bos_token_id + token_ids_a + eos_token_id

      return output







   def 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase = None       ,	lowerCamelCase = False				):




      '''simple docstring'''




      if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=lowerCamelCase       ,	token_ids_a=lowerCamelCase       ,	already_has_special_tokens=lowerCamelCase				)

      _lowerCAmelCase					     =		[1] if self.add_bos_token else []
      _lowerCAmelCase					     =		[1] if self.add_eos_token else []

      if token_ids_a is None:
         return bos_token_id + ([0] * len(lowerCamelCase				)) + eos_token_id
      return (
          bos_token_id
          + ([0] * len(lowerCamelCase				))
          + eos_token_id
          + bos_token_id
          + ([0] * len(lowerCamelCase				))
          + eos_token_id
      )







   def 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase = None				):




      '''simple docstring'''




      _lowerCAmelCase					     =		[self.bos_token_id] if self.add_bos_token else []
      _lowerCAmelCase					     =		[self.eos_token_id] if self.add_eos_token else []

      _lowerCAmelCase					     =		[0] * len(bos_token_id + token_ids_a + eos_token_id				)

      if token_ids_a is not None:
         output += [1] * len(bos_token_id + token_ids_a + eos_token_id				)

      return output







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      _lowerCAmelCase					     =		list(conversation.iter_texts()				)
      if not all([is_user for is_user, msg in dialogue[::2]]				) or not all(
          [not is_user for is_user, msg in dialogue[1::2]]				):
         raise ValueError(
             """The model only supports 'user' and 'assistant' roles, starting with user and alternating (u/a/u/a/u...)"""				)

      _lowerCAmelCase					     =		[]
      if len(conversation.past_user_inputs				) > 0:
         if not conversation.past_user_inputs[0].startswith(lowerCamelCase				) or E_SYS not in conversation.past_user_inputs[0]:
            _lowerCAmelCase					     =		(
                B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
            )
      elif not dialogue[0][1].startswith(lowerCamelCase				) or E_SYS not in dialogue[0][1]:
         _lowerCAmelCase					     =		(dialogue[0][0], B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + dialogue[0][1])

      dialog_tokens += sum(
          [
              [self.bos_token_id]
              + self.encode(
                  f"""{B_INST} {(prompt[1]).strip()} {E_INST} {(answer[1]).strip()} """       ,	add_special_tokens=lowerCamelCase				)
              + [self.eos_token_id]
              for prompt, answer in zip(dialogue[::2]       ,	dialogue[1::2]				)
          ]       ,	[]       ,	)
      if not (dialogue[-1][0]):
         raise ValueError(f"""Last message must be from user, got {dialogue[-1]["role"]}"""				)
      dialog_tokens += [self.bos_token_id] + self.encode(
          f"""{B_INST} {(dialogue[-1][1]).strip()} {E_INST}"""       ,	add_special_tokens=lowerCamelCase				)
      return dialog_tokens




"""simple docstring"""





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				:     Optional[Any]          =	logging.get_logger(__name__)


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

# See all MVP models at https://huggingface.co/models?filter=mvp
SCREAMING_SNAKE_CASE				:     Union[str, Any]          =	{
    '''vocab_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json''',
    },
    '''added_tokens.json''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json''',
    },
    '''merges_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt''',
    },
}

SCREAMING_SNAKE_CASE				:     Union[str, Any]          =	{
    '''RUCAIBox/mvp''': 1_0_2_4,
}






@lru_cache()
def 	__UpperCAmelCase					(       )							->	Tuple:






   """simple docstring"""


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






def 	__UpperCAmelCase					(       snake_case_  :  Dict   )							->	List[Any]:






   """simple docstring"""


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



class       __lowerCamelCase	(   __lowercase    ):
   __UpperCamelCase									=   VOCAB_FILES_NAMES
   __UpperCamelCase									=   PRETRAINED_VOCAB_FILES_MAP
   __UpperCamelCase									=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCamelCase									=   ['input_ids', 'attention_mask']







   def __init__(self       ,	lowerCamelCase       ,	lowerCamelCase       ,	lowerCamelCase="replace"       ,	lowerCamelCase="<s>"       ,	lowerCamelCase="</s>"       ,	lowerCamelCase="</s>"       ,	lowerCamelCase="<s>"       ,	lowerCamelCase="<unk>"       ,	lowerCamelCase="<pad>"       ,	lowerCamelCase="<mask>"       ,	lowerCamelCase=False       ,	**lowerCamelCase       ,	):




      '''simple docstring'''




      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else bos_token
      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else eos_token
      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else sep_token
      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else cls_token
      _lowerCAmelCase					     =		AddedToken(lowerCamelCase       ,	lstrip=lowerCamelCase       ,	rstrip=lowerCamelCase				) if isinstance(lowerCamelCase       ,	lowerCamelCase				) else unk_token
      _lowerCAmelCase					     =		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
      _lowerCAmelCase					     =		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:
         _lowerCAmelCase					     =		json.load(lowerCamelCase				)
      _lowerCAmelCase					     =		{v: k for k, v in self.encoder.items()}
      _lowerCAmelCase					     =		errors  # how to handle errors in decoding
      _lowerCAmelCase					     =		bytes_to_unicode()
      _lowerCAmelCase					     =		{v: k for k, v in self.byte_encoder.items()}
      with open(lowerCamelCase       ,	encoding="""utf-8"""				) as merges_handle:
         _lowerCAmelCase					     =		merges_handle.read().split("""\n"""				)[1:-1]
      _lowerCAmelCase					     =		[tuple(merge.split()				) for merge in bpe_merges]
      _lowerCAmelCase					     =		dict(zip(lowerCamelCase       ,	range(len(lowerCamelCase				)				)				)				)
      _lowerCAmelCase					     =		{}
      _lowerCAmelCase					     =		add_prefix_space

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







   @property
   def 							A__						(self				):




      '''simple docstring'''




      return len(self.encoder				)







   def 							A__						(self				):




      '''simple docstring'''




      return dict(self.encoder       ,	**self.added_tokens_encoder				)







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      if token in self.cache:
         return self.cache[token]
      _lowerCAmelCase					     =		tuple(lowerCamelCase				)
      _lowerCAmelCase					     =		get_pairs(lowerCamelCase				)

      if not pairs:
         return token

      while True:
         _lowerCAmelCase					     =		min(lowerCamelCase       ,	key=lambda lowerCamelCase				: self.bpe_ranks.get(lowerCamelCase       ,	float("""inf"""				)				)				)
         if bigram not in self.bpe_ranks:
            break
         _lowerCAmelCase     ,						_lowerCAmelCase					     =		bigram
         _lowerCAmelCase					     =		[]
         _lowerCAmelCase					     =		0
         while i < len(lowerCamelCase				):
            try:
               _lowerCAmelCase					     =		word.index(lowerCamelCase       ,	lowerCamelCase				)
            except ValueError:
               new_word.extend(word[i:]				)
               break
            else:
               new_word.extend(word[i:j]				)
               _lowerCAmelCase					     =		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
         _lowerCAmelCase					     =		tuple(lowerCamelCase				)
         _lowerCAmelCase					     =		new_word
         if len(lowerCamelCase				) == 1:
            break
         else:
            _lowerCAmelCase					     =		get_pairs(lowerCamelCase				)
      _lowerCAmelCase					     =		""" """.join(lowerCamelCase				)
      _lowerCAmelCase					     =		word
      return word







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      _lowerCAmelCase					     =		[]
      for token in re.findall(self.pat       ,	lowerCamelCase				):
         _lowerCAmelCase					     =		"""""".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 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      return self.encoder.get(lowerCamelCase       ,	self.encoder.get(self.unk_token				)				)







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      return self.decoder.get(lowerCamelCase				)







   def 							A__						(self       ,	lowerCamelCase				):




      '''simple docstring'''




      _lowerCAmelCase					     =		"""""".join(lowerCamelCase				)
      _lowerCAmelCase					     =		bytearray([self.byte_decoder[c] for c in text]				).decode("""utf-8"""       ,	errors=self.errors				)
      return text







   def 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase = None				):




      '''simple docstring'''




      if not os.path.isdir(lowerCamelCase				):
         logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
         return
      _lowerCAmelCase					     =		os.path.join(
          lowerCamelCase       ,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)
      _lowerCAmelCase					     =		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"""				)

      _lowerCAmelCase					     =		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!"""				)
               _lowerCAmelCase					     =		token_index
            writer.write(""" """.join(lowerCamelCase				) + """\n"""				)
            index += 1

      return vocab_file, merge_file







   def 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase = None				):




      '''simple docstring'''




      if token_ids_a is None:
         return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      _lowerCAmelCase					     =		[self.cls_token_id]
      _lowerCAmelCase					     =		[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep







   def 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase = None       ,	lowerCamelCase = False				):




      '''simple docstring'''




      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 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase = None				):




      '''simple docstring'''




      _lowerCAmelCase					     =		[self.sep_token_id]
      _lowerCAmelCase					     =		[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 							A__						(self       ,	lowerCamelCase       ,	lowerCamelCase=False       ,	**lowerCamelCase				):




      '''simple docstring'''




      _lowerCAmelCase					     =		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()):
         _lowerCAmelCase					     =		""" """ + text
      return (text, kwargs)