import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase__											=					logging.get_logger(__name__)

UpperCamelCase__											=					'▁'

UpperCamelCase__											=					{'vocab_file': 'vocab.txt', 'sentencepiece_model_ckpt': 'sentencepiece.bpe.model'}

UpperCamelCase__											=					{
    'sentencepiece_model_file': 'sentencepiece.bpe.model',
    'vocab_file': 'vocab.txt',
}

UpperCamelCase__											=					{
    'vocab_file': {
        'ernie-m-base': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt',
        'ernie-m-large': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt',
    },
    'sentencepiece_model_file': {
        'ernie-m-base': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model',
        'ernie-m-large': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model',
    },
}

UpperCamelCase__											=					{
    'ernie-m-base': 5_1_4,
    'ernie-m-large': 5_1_4,
}

UpperCamelCase__											=					{
    'ernie-m-base': {'do_lower_case': False},
    'ernie-m-large': {'do_lower_case': False},
}





class      A							(				UpperCAmelCase_     ):
   __UpperCAmelCase : List[str]      =			["input_ids"]

   __UpperCAmelCase : int      =			VOCAB_FILES_NAMES
   __UpperCAmelCase : Tuple      =			PRETRAINED_INIT_CONFIGURATION
   __UpperCAmelCase : Union[str, Any]      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase : Optional[Any]      =			PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase : str      =			RESOURCE_FILES_NAMES


   def __init__(self     :						Tuple       ,  __UpperCAmelCase     :						List[str]       ,  __UpperCAmelCase     :						Dict=None       ,  __UpperCAmelCase     :						List[str]=False       ,  __UpperCAmelCase     :						Optional[Any]="utf8"       ,  __UpperCAmelCase     :						Union[str, Any]="[UNK]"       ,  __UpperCAmelCase     :						Any="[SEP]"       ,  __UpperCAmelCase     :						Union[str, Any]="[PAD]"       ,  __UpperCAmelCase     :						Optional[Any]="[CLS]"       ,  __UpperCAmelCase     :						Tuple="[MASK]"       ,  __UpperCAmelCase     :						Optional[Dict[str, Any]] = None       ,  **__UpperCAmelCase     :						Optional[Any]       ,  )						->				None:
         """simple docstring"""



         UpperCAmelCase__								=  {} if sp_model_kwargs is None else sp_model_kwargs
         super().__init__(
             do_lower_case=__UpperCAmelCase       ,  unk_token=__UpperCAmelCase       ,  sep_token=__UpperCAmelCase       ,  pad_token=__UpperCAmelCase       ,  cls_token=__UpperCAmelCase       ,  mask_token=__UpperCAmelCase       ,  vocab_file=__UpperCAmelCase       ,  encoding=__UpperCAmelCase       ,  sp_model_kwargs=self.sp_model_kwargs       ,  **__UpperCAmelCase       ,  )
         UpperCAmelCase__								=  do_lower_case
         UpperCAmelCase__								=  sentencepiece_model_ckpt
         UpperCAmelCase__								=  spm.SentencePieceProcessor(**self.sp_model_kwargs		)
         self.sp_model.Load(__UpperCAmelCase		)

         # to mimic paddlenlp.transformers.ernie_m.tokenizer.ErnieMTokenizer functioning
         if vocab_file is not None:
               UpperCAmelCase__								=  self.load_vocab(filepath=__UpperCAmelCase		)
         else:
               UpperCAmelCase__								=  {self.sp_model.id_to_piece(__UpperCAmelCase		): id for id in range(self.sp_model.get_piece_size()		)}
         UpperCAmelCase__								=  {v: k for k, v in self.vocab.items()}


   def 			lowercase_      (self     :						Optional[Any]       ,  __UpperCAmelCase     :						str		)						->				int:
         """simple docstring"""



         if text is None:
               return None

         UpperCAmelCase__								=  self.tokenize(__UpperCAmelCase		)
         UpperCAmelCase__		,      UpperCAmelCase__								=  "", []

         for i, ch in enumerate(__UpperCAmelCase		):
               if ch in self.SP_CHAR_MAPPING:
                     UpperCAmelCase__								=  self.SP_CHAR_MAPPING.get(__UpperCAmelCase		)
               else:
                     UpperCAmelCase__								=  unicodedata.normalize("NFKC"       ,  __UpperCAmelCase		)
               if self.is_whitespace(__UpperCAmelCase		):
                     continue
               normalized_text += ch
               char_mapping.extend([i] * len(__UpperCAmelCase		)		)

         UpperCAmelCase__		,      UpperCAmelCase__		,      UpperCAmelCase__								=  normalized_text, [], 0

         if self.do_lower_case:
               UpperCAmelCase__								=  text.lower()

         for token in split_tokens:
               if token[:1] == "▁":
                     UpperCAmelCase__								=  token[1:]
               UpperCAmelCase__								=  text[offset:].index(__UpperCAmelCase		) + offset
               UpperCAmelCase__								=  start + len(__UpperCAmelCase		)

               token_mapping.append((char_mapping[start], char_mapping[end - 1] + 1)		)
               UpperCAmelCase__								=  end
         return token_mapping


   @property
   def 			lowercase_      (self     :						str		)						->				List[str]:
         """simple docstring"""



         return len(self.vocab		)


   def 			lowercase_      (self     :						Dict		)						->				Tuple:
         """simple docstring"""



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


   def __getstate__(self     :						List[str]		)						->				List[str]:
         """simple docstring"""



         UpperCAmelCase__								=  self.__dict__.copy()
         UpperCAmelCase__								=  None
         return state


   def __setstate__(self     :						int       ,  __UpperCAmelCase     :						Dict		)						->				List[str]:
         """simple docstring"""



         UpperCAmelCase__								=  d

         # for backward compatibility
         if not hasattr(self       ,  "sp_model_kwargs"		):
               UpperCAmelCase__								=  {}

         UpperCAmelCase__								=  spm.SentencePieceProcessor(**self.sp_model_kwargs		)
         self.sp_model.Load(self.sentencepiece_model_ckpt		)


   def 			lowercase_      (self     :						Union[str, Any]       ,  __UpperCAmelCase     :						str		)						->				Any:
         """simple docstring"""



         return "".join((self.SP_CHAR_MAPPING.get(__UpperCAmelCase       ,  __UpperCAmelCase		) for c in text)		)


   def 			lowercase_      (self     :						str       ,  __UpperCAmelCase     :						Any       ,  __UpperCAmelCase     :						Dict=False       ,  __UpperCAmelCase     :						str=6_4       ,  __UpperCAmelCase     :						str=0.1		)						->				str:
         """simple docstring"""



         if self.sp_model_kwargs.get("enable_sampling"		) is True:
               UpperCAmelCase__								=  True
         if self.sp_model_kwargs.get("alpha"		) is not None:
               UpperCAmelCase__								=  self.sp_model_kwargs.get("alpha"		)
         if self.sp_model_kwargs.get("nbest_size"		) is not None:
               UpperCAmelCase__								=  self.sp_model_kwargs.get("nbest_size"		)

         if not enable_sampling:
               UpperCAmelCase__								=  self.sp_model.EncodeAsPieces(__UpperCAmelCase		)
         else:
               UpperCAmelCase__								=  self.sp_model.SampleEncodeAsPieces(__UpperCAmelCase       ,  __UpperCAmelCase       ,  __UpperCAmelCase		)
         UpperCAmelCase__								=  []
         for pi, piece in enumerate(__UpperCAmelCase		):
               if piece == SPIECE_UNDERLINE:
                     if not pieces[pi + 1].startswith(__UpperCAmelCase		) and pi != 0:
                           new_pieces.append(__UpperCAmelCase		)
                           continue
                     else:
                           continue
               UpperCAmelCase__								=  0
               for i, chunk in enumerate(__UpperCAmelCase		):
                     if chunk == SPIECE_UNDERLINE:
                           continue
                     if self.is_ch_char(__UpperCAmelCase		) or self.is_punct(__UpperCAmelCase		):
                           if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
                                 new_pieces.append(piece[lst_i:i]		)
                           new_pieces.append(__UpperCAmelCase		)
                           UpperCAmelCase__								=  i + 1
                     elif chunk.isdigit() and i > 0 and not piece[i - 1].isdigit():
                           if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
                                 new_pieces.append(piece[lst_i:i]		)
                           UpperCAmelCase__								=  i
                     elif not chunk.isdigit() and i > 0 and piece[i - 1].isdigit():
                           if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
                                 new_pieces.append(piece[lst_i:i]		)
                           UpperCAmelCase__								=  i
               if len(__UpperCAmelCase		) > lst_i:
                     new_pieces.append(piece[lst_i:]		)
         return new_pieces


   def 			lowercase_      (self     :						Tuple       ,  __UpperCAmelCase     :						Dict		)						->				Any:
         """simple docstring"""



         UpperCAmelCase__								=  "".join(__UpperCAmelCase		).replace(__UpperCAmelCase       ,  " "		).strip()
         return out_string


   def 			lowercase_      (self     :						Any       ,  __UpperCAmelCase     :						Any		)						->				Tuple:
         """simple docstring"""



         UpperCAmelCase__								=  self.convert_ids_to_tokens(__UpperCAmelCase		)
         UpperCAmelCase__								=  "".join(__UpperCAmelCase		).replace(__UpperCAmelCase       ,  " "		).strip()
         return out_string


   def 			lowercase_      (self     :						Optional[Any]       ,  __UpperCAmelCase     :						Dict		)						->				Tuple:
         """simple docstring"""



         return self.vocab.get(__UpperCAmelCase       ,  self.vocab.get(self.unk_token		)		)


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



         return self.reverse_vocab.get(__UpperCAmelCase       ,  self.unk_token		)


   def 			lowercase_      (self     :						int       ,  __UpperCAmelCase     :						Dict       ,  __UpperCAmelCase     :						List[Any]=None		)						->				Dict:
         """simple docstring"""



         if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         UpperCAmelCase__								=  [self.cls_token_id]
         UpperCAmelCase__								=  [self.sep_token_id]
         return _cls + token_ids_a + _sep + _sep + token_ids_a + _sep


   def 			lowercase_      (self     :						str       ,  __UpperCAmelCase     :						Union[str, Any]       ,  __UpperCAmelCase     :						str=None		)						->				Dict:
         """simple docstring"""



         if offset_mapping_a is None:
               return [(0, 0)] + offset_mapping_a + [(0, 0)]

         return [(0, 0)] + offset_mapping_a + [(0, 0), (0, 0)] + offset_mapping_a + [(0, 0)]


   def 			lowercase_      (self     :						Union[str, Any]       ,  __UpperCAmelCase     :						Optional[int]       ,  __UpperCAmelCase     :						Optional[int]=None       ,  __UpperCAmelCase     :						Optional[int]=False		)						->				Tuple:
         """simple docstring"""



         if already_has_special_tokens:
               if token_ids_a is not None:
                     raise ValueError(
                         "You should not supply a second sequence if the provided sequence of "
                         "ids is already formatted with special tokens for the model."		)
               return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

         if token_ids_a is not None:
               return [1] + ([0] * len(__UpperCAmelCase		)) + [1, 1] + ([0] * len(__UpperCAmelCase		)) + [1]
         return [1] + ([0] * len(__UpperCAmelCase		)) + [1]


   def 			lowercase_      (self     :						Optional[Any]       ,  __UpperCAmelCase     :						List[int]       ,  __UpperCAmelCase     :						Optional[List[int]] = None		)						->				List[int]:
         """simple docstring"""



         if token_ids_a is None:
               # [CLS] X [SEP]
               return (len(__UpperCAmelCase		) + 2) * [0]

         # [CLS] A [SEP] [SEP] B [SEP]
         return [0] * (len(__UpperCAmelCase		) + 1) + [1] * (len(__UpperCAmelCase		) + 3)


   def 			lowercase_      (self     :						Any       ,  __UpperCAmelCase     :						Dict		)						->				Optional[Any]:
         """simple docstring"""



         if "\u4e00" <= char <= "\u9fff":
               return True
         return False


   def 			lowercase_      (self     :						Dict       ,  __UpperCAmelCase     :						Union[str, Any]		)						->				Dict:
         """simple docstring"""



         if ("a" <= char <= "z") or ("A" <= char <= "Z"):
               return True
         return False


   def 			lowercase_      (self     :						Union[str, Any]       ,  __UpperCAmelCase     :						str		)						->				Optional[int]:
         """simple docstring"""



         if char in ",;:.?!~，；：。？！《》【】":
               return True
         return False


   def 			lowercase_      (self     :						str       ,  __UpperCAmelCase     :						Union[str, Any]		)						->				Any:
         """simple docstring"""



         if char == " " or char == "\t" or char == "\n" or char == "\r":
               return True
         if len(__UpperCAmelCase		) == 1:
               UpperCAmelCase__								=  unicodedata.category(__UpperCAmelCase		)
               if cat == "Zs":
                     return True
         return False


   def 			lowercase_      (self     :						Union[str, Any]       ,  __UpperCAmelCase     :						Tuple		)						->				Optional[int]:
         """simple docstring"""



         UpperCAmelCase__								=  {}
         with io.open(__UpperCAmelCase       ,  "r"       ,  encoding="utf-8"		) as f:
               for index, line in enumerate(__UpperCAmelCase		):
                     UpperCAmelCase__								=  line.rstrip("\n"		)
                     UpperCAmelCase__								=  int(__UpperCAmelCase		)

         return token_to_idx





   def 			lowercase_      (self     :						Dict       ,  __UpperCAmelCase     :						str       ,  __UpperCAmelCase     :						Optional[str] = None		)						->				Tuple[str]:
         """simple docstring"""



         UpperCAmelCase__								=  0
         if os.path.isdir(__UpperCAmelCase		):
               UpperCAmelCase__								=  os.path.join(
                   __UpperCAmelCase       ,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
         else:
               UpperCAmelCase__								=  (filename_prefix + "-" if filename_prefix else "") + save_directory
         with open(__UpperCAmelCase       ,  "w"       ,  encoding="utf-8"		) as writer:
               for token, token_index in sorted(self.vocab.items()       ,  key=lambda __UpperCAmelCase		: kv[1]		):
                     if index != token_index:
                           logger.warning(
                               f"""Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."""
                               " Please check that the vocabulary is not corrupted!"		)
                           UpperCAmelCase__								=  token_index
                     writer.write(token + "\n"		)
                     index += 1

         UpperCAmelCase__								=  os.path.join(__UpperCAmelCase       ,  "sentencepiece.bpe.model"		)
         with open(__UpperCAmelCase       ,  "wb"		) as fi:
               UpperCAmelCase__								=  self.sp_model.serialized_model_proto()
               fi.write(__UpperCAmelCase		)

         return (vocab_file,)




import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase__											=					logging.get_logger(__name__)


UpperCamelCase__											=					{
    'vocab_file': 'vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
    'merges_file': 'merges.txt',
}

UpperCamelCase__											=					{
    'vocab_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json'
        ),
    },
    'tokenizer_config_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json'
        ),
    },
    'merges_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt'
        ),
    },
}

UpperCamelCase__											=					'</w>'
UpperCamelCase__											=					'@@ '




def    lowerCAmelCase_ (     __A							)     ->				str:







      '''simple docstring'''


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


# Speech2Text2 has no max input length
UpperCamelCase__											=					{'facebook/s2t-wav2vec2-large-en-de': 1_0_2_4}







class      A							(				UpperCAmelCase_     ):
   __UpperCAmelCase : str      =			VOCAB_FILES_NAMES
   __UpperCAmelCase : str      =			PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase : Union[str, Any]      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase : Dict      =			['input_ids', 'attention_mask']


   def __init__(self     :						Tuple       ,  __UpperCAmelCase     :						List[Any]       ,  __UpperCAmelCase     :						Dict="<s>"       ,  __UpperCAmelCase     :						Tuple="<pad>"       ,  __UpperCAmelCase     :						str="</s>"       ,  __UpperCAmelCase     :						int="<unk>"       ,  __UpperCAmelCase     :						List[str]=False       ,  __UpperCAmelCase     :						str=None       ,  **__UpperCAmelCase     :						Optional[Any]       ,  )						->				Tuple:
         """simple docstring"""



         super().__init__(
             unk_token=__UpperCAmelCase       ,  bos_token=__UpperCAmelCase       ,  eos_token=__UpperCAmelCase       ,  pad_token=__UpperCAmelCase       ,  do_lower_case=__UpperCAmelCase       ,  **__UpperCAmelCase       ,  )

         UpperCAmelCase__								=  do_lower_case

         with open(__UpperCAmelCase       ,  encoding="utf-8"		) as vocab_handle:
               UpperCAmelCase__								=  json.load(__UpperCAmelCase		)
         UpperCAmelCase__								=  {v: k for k, v in self.encoder.items()}

         if merges_file is None:
               logger.info(f"""No merges files provided. {self.__class__.__name__} can only be used for decoding."""		)

               UpperCAmelCase__								=  None
               UpperCAmelCase__								=  None
         else:
               with open(__UpperCAmelCase       ,  encoding="utf-8"		) as merges_handle:
                     UpperCAmelCase__								=  merges_handle.read().split("\n"		)[:-1]

               UpperCAmelCase__								=  [tuple(merge.split()[:2]		) for merge in merges]
               UpperCAmelCase__								=  dict(zip(__UpperCAmelCase       ,  range(len(__UpperCAmelCase		)		)		)		)
               UpperCAmelCase__								=  {}


   @property
   def 			lowercase_      (self     :						List[str]		)						->				int:
         """simple docstring"""



         return len(self.decoder		)


   def 			lowercase_      (self     :						Union[str, Any]		)						->				Dict:
         """simple docstring"""



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


   def 			lowercase_      (self     :						Dict       ,  __UpperCAmelCase     :						Union[str, Any]		)						->				str:
         """simple docstring"""



         UpperCAmelCase__								=  tuple(token[:-1]		) + (token[-1] + BPE_TOKEN_MERGES,)
         if token in self.cache:
               return self.cache[token]
         UpperCAmelCase__								=  get_pairs(__UpperCAmelCase		)

         if not pairs:
               return token

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

                     if word[i] == first and i < len(__UpperCAmelCase		) - 1 and word[i + 1] == second:
                           new_word.append(first + second		)
                           i += 2
                     else:
                           new_word.append(word[i]		)
                           i += 1
               UpperCAmelCase__								=  tuple(__UpperCAmelCase		)
               UpperCAmelCase__								=  new_word
               if len(__UpperCAmelCase		) == 1:
                     break
               else:
                     UpperCAmelCase__								=  get_pairs(__UpperCAmelCase		)
         UpperCAmelCase__								=  " ".join(__UpperCAmelCase		)
         if word == "\n  " + BPE_TOKEN_MERGES:
               UpperCAmelCase__								=  "\n" + BPE_TOKEN_MERGES

         if word.endswith(__UpperCAmelCase		):
               UpperCAmelCase__								=  word.replace(__UpperCAmelCase       ,  ""		)

         UpperCAmelCase__								=  word.replace(" "       ,  __UpperCAmelCase		)
         UpperCAmelCase__								=  word
         return word


   def 			lowercase_      (self     :						Tuple       ,  __UpperCAmelCase     :						int		)						->				Optional[int]:
         """simple docstring"""



         if self.bpe_ranks is None:
               raise ValueError(
                   "This tokenizer was instantiated without a `merges.txt` file, so"
                   " that it can only be used for decoding, not for encoding."
                   "Make sure to provide `merges.txt` file at instantiation to enable "
                   "encoding."		)

         if self.do_lower_case:
               UpperCAmelCase__								=  text.lower()

         UpperCAmelCase__								=  text.split()

         UpperCAmelCase__								=  []
         for token in text:
               if token:
                     split_tokens.extend(list(self.bpe(__UpperCAmelCase		).split(" "		)		)		)

         return split_tokens


   def 			lowercase_      (self     :						Union[str, Any]       ,  __UpperCAmelCase     :						str		)						->				int:
         """simple docstring"""



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


   def 			lowercase_      (self     :						Any       ,  __UpperCAmelCase     :						int		)						->				str:
         """simple docstring"""



         UpperCAmelCase__								=  self.decoder.get(__UpperCAmelCase       ,  self.unk_token		)
         return result


   def 			lowercase_      (self     :						Dict       ,  __UpperCAmelCase     :						List[str]		)						->				str:
         """simple docstring"""



         UpperCAmelCase__								=  " ".join(__UpperCAmelCase		)

         # make sure @@ tokens are concatenated
         UpperCAmelCase__								=  "".join(string.split(__UpperCAmelCase		)		)

         return string





   def 			lowercase_      (self     :						Union[str, Any]       ,  __UpperCAmelCase     :						str       ,  __UpperCAmelCase     :						Optional[str] = None		)						->				Tuple[str]:
         """simple docstring"""



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

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

         UpperCAmelCase__								=  0
         if self.bpe_ranks is None:
               return (vocab_file,)

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

         return (vocab_file, merges_file)



