code: 
  
  
  """simple docstring"""
  import json
  import os
  from typing import List, Optional, Tuple
  
  from ...tokenization_utils import PreTrainedTokenizer
  from ...utils import logging
  
  
  UpperCAmelCase   =	logging.get_logger(__name__)
  
  UpperCAmelCase   =	{
      """vocab_file""": """vocab.json""",
      """merges_file""": """merges.txt""",
  }
  
  UpperCAmelCase   =	{
      """vocab_file""": {
          """microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json""",
      },
      """merges_file""": {"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt"""},
  }
  
  UpperCAmelCase   =	{
      """microsoft/biogpt""": 1024,
  }
  
  def 							_snake_case			(      __snake_case       :			int      ):
  
  
  
  
   """simple docstring"""
  
  
  
  
  
  
  
   _lowerCamelCase  :				Tuple      =		set()
   _lowerCamelCase  :				Any      =		word[0]
   for char in word[1:]:
    pairs.add((prev_char, char)      )
    _lowerCamelCase  :				Union[str, Any]      =		char
   return pairs
  
  
  
  
  
  class   lowercase__							(				_a							):
     __UpperCAmelCase       					=				VOCAB_FILES_NAMES
     __UpperCAmelCase       					=				PRETRAINED_VOCAB_FILES_MAP
     __UpperCAmelCase       					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __UpperCAmelCase       					=				['''input_ids''', '''attention_mask''']
  
  
  
  
  
     def __init__(       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE="<unk>"			,      SCREAMING_SNAKE_CASE="<s>"			,      SCREAMING_SNAKE_CASE="</s>"			,      SCREAMING_SNAKE_CASE="</s>"			,      SCREAMING_SNAKE_CASE="<pad>"			,      **SCREAMING_SNAKE_CASE			,      )     ->     Tuple:
      super().__init__(
          bos_token=lowerCamelCase__			,      eos_token=lowerCamelCase__			,      sep_token=lowerCamelCase__			,      unk_token=lowerCamelCase__			,      pad_token=lowerCamelCase__			,      **lowerCamelCase__			,      )
  
      try:
       import sacremoses
      except ImportError:
       raise ImportError(
           """You need to install sacremoses to use BioGptTokenizer. """
           """See https://pypi.org/project/sacremoses/ for installation.""")
  
      _lowerCamelCase  :				List[str]      =		"en"
      _lowerCamelCase  :				str      =		sacremoses
      # cache of sm.MosesTokenizer instance
      _lowerCamelCase  :				int      =		{}
      _lowerCamelCase  :				Optional[int]      =		{}
      with open(lowerCamelCase__			,      encoding="""utf-8""") as vocab_handle:
       _lowerCamelCase  :				Tuple      =		json.load(lowerCamelCase__)
      _lowerCamelCase  :				Union[str, Any]      =		{v: k for k, v in self.encoder.items()}
      with open(lowerCamelCase__			,      encoding="""utf-8""") as merges_handle:
       _lowerCamelCase  :				Union[str, Any]      =		merges_handle.read().split("""\n""")[:-1]
      _lowerCamelCase  :				Optional[Any]      =		[tuple(merge.split()[:2]) for merge in merges]
      _lowerCamelCase  :				Tuple      =		dict(zip(lowerCamelCase__			,      range(len(lowerCamelCase__))))
      _lowerCamelCase  :				str      =		{}
  
  
  
  
  
     @property
     def 		UpperCamelCase_     (       self)     ->     List[str]:
      return len(self.encoder)
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     List[Any]:
      return dict(self.encoder			,      **self.added_tokens_encoder)
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)     ->     str:
      if lang not in self.cache_moses_tokenizer:
       _lowerCamelCase  :				Any      =		self.sm.MosesTokenizer(lang=lowerCamelCase__)
       _lowerCamelCase  :				Union[str, Any]      =		moses_tokenizer
      return self.cache_moses_tokenizer[lang].tokenize(
          lowerCamelCase__			,      aggressive_dash_splits=lowerCamelCase__			,      return_str=lowerCamelCase__			,      escape=lowerCamelCase__)
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)     ->     str:
      if lang not in self.cache_moses_detokenizer:
       _lowerCamelCase  :				str      =		self.sm.MosesDetokenizer(lang=lowerCamelCase__)
       _lowerCamelCase  :				List[Any]      =		moses_detokenizer
      return self.cache_moses_detokenizer[lang].detokenize(lowerCamelCase__)
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     Tuple:
      _lowerCamelCase  :				Optional[Any]      =		tuple(token[:-1]) + (token[-1] + "</w>",)
      if token in self.cache:
       return self.cache[token]
      _lowerCamelCase  :				Optional[Any]      =		get_pairs(lowerCamelCase__)
  
      if not pairs:
       return token + "</w>"
  
      while True:
       _lowerCamelCase  :				Union[str, Any]      =		min(lowerCamelCase__			,      key=lambda SCREAMING_SNAKE_CASE: self.bpe_ranks.get(lowerCamelCase__			,      float("""inf""")))
       if bigram not in self.bpe_ranks:
        break
       _lowerCamelCase  :				Optional[int]      =		bigram
       _lowerCamelCase  :				Optional[Any]      =		[]
       _lowerCamelCase  :				List[str]      =		0
       while i < len(lowerCamelCase__):
        try:
         _lowerCamelCase  :				int      =		word.index(lowerCamelCase__			,      lowerCamelCase__)
        except ValueError:
         new_word.extend(word[i:])
         break
        else:
         new_word.extend(word[i:j])
         _lowerCamelCase  :				int      =		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  :				Any      =		tuple(lowerCamelCase__)
       _lowerCamelCase  :				Any      =		new_word
       if len(lowerCamelCase__) == 1:
        break
       else:
        _lowerCamelCase  :				Any      =		get_pairs(lowerCamelCase__)
      _lowerCamelCase  :				Tuple      =		" ".join(lowerCamelCase__)
      if word == "\n  </w>":
       _lowerCamelCase  :				Tuple      =		"\n</w>"
      _lowerCamelCase  :				Optional[int]      =		word
      return word
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE=False)     ->     Tuple:
      if bypass_tokenizer:
       _lowerCamelCase  :				List[str]      =		text.split()
      else:
       _lowerCamelCase  :				int      =		self.moses_tokenize(lowerCamelCase__			,      self.lang)
  
      _lowerCamelCase  :				str      =		[]
      for token in text:
       if token:
        split_tokens.extend(list(self.bpe(lowerCamelCase__).split(""" """)))
  
      return split_tokens
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     int:
      return self.encoder.get(lowerCamelCase__			,      self.encoder.get(self.unk_token))
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     List[Any]:
      return self.decoder.get(lowerCamelCase__			,      self.unk_token)
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     Optional[int]:
      _lowerCamelCase  :				Optional[Any]      =		[t.replace(""" """			,      """""").replace("""</w>"""			,      """ """) for t in tokens]
      _lowerCamelCase  :				Any      =		"".join(lowerCamelCase__).split()
      # detokenize
      _lowerCamelCase  :				Any      =		self.moses_detokenize(lowerCamelCase__			,      self.lang)
      return text
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE = None)     ->     str:
      if token_ids_a is None:
       return [self.sep_token_id] + token_ids_a
      _lowerCamelCase  :				str      =		[self.sep_token_id]
      return sep + token_ids_a + sep + token_ids_a
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE = None			,      SCREAMING_SNAKE_CASE = False)     ->     str:
      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=lowerCamelCase__			,      token_ids_a=lowerCamelCase__			,      already_has_special_tokens=lowerCamelCase__)
      # no bos used in fairseq
      if token_ids_a is not None:
       return [1] + ([0] * len(lowerCamelCase__)) + [1] + ([0] * len(lowerCamelCase__))
      return [1] + ([0] * len(lowerCamelCase__))
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE = None)     ->     Optional[Any]:
      _lowerCamelCase  :				List[str]      =		[self.sep_token_id]
  
      # no bos used in fairseq
      if token_ids_a is None:
       return len(token_ids_a + sep) * [0]
      return len(token_ids_a + sep) * [0] + len(token_ids_a + sep) * [1]
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE = None)     ->     Any:
      if not os.path.isdir(lowerCamelCase__):
       logger.error(F'Vocabulary path ({save_directory}) should be a directory')
       return
      _lowerCamelCase  :				Optional[int]      =		os.path.join(
          lowerCamelCase__			,      (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""])
      _lowerCamelCase  :				Union[str, Any]      =		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  :				Union[str, Any]      =		0
      with open(lowerCamelCase__			,      """w"""			,      encoding="""utf-8""") as writer:
       for bpe_tokens, token_index in sorted(self.bpe_ranks.items()			,      key=lambda SCREAMING_SNAKE_CASE: 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  :				Optional[Any]      =		token_index
        writer.write(""" """.join(lowerCamelCase__) + """\n""")
        index += 1
  
      return vocab_file, merge_file
  
  
  
  
  
     def __getstate__(       self)     ->     Any:
      _lowerCamelCase  :				List[str]      =		self.__dict__.copy()
      _lowerCamelCase  :				Union[str, Any]      =		None
      return state
  
  
  
  
  
     def __setstate__(       self			,      SCREAMING_SNAKE_CASE)     ->     int:
      _lowerCamelCase  :				List[str]      =		d
  
      try:
       import sacremoses
      except ImportError:
       raise ImportError(
           """You need to install sacremoses to use XLMTokenizer. """
           """See https://pypi.org/project/sacremoses/ for installation.""")
  
      _lowerCamelCase  :				List[str]      =		sacremoses
  
  
style_context: 
  
  
  """simple docstring"""
  from typing import List, Optional, Tuple
  
  from tokenizers import pre_tokenizers
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_clip import CLIPTokenizer
  
  
  UpperCAmelCase   =	logging.get_logger(__name__)
  
  UpperCAmelCase   =	{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}
  
  UpperCAmelCase   =	{
      """vocab_file""": {
          """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json""",
      },
      """merges_file""": {
          """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt""",
      },
      """tokenizer_file""": {
          """openai/clip-vit-base-patch32""": (
              """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json"""
          ),
      },
  }
  
  UpperCAmelCase   =	{
      """openai/clip-vit-base-patch32""": 77,
  }
  
  
  
  
  class   lowercase__							(				A_							):
     __UpperCAmelCase       					=				VOCAB_FILES_NAMES
     __UpperCAmelCase       					=				PRETRAINED_VOCAB_FILES_MAP
     __UpperCAmelCase       					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __UpperCAmelCase       					=				['''input_ids''', '''attention_mask''']
     __UpperCAmelCase       					=				CLIPTokenizer
  
  
  
  
  
     def __init__(       self			,      SCREAMING_SNAKE_CASE=None			,      SCREAMING_SNAKE_CASE=None			,      SCREAMING_SNAKE_CASE=None			,      SCREAMING_SNAKE_CASE="<|endoftext|>"			,      SCREAMING_SNAKE_CASE="<|startoftext|>"			,      SCREAMING_SNAKE_CASE="<|endoftext|>"			,      SCREAMING_SNAKE_CASE="<|endoftext|>"			,      **SCREAMING_SNAKE_CASE			,      )     ->     List[Any]:
        super().__init__(
            SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      tokenizer_file=SCREAMING_SNAKE_CASE			,      unk_token=SCREAMING_SNAKE_CASE			,      bos_token=SCREAMING_SNAKE_CASE			,      eos_token=SCREAMING_SNAKE_CASE			,      pad_token=SCREAMING_SNAKE_CASE			,      **SCREAMING_SNAKE_CASE			,      )
  
        if not isinstance(self.backend_tokenizer.pre_tokenizer			,      pre_tokenizers.Sequence):
           raise ValueError(
               """The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been"""
               """ heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using"""
               """ to be compatible with this version.The easiest way to do so is"""
               """ `CLIPTokenizerFast.from_pretrained(\"path_to_local_folder_or_hub_repo, from_slow=True)`. If you want"""
               """ to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of"""
               """ transformers.""")
  
        self._wrap_decode_method_backend_tokenizer()
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Union[str, Any]:
        _lowerCamelCase  :				str      =		self.backend_tokenizer.decode
  
        def new_decode_method(*SCREAMING_SNAKE_CASE			,      **SCREAMING_SNAKE_CASE):
           _lowerCamelCase  :				Any      =		orig_decode_method(*SCREAMING_SNAKE_CASE			,      **SCREAMING_SNAKE_CASE)
           _lowerCamelCase  :				Optional[int]      =		text.replace(self.backend_tokenizer.model.end_of_word_suffix			,      """ """).strip()
           return text
  
        _lowerCamelCase  :				List[str]      =		new_decode_method
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE = None)     ->     List[int]:
        _lowerCamelCase  :				str      =		[self.bos_token_id]
        _lowerCamelCase  :				Union[str, Any]      =		[self.eos_token_id]
  
        if token_ids_a is None:
           return bos_token + token_ids_a + eos_token
        return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE = None)     ->     List[int]:
        _lowerCamelCase  :				Any      =		[self.bos_token_id]
        _lowerCamelCase  :				int      =		[self.eos_token_id]
  
        if token_ids_a is None:
           return len(bos_token + token_ids_a + eos_token) * [0]
        return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token) * [0]
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE = None)     ->     Tuple[str]:
        _lowerCamelCase  :				Dict      =		self._tokenizer.model.save(SCREAMING_SNAKE_CASE			,      name=SCREAMING_SNAKE_CASE)
        return tuple(SCREAMING_SNAKE_CASE)
  
  