code: 
  
  
  """simple docstring"""
  
  
  
  
  import json
  import os
  import re
  import warnings
  from pathlib import Path
  from shutil import copyfile
  from typing import Any, Dict, List, Optional, Tuple, Union
  
  import sentencepiece
  
  from ...tokenization_utils import PreTrainedTokenizer
  from ...utils import logging
  
  
  __SCREAMING_SNAKE_CASE					=						logging.get_logger(__name__)
  
  __SCREAMING_SNAKE_CASE					=						{
      """source_spm""": """source.spm""",
      """target_spm""": """target.spm""",
      """vocab""": """vocab.json""",
      """target_vocab_file""": """target_vocab.json""",
      """tokenizer_config_file""": """tokenizer_config.json""",
  }
  
  __SCREAMING_SNAKE_CASE					=						{
      """source_spm""": {
          """Helsinki-NLP/opus-mt-en-de""": """https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/source.spm"""
      },
      """target_spm""": {
          """Helsinki-NLP/opus-mt-en-de""": """https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/target.spm"""
      },
      """vocab""": {
          """Helsinki-NLP/opus-mt-en-de""": """https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/vocab.json"""
      },
      """tokenizer_config_file""": {
          """Helsinki-NLP/opus-mt-en-de""": (
              """https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/tokenizer_config.json"""
          )
      },
  }
  
  __SCREAMING_SNAKE_CASE					=						{"""Helsinki-NLP/opus-mt-en-de""": 5_12}
  __SCREAMING_SNAKE_CASE					=						{}
  
  
  
  
  
  class __snake_case		(					_SCREAMING_SNAKE_CASE      ):
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
  
     lowerCAmelCase_				:   Tuple     	=			VOCAB_FILES_NAMES
     lowerCAmelCase_				:   Optional[Any]     	=			PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase_				:   Any     	=			PRETRAINED_INIT_CONFIGURATION
     lowerCAmelCase_				:   Any     	=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase_				:   Optional[Any]     	=			['input_ids', 'attention_mask']
     lowerCAmelCase_				:   Optional[Any]     	=			re.compile('>>.+<<'      )  # type: re.Pattern
  
  
  
  
     def __init__(		self							:Optional[int]				,  UpperCamelCase__							:List[Any]				,  UpperCamelCase__							:List[str]				,  UpperCamelCase__							:Tuple				,  UpperCamelCase__							:str=None				,  UpperCamelCase__							:Optional[Any]=None				,  UpperCamelCase__							:str=None				,  UpperCamelCase__							:Any="<unk>"				,  UpperCamelCase__							:List[str]="</s>"				,  UpperCamelCase__							:List[Any]="<pad>"				,  UpperCamelCase__							:Union[str, Any]=512				,  UpperCamelCase__							:Optional[Dict[str, Any]] = None				,  UpperCamelCase__							:str=False				,  **UpperCamelCase__							:Tuple				,  ):
            _a          =				{} if sp_model_kwargs is None else sp_model_kwargs
  
            super().__init__(
                # bos_token=bos_token,  unused. Start decoding with config.decoder_start_token_id
                source_lang=UpperCamelCase__				,  target_lang=UpperCamelCase__				,  unk_token=UpperCamelCase__				,  eos_token=UpperCamelCase__				,  pad_token=UpperCamelCase__				,  model_max_length=UpperCamelCase__				,  sp_model_kwargs=self.sp_model_kwargs				,  target_vocab_file=UpperCamelCase__				,  separate_vocabs=UpperCamelCase__				,  **UpperCamelCase__				,  )
            assert Path(UpperCamelCase__       ).exists(), f'cannot find spm source {source_spm}'
  
            _a          =				separate_vocabs
            _a          =				load_json(UpperCamelCase__       )
            if self.unk_token not in self.encoder:
                   raise KeyError("<unk> token must be in vocab"       )
            assert self.pad_token in self.encoder
  
            if separate_vocabs:
                   _a          =				load_json(UpperCamelCase__       )
                   _a          =				{v: k for k, v in self.target_encoder.items()}
                   _a          =				[]
            else:
                   _a          =				{v: k for k, v in self.encoder.items()}
                   _a          =				[k for k in self.encoder if k.startswith(">>"       ) and k.endswith("<<"       )]
  
            _a          =				source_lang
            _a          =				target_lang
            _a          =				[source_spm, target_spm]
  
            # load SentencePiece model for pre-processing
            _a          =				load_spm(UpperCamelCase__				,  self.sp_model_kwargs       )
            _a          =				load_spm(UpperCamelCase__				,  self.sp_model_kwargs       )
            _a          =				self.spm_source
            _a          =				self.encoder
  
            # Multilingual target side: default to using first supported language code.
  
            self._setup_normalizer()
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:str       ):
            try:
                   from sacremoses import MosesPunctNormalizer
  
                   _a          =				MosesPunctNormalizer(self.source_lang       ).normalize
            except (ImportError, FileNotFoundError):
                   warnings.warn("Recommended: pip install sacremoses."       )
                   _a          =				lambda UpperCamelCase__       : x
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Dict				,  UpperCamelCase__							:str       ):
            return self.punc_normalizer(UpperCamelCase__       ) if x else ""
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:List[Any]				,  UpperCamelCase__							:Optional[int]       ):
            return self.current_encoder.get(UpperCamelCase__				,  self.current_encoder[self.unk_token]       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Optional[Any]				,  UpperCamelCase__							:str       ):
            _a          =				self.language_code_re.match(UpperCamelCase__       )
            _a          =				[match.group(0       )] if match else []
            return code, self.language_code_re.sub(""				,  UpperCamelCase__       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:List[str]				,  UpperCamelCase__							:str       ):
            _a   , _a          =				self.remove_language_code(UpperCamelCase__       )
            _a          =				self.current_spm.encode(UpperCamelCase__				,  out_type=UpperCamelCase__       )
            return code + pieces
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Any				,  UpperCamelCase__							:int       ):
            return self.decoder.get(UpperCamelCase__				,  self.unk_token       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Optional[Any]				,  UpperCamelCase__							:int				,  **UpperCamelCase__							:Tuple       ):
            return super().batch_decode(UpperCamelCase__				,  **UpperCamelCase__       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Optional[Any]				,  UpperCamelCase__							:List[Any]				,  **UpperCamelCase__							:Dict       ):
            return super().decode(UpperCamelCase__				,  **UpperCamelCase__       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Any				,  UpperCamelCase__							:List[str]       ):
            _a          =				self.spm_source if self._decode_use_source_tokenizer else self.spm_target
            _a          =				[]
            _a          =				""
            for token in tokens:
                   # make sure that special tokens are not decoded using sentencepiece model
                   if token in self.all_special_tokens:
                          out_string += sp_model.decode_pieces(UpperCamelCase__       ) + token + " "
                          _a          =				[]
                   else:
                          current_sub_tokens.append(UpperCamelCase__       )
            out_string += sp_model.decode_pieces(UpperCamelCase__       )
            return out_string.strip()
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Any				,  UpperCamelCase__							:Dict				,  UpperCamelCase__							:List[Any]=None       ):
            if token_ids_a is None:
                   return token_ids_a + [self.eos_token_id]
            # We don't expect to process pairs, but leave the pair logic for API consistency
            return token_ids_a + token_ids_a + [self.eos_token_id]
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Dict       ):
            _a          =				self.spm_source
            _a          =				self.encoder
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Dict       ):
            _a          =				self.spm_target
            if self.separate_vocabs:
                   _a          =				self.target_encoder
  
  
  
  
     @property
     def SCREAMING_SNAKE_CASE_      (		self							:Any       ):
            return len(self.encoder       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Tuple				,  UpperCamelCase__							:str				,  UpperCamelCase__							:Optional[str] = None       ):
            if not os.path.isdir(UpperCamelCase__       ):
                   logger.error(f'Vocabulary path ({save_directory}) should be a directory'       )
                   return
            _a          =				[]
  
            if self.separate_vocabs:
                   _a          =				os.path.join(
                       UpperCamelCase__				,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab"]				,  )
                   _a          =				os.path.join(
                       UpperCamelCase__				,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["target_vocab_file"]				,  )
                   save_json(self.encoder				,  UpperCamelCase__       )
                   save_json(self.target_encoder				,  UpperCamelCase__       )
                   saved_files.append(UpperCamelCase__       )
                   saved_files.append(UpperCamelCase__       )
            else:
                   _a          =				os.path.join(
                       UpperCamelCase__				,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab"]       )
                   save_json(self.encoder				,  UpperCamelCase__       )
                   saved_files.append(UpperCamelCase__       )
  
            for spm_save_filename, spm_orig_path, spm_model in zip(
                [VOCAB_FILES_NAMES["source_spm"], VOCAB_FILES_NAMES["target_spm"]]				,  self.spm_files				,  [self.spm_source, self.spm_target]				,  ):
                   _a          =				os.path.join(
                       UpperCamelCase__				,  (filename_prefix + "-" if filename_prefix else "") + spm_save_filename       )
                   if os.path.abspath(UpperCamelCase__       ) != os.path.abspath(UpperCamelCase__       ) and os.path.isfile(UpperCamelCase__       ):
                          copyfile(UpperCamelCase__				,  UpperCamelCase__       )
                          saved_files.append(UpperCamelCase__       )
                   elif not os.path.isfile(UpperCamelCase__       ):
                          with open(UpperCamelCase__				,  "wb"       ) as fi:
                                 _a          =				spm_model.serialized_model_proto()
                                 fi.write(UpperCamelCase__       )
                          saved_files.append(UpperCamelCase__       )
  
            return tuple(UpperCamelCase__       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Optional[Any]       ):
            return self.get_src_vocab()
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:List[Any]       ):
            return dict(self.encoder				,  **self.added_tokens_encoder       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:int       ):
            return dict(self.target_encoder				,  **self.added_tokens_decoder       )
  
  
  
  
     def __getstate__(		self							:Union[str, Any]       ):
            _a          =				self.__dict__.copy()
            state.update(
                {k: None for k in ["spm_source", "spm_target", "current_spm", "punc_normalizer", "target_vocab_file"]}       )
            return state
  
  
  
  
     def __setstate__(		self							:List[str]				,  UpperCamelCase__							:Dict       ):
            _a          =				d
  
            # for backward compatibility
            if not hasattr(self				,  "sp_model_kwargs"       ):
                   _a          =				{}
  
            _a   , _a          =				(load_spm(UpperCamelCase__				,  self.sp_model_kwargs       ) for f in self.spm_files)
            _a          =				self.spm_source
            self._setup_normalizer()
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:List[Any]				,  *UpperCamelCase__							:List[Any]				,  **UpperCamelCase__							:List[Any]       ):
            return 1
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:List[Any]				,  UpperCamelCase__							:List[str]       ):
            _a          =				set(self.all_special_ids       )  # call it once instead of inside list comp
            all_special_ids.remove(self.unk_token_id       )  # <unk> is only sometimes special
            return [1 if x in all_special_ids else 0 for x in seq]
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:str				,  UpperCamelCase__							:List				,  UpperCamelCase__							:Optional[List] = None				,  UpperCamelCase__							:bool = False       ):
            if already_has_special_tokens:
                   return self._special_token_mask(UpperCamelCase__       )
            elif token_ids_a is None:
                   return self._special_token_mask(UpperCamelCase__       ) + [1]
            else:
                   return self._special_token_mask(token_ids_a + token_ids_a       ) + [1]
  
  
  
  
  
  
  def 						__a      (  a,		a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         _a          =				sentencepiece.SentencePieceProcessor(**a					)
         spm.Load(a					)
         return spm
  
  
  
  def 						__a      (  a,		a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         with open(a,		"w"					) as f:
                json.dump(a,		a,		indent=2					)
  
  
  
  def 						__a      (  a					):
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         with open(a,		"r"					) as f:
                return json.load(a					)
  
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  from __future__ import annotations
  
  from collections.abc import Iterator
  from typing import Any
  
  
  
  
  
  class __snake_case		:
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
  
     def __init__(		self							:List[Any]				,  UpperCamelCase__							:Any       ):
            _a          =				data
            _a          =				None
  
  
  
  
     def __str__(		self							:Any       ):
            return f'{self.data}'
  
  
  
  
  
  
  class __snake_case		:
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
  
     def __init__(		self							:Any       ):
            _a          =				None
            _a          =				None
  
  
  
  
     def __iter__(		self							:List[str]       ):
            _a          =				self.front
            while node:
                   yield node.data
                   _a          =				node.next
  
  
  
  
     def __len__(		self							:List[str]       ):
            return len(tuple(iter(self       )       )       )
  
  
  
  
     def __str__(		self							:Union[str, Any]       ):
            return " <- ".join(str(UpperCamelCase__       ) for item in self       )
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Any       ):
            return len(self       ) == 0
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:List[str]				,  UpperCamelCase__							:Any       ):
            _a          =				Node(UpperCamelCase__       )
            if self.is_empty():
                   _a          =				_a          =				node
            else:
                   assert isinstance(self.rear				,  UpperCamelCase__       )
                   _a          =				node
                   _a          =				node
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:Tuple       ):
            if self.is_empty():
                   raise IndexError("dequeue from empty queue"       )
            assert isinstance(self.front				,  UpperCamelCase__       )
            _a          =				self.front
            _a          =				self.front.next
            if self.front is None:
                   _a          =				None
            return node.data
  
  
  
  
     def SCREAMING_SNAKE_CASE_      (		self							:int       ):
            _a          =				_a          =				None
  
  
  if __name__ == "__main__":
     from doctest import testmod
  
     testmod()
  