
'''simple docstring'''
import json
import os
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


A__   :		int 		=logging.get_logger(__name__)

A__   :		Optional[Any] 		='▁'

A__   :		List[str] 		={
    'vocab_file': 'vocab.json',
    'spm_file': 'sentencepiece.bpe.model',
}

A__   :		int 		={
    'vocab_file': {
        'facebook/s2t-small-librispeech-asr': (
            'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/vocab.json'
        ),
    },
    'spm_file': {
        'facebook/s2t-small-librispeech-asr': (
            'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/sentencepiece.bpe.model'
        )
    },
}

A__   :		Optional[int] 		={
    'facebook/s2t-small-librispeech-asr': 1_024,
}

A__   :		Any 		=['pt', 'fr', 'ru', 'nl', 'ro', 'it', 'es', 'de']

A__   :		Tuple 		={'mustc': MUSTC_LANGS}







class  __A				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       =VOCAB_FILES_NAMES
 lowerCamelCase				       =PRETRAINED_VOCAB_FILES_MAP
 lowerCamelCase				       =MAX_MODEL_INPUT_SIZES
 lowerCamelCase				       =['''input_ids''', '''attention_mask''']

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



   """simple docstring"""





   __A		:     Any												=		{} if sp_model_kwargs is None else sp_model_kwargs

   super().__init__(
       bos_token=lowerCamelCase				,   eos_token=lowerCamelCase				,   unk_token=lowerCamelCase				,   pad_token=lowerCamelCase				,   do_upper_case=lowerCamelCase				,   do_lower_case=lowerCamelCase				,   tgt_lang=lowerCamelCase				,   lang_codes=lowerCamelCase				,   sp_model_kwargs=self.sp_model_kwargs				,   **lowerCamelCase				,   )
   __A		:     int												=		do_upper_case
   __A		:     Any												=		do_lower_case

   __A		:     List[str]												=		load_json(lowerCamelCase       )
   __A		:     int												=		{v: k for k, v in self.encoder.items()}
   __A		:     Optional[Any]												=		spm_file
   __A		:     str												=		load_spm(lowerCamelCase				,   self.sp_model_kwargs       )

   if lang_codes is not None:
     __A		:     int												=		lang_codes
     __A		:     Tuple												=		LANGUAGES[lang_codes]
     __A		:     int												=		[f"<lang:{lang}>" for lang in self.langs]
     __A		:     int												=		{lang: self.sp_model.PieceToId(f"<lang:{lang}>"       ) for lang in self.langs}

     __A		:     Dict												=		self.lang_tokens
     __A		:     Union[str, Any]												=		tgt_lang if tgt_lang is not None else self.langs[0]

     self.set_tgt_lang_special_tokens(self._tgt_lang       )
   else:
     __A		:     Optional[int]												=		{}
 @property
 def 		lowercase_(   self			:    Any       ):



   """simple docstring"""





   return len(self.encoder       )
 @property
 def 		lowercase_(   self			:    List[str]       ):



   """simple docstring"""





   return self._tgt_lang
 @tgt_lang.setter
 def 		lowercase_(   self			:    List[str]				,   lowerCamelCase			:    Any       ):



   """simple docstring"""





   __A		:     Any												=		new_tgt_lang
   self.set_tgt_lang_special_tokens(lowerCamelCase       )
 def 		lowercase_(   self			:    str				,   lowerCamelCase			:    str       ):



   """simple docstring"""





   __A		:     Optional[int]												=		self.lang_code_to_id[tgt_lang]
   __A		:     Any												=		[lang_code_id]
 def 		lowercase_(   self			:    List[str]				,   lowerCamelCase			:    str       ):



   """simple docstring"""





   return self.sp_model.encode(lowerCamelCase				,   out_type=lowerCamelCase       )
 def 		lowercase_(   self			:    Tuple				,   lowerCamelCase			:    Any       ):



   """simple docstring"""





   return self.encoder.get(lowerCamelCase				,   self.encoder[self.unk_token]       )
 def 		lowercase_(   self			:    List[str]				,   lowerCamelCase			:    int       ):



   """simple docstring"""





   return self.decoder.get(lowerCamelCase				,   self.unk_token       )
 def 		lowercase_(   self			:    Optional[int]				,   lowerCamelCase			:    List[str]       ):



   """simple docstring"""





   __A		:     Optional[int]												=		[]
   __A		:     Tuple												=		""""""
   for token in tokens:
     # make sure that special tokens are not decoded using sentencepiece model
     if token in self.all_special_tokens:
       __A		:     str												=		self.sp_model.decode(lowerCamelCase       )
       out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
       __A		:     Any												=		[]
     else:
       current_sub_tokens.append(lowerCamelCase       )
   __A		:     int												=		self.sp_model.decode(lowerCamelCase       )
   out_string += decoded.upper() if self.do_upper_case else decoded
   return out_string.strip()
 def 		lowercase_(   self			:    int				,   lowerCamelCase			:    Union[str, Any]				,   lowerCamelCase			:    Union[str, Any]=None       ):



   """simple docstring"""





   if token_ids_a is None:
     return self.prefix_tokens + token_ids_a + [self.eos_token_id]
   # We don't expect to process pairs, but leave the pair logic for API consistency
   return self.prefix_tokens + token_ids_a + token_ids_a + [self.eos_token_id]
 def 		lowercase_(   self			:    Optional[int]				,   lowerCamelCase			:    List[int]				,   lowerCamelCase			:    Optional[List[int]] = None				,   lowerCamelCase			:    bool = 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       )

   __A		:     int												=		[1] * len(self.prefix_tokens       )
   __A		:     Optional[Any]												=		[1]
   if token_ids_a is None:
     return prefix_ones + ([0] * len(lowerCamelCase       )) + suffix_ones
   return prefix_ones + ([0] * len(lowerCamelCase       )) + ([0] * len(lowerCamelCase       )) + suffix_ones
 def 		lowercase_(   self			:    Optional[int]       ):



   """simple docstring"""





   __A		:     List[Any]												=		self.encoder.copy()
   vocab.update(self.added_tokens_encoder       )
   return vocab
 def __getstate__(   self			:    Optional[int]       ):



   """simple docstring"""





   __A		:     Optional[Any]												=		self.__dict__.copy()
   __A		:     List[Any]												=		None
   return state
 def __setstate__(   self			:    List[str]				,   lowerCamelCase			:    Dict       ):



   """simple docstring"""





   __A		:     Dict												=		d

   # for backward compatibility
   if not hasattr(self				,   """sp_model_kwargs"""       ):
     __A		:     List[str]												=		{}

   __A		:     List[Any]												=		load_spm(self.spm_file				,   self.sp_model_kwargs       )






 def 		lowercase_(   self			:    Dict				,   lowerCamelCase			:    str				,   lowerCamelCase			:    Optional[str] = None       ):



   """simple docstring"""





   __A		:     Dict												=		Path(lowerCamelCase       )
   assert save_dir.is_dir(), f"{save_directory} should be a directory"
   __A		:     Dict												=		save_dir / (
       (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""vocab_file"""]
   )
   __A		:     Union[str, Any]												=		save_dir / (
       (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""spm_file"""]
   )

   save_json(self.encoder				,   lowerCamelCase       )

   if os.path.abspath(self.spm_file       ) != os.path.abspath(lowerCamelCase       ) and os.path.isfile(self.spm_file       ):
     copyfile(self.spm_file				,   lowerCamelCase       )
   elif not os.path.isfile(self.spm_file       ):
     with open(lowerCamelCase				,   """wb"""       ) as fi:
       __A		:     List[str]												=		self.sp_model.serialized_model_proto()
       fi.write(lowerCamelCase       )

   return (str(lowerCamelCase       ), str(lowerCamelCase       ))







def        A_     (						__SCREAMING_SNAKE_CASE						:  str			,     __SCREAMING_SNAKE_CASE						:  Dict[str, Any] )				->       sentencepiece.SentencePieceProcessor:





  """simple docstring"""

  __A		:     Optional[int]												=		sentencepiece.SentencePieceProcessor(**__SCREAMING_SNAKE_CASE )
  spm.Load(str(__SCREAMING_SNAKE_CASE ) )
  return spm







def        A_     (						__SCREAMING_SNAKE_CASE						:  str )				->       Union[Dict, List]:





  """simple docstring"""

  with open(__SCREAMING_SNAKE_CASE			,     """r""" ) as f:
    return json.load(__SCREAMING_SNAKE_CASE )







def        A_     (						__SCREAMING_SNAKE_CASE						:  Dict			,     __SCREAMING_SNAKE_CASE						:  str )				->       None:





  """simple docstring"""

  with open(__SCREAMING_SNAKE_CASE			,     """w""" ) as f:
    json.dump(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     indent=2 )

'''simple docstring'''
A__   :		List[Any] 		=[
    'Audio',
    'Array2D',
    'Array3D',
    'Array4D',
    'Array5D',
    'ClassLabel',
    'Features',
    'Sequence',
    'Value',
    'Image',
    'Translation',
    'TranslationVariableLanguages',
]
from .audio import Audio
from .features import ArrayaD, ArrayaD, ArrayaD, ArrayaD, ClassLabel, Features, Sequence, Value
from .image import Image
from .translation import Translation, TranslationVariableLanguages



