

"""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


SCREAMING_SNAKE_CASE_					:	Union[str, Any]							  =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_					:	Any							  =						'▁'

SCREAMING_SNAKE_CASE_					:	Dict							  =						{
    'vocab_file': 'vocab.json',
    'spm_file': 'sentencepiece.bpe.model',
}

SCREAMING_SNAKE_CASE_					:	str							  =						{
    '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'
        )
    },
}

SCREAMING_SNAKE_CASE_					:	List[Any]							  =						{
    'facebook/s2t-small-librispeech-asr': 1_0_2_4,
}

SCREAMING_SNAKE_CASE_					:	Tuple							  =						['pt', 'fr', 'ru', 'nl', 'ro', 'it', 'es', 'de']

SCREAMING_SNAKE_CASE_					:	str							  =						{'mustc': MUSTC_LANGS}



class 					a						(       _lowerCamelCase				):



    """simple docstring"""



    UpperCAmelCase						 =					VOCAB_FILES_NAMES
    UpperCAmelCase						 =					PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase						 =					MAX_MODEL_INPUT_SIZES
    UpperCAmelCase						 =					["input_ids", "attention_mask"]

    UpperCAmelCase						 =					[]

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






         """simple docstring"""


         A__										=  {} if sp_model_kwargs is None else sp_model_kwargs

         super().__init__(
             bos_token=UpperCamelCase    ,						eos_token=UpperCamelCase    ,						unk_token=UpperCamelCase    ,						pad_token=UpperCamelCase    ,						do_upper_case=UpperCamelCase    ,						do_lower_case=UpperCamelCase    ,						tgt_lang=UpperCamelCase    ,						lang_codes=UpperCamelCase    ,						sp_model_kwargs=self.sp_model_kwargs    ,						**UpperCamelCase    ,						)
         A__										=  do_upper_case
         A__										=  do_lower_case

         A__										=  load_json(UpperCamelCase       )
         A__										=  {v: k for k, v in self.encoder.items()}
         A__										=  spm_file
         A__										=  load_spm(UpperCamelCase    ,						self.sp_model_kwargs       )

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

              A__										=  self.lang_tokens
              A__										=  tgt_lang if tgt_lang is not None else self.langs[0]

              self.set_tgt_lang_special_tokens(self._tgt_lang       )
         else:
              A__										=  {}

    @property
    def 				UpperCamelCase	(     self: Union[str, Any]       ):






         """simple docstring"""


         return len(self.encoder       )

    @property
    def 				UpperCamelCase	(     self: Dict       ):






         """simple docstring"""


         return self._tgt_lang

    @tgt_lang.setter
    def 				UpperCamelCase	(     self: Any    ,						UpperCamelCase: List[str]       ):






         """simple docstring"""


         A__										=  new_tgt_lang
         self.set_tgt_lang_special_tokens(UpperCamelCase       )

    def 				UpperCamelCase	(     self: int    ,						UpperCamelCase: str       ):






         """simple docstring"""


         A__										=  self.lang_code_to_id[tgt_lang]
         A__										=  [lang_code_id]

    def 				UpperCamelCase	(     self: Dict    ,						UpperCamelCase: str       ):






         """simple docstring"""


         return self.sp_model.encode(UpperCamelCase    ,						out_type=UpperCamelCase       )

    def 				UpperCamelCase	(     self: Dict    ,						UpperCamelCase: Dict       ):






         """simple docstring"""


         return self.encoder.get(UpperCamelCase    ,						self.encoder[self.unk_token]       )

    def 				UpperCamelCase	(     self: Optional[Any]    ,						UpperCamelCase: int       ):






         """simple docstring"""


         return self.decoder.get(UpperCamelCase    ,						self.unk_token       )

    def 				UpperCamelCase	(     self: str    ,						UpperCamelCase: List[str]       ):






         """simple docstring"""


         A__										=  []
         A__										=  """"""
         for token in tokens:
              # make sure that special tokens are not decoded using sentencepiece model
              if token in self.all_special_tokens:
                   A__										=  self.sp_model.decode(UpperCamelCase       )
                   out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
                   A__										=  []
              else:
                   current_sub_tokens.append(UpperCamelCase       )
         A__										=  self.sp_model.decode(UpperCamelCase       )
         out_string += decoded.upper() if self.do_upper_case else decoded
         return out_string.strip()

    def 				UpperCamelCase	(     self: Union[str, Any]    ,						UpperCamelCase: List[Any]    ,						UpperCamelCase: int=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 				UpperCamelCase	(     self: List[Any]    ,						UpperCamelCase: List[int]    ,						UpperCamelCase: Optional[List[int]] = None    ,						UpperCamelCase: bool = False       ):






         """simple docstring"""


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

         A__										=  [1] * len(self.prefix_tokens       )
         A__										=  [1]
         if token_ids_a is None:
              return prefix_ones + ([0] * len(UpperCamelCase       )) + suffix_ones
         return prefix_ones + ([0] * len(UpperCamelCase       )) + ([0] * len(UpperCamelCase       )) + suffix_ones

    def 				UpperCamelCase	(     self: str       ):






         """simple docstring"""


         A__										=  self.encoder.copy()
         vocab.update(self.added_tokens_encoder       )
         return vocab

    def __getstate__(     self: str       ):






         """simple docstring"""


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

    def __setstate__(     self: Any    ,						UpperCamelCase: Dict       ):






         """simple docstring"""


         A__										=  d

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

         A__										=  load_spm(self.spm_file    ,						self.sp_model_kwargs       )





    def 				UpperCamelCase	(     self: Optional[int]    ,						UpperCamelCase: str    ,						UpperCamelCase: Optional[str] = None       ):






         """simple docstring"""


         A__										=  Path(UpperCamelCase       )
         assert save_dir.is_dir(), f"""{save_directory} should be a directory"""
         A__										=  save_dir / (
             (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""vocab_file"""]
         )
         A__										=  save_dir / (
             (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""spm_file"""]
         )

         save_json(self.encoder    ,						UpperCamelCase       )

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

         return (str(UpperCamelCase       ), str(UpperCamelCase       ))





def  _snake_case     (    UpperCAmelCase_  :					str					,   UpperCAmelCase_  :					Dict[str, Any]			):
     A__										=  sentencepiece.SentencePieceProcessor(**UpperCAmelCase_			)
     spm.Load(str(UpperCAmelCase_			)			)
     return spm





def  _snake_case     (    UpperCAmelCase_  :					str			):
     with open(UpperCAmelCase_					,   """r"""			) as f:
          return json.load(UpperCAmelCase_			)





def  _snake_case     (    UpperCAmelCase_  :					Optional[Any]					,   UpperCAmelCase_  :					str			):
     with open(UpperCAmelCase_					,   """w"""			) as f:
          json.dump(UpperCAmelCase_					,   UpperCAmelCase_					,   indent=2			)









"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE_					:	Any							  =						{
    'configuration_jukebox': [
        'JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'JukeboxConfig',
        'JukeboxPriorConfig',
        'JukeboxVQVAEConfig',
    ],
    'tokenization_jukebox': ['JukeboxTokenizer'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_					:	Union[str, Any]							  =						[
     'JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST',
     'JukeboxModel',
     'JukeboxPreTrainedModel',
     'JukeboxVQVAE',
     'JukeboxPrior',
 ]

if TYPE_CHECKING:
 from .configuration_jukebox import (
     JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP,
     JukeboxConfig,
     JukeboxPriorConfig,
     JukeboxVQVAEConfig,
 )
 from .tokenization_jukebox import JukeboxTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_jukebox import (
      JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST,
      JukeboxModel,
      JukeboxPreTrainedModel,
      JukeboxPrior,
      JukeboxVQVAE,
  )

else:
 import sys

 SCREAMING_SNAKE_CASE_					:	Optional[int]							  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






