"""simple docstring"""
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowercase__   			=      logging.get_logger(__name__)




class   __snake_case			(	__lowerCAmelCase							):
      a__								=						["""input_ids""", """attention_mask"""]



      def __init__(		self       ,     lowercase="[PAD]"       ,     lowercase="[BOS]"       ,     lowercase="[EOS]"       ,     lowercase="[MASK]"       ,     lowercase="[CLS]"       ,     lowercase="[SEP]"       ,     lowercase=20_48       ,     **lowercase       ,     )      ->     None:





        '''simple docstring'''





        a__:	Any     				=      AddedToken(lowercase       ,     lstrip=lowercase       ,     rstrip=lowercase) if isinstance(lowercase       ,     lowercase) else pad_token
        a__:	Tuple     				=      AddedToken(lowercase       ,     lstrip=lowercase       ,     rstrip=lowercase) if isinstance(lowercase       ,     lowercase) else bos_token
        a__:	Union[str, Any]     				=      AddedToken(lowercase       ,     lstrip=lowercase       ,     rstrip=lowercase) if isinstance(lowercase       ,     lowercase) else eos_token
        a__:	Tuple     				=      AddedToken(lowercase       ,     lstrip=lowercase       ,     rstrip=lowercase) if isinstance(lowercase       ,     lowercase) else mask_token
        a__:	int     				=      AddedToken(lowercase       ,     lstrip=lowercase       ,     rstrip=lowercase) if isinstance(lowercase       ,     lowercase) else cls_token
        a__:	Any     				=      AddedToken(lowercase       ,     lstrip=lowercase       ,     rstrip=lowercase) if isinstance(lowercase       ,     lowercase) else sep_token

        super().__init__(
            pad_token=lowercase       ,     bos_token=lowercase       ,     eos_token=lowercase       ,     mask_token=lowercase       ,     cls_token=lowercase       ,     sep_token=lowercase       ,     model_max_length=lowercase       ,     **lowercase       ,     )

        a__:	Optional[Any]     				=      2**8  # utf is 8 bits

        # define special tokens dict
        a__:	Dict[str, int]     				=      {
            self.pad_token: 0,
            self.bos_token: 1,
            self.eos_token: 2,
            self.mask_token: 3,
            self.cls_token: 4,
            self.sep_token: 5,
        }
        a__:	Union[str, Any]     				=      len(self.special_tokens_encoder)
        a__:	Dict[int, str]     				=      {v: k for k, v in self.special_tokens_encoder.items()}



      def     lowerCamelCase_  (		self)      ->     Dict[str, int]:





        '''simple docstring'''





        a__:	Optional[int]     				=      self.special_tokens_encoder.copy()
        vocab.update(self.added_tokens_encoder)
        for i in range(self._utf_vocab_size):
          a__:	Optional[int]     				=      chr(lowercase)
          a__:	str     				=      i + len(self.special_tokens_encoder)
        return vocab



      @property
      def     lowerCamelCase_  (		self)      ->     List[Any]:





        '''simple docstring'''





        return self._utf_vocab_size + self._num_special_tokens



      def     lowerCamelCase_  (		self       ,     lowercase       ,     lowercase = None       ,     lowercase = False)      ->     List[int]:





        '''simple docstring'''





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

        # normal case: some special tokens
        if token_ids_a is None:
          return [1] + [0] * len(lowercase) + [1]
        return [1] + ([0] * len(lowercase)) + [1] + ([0] * len(lowercase)) + [1]



      def     lowerCamelCase_  (		self       ,     lowercase       ,     lowercase = None)      ->     List[int]:





        '''simple docstring'''





        if token_ids_a is None:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        else:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]



      def     lowerCamelCase_  (		self       ,     lowercase)      ->     List[str]:





        '''simple docstring'''





        a__:	Any     				=      [chr(lowercase) for i in text.encode('utf-8')]
        return tokens



      def     lowerCamelCase_  (		self       ,     lowercase)      ->     Union[str, Any]:





        '''simple docstring'''





        if token in self.special_tokens_encoder:
          a__:	Optional[int]     				=      self.special_tokens_encoder[token]
        elif token in self.added_tokens_encoder:
          a__:	Optional[int]     				=      self.added_tokens_encoder[token]
        elif len(lowercase) != 1:
          a__:	Dict     				=      self.unk_token_id
        else:
          a__:	Optional[Any]     				=      ord(lowercase) + self._num_special_tokens
        return token_id



      def     lowerCamelCase_  (		self       ,     lowercase)      ->     Tuple:





        '''simple docstring'''





        if index in self.special_tokens_decoder:
          a__:	List[Any]     				=      self.special_tokens_decoder[index]
        elif index in self.added_tokens_decoder:
          a__:	Tuple     				=      self.added_tokens_decoder[index]
        else:
          a__:	List[str]     				=      chr(index - self._num_special_tokens)
        return token



      def     lowerCamelCase_  (		self       ,     lowercase)      ->     Optional[int]:





        '''simple docstring'''





        a__:	Any     				=      B''
        for token in tokens:
          if token in self.special_tokens_decoder:
            a__:	str     				=      self.special_tokens_decoder[token].encode('utf-8')
          elif token in self.added_tokens_decoder:
            a__:	Optional[Any]     				=      self.special_tokens_decoder[token].encode('utf-8')
          elif token in self.special_tokens_encoder:
            a__:	Optional[Any]     				=      token.encode('utf-8')
          elif token in self.added_tokens_encoder:
            a__:	str     				=      token.encode('utf-8')
          else:
            a__:	Tuple     				=      bytes([ord(lowercase)])
          bstring += tok_string
        a__:	List[str]     				=      bstring.decode('utf-8'       ,     errors='replace')
        return string



      def     lowerCamelCase_  (		self       ,     lowercase       ,     lowercase = None)      ->     Tuple[str]:





        '''simple docstring'''





        return ()





import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin







class 					__lowerCamelCase							(      __snake_case      ):
      lowerCamelCase_      : Dict  			=   'AutoFeatureExtractor'
      lowerCamelCase_      : Optional[int]  			=   'Speech2Text2Tokenizer'







      def __init__(	self				,    lowerCamelCase				,    lowerCamelCase  )		->			List[str]:
        super().__init__(lowerCamelCase				,    lowerCamelCase  )
        snake_case_					= self.feature_extractor
        snake_case_					= False







      def __call__(	self				,    *lowerCamelCase				,    **lowerCamelCase  )		->			Dict:
        # For backward compatibility
        if self._in_target_context_manager:
          return self.current_processor(*lowerCamelCase				,    **lowerCamelCase  )

        if "raw_speech" in kwargs:
          warnings.warn("""Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead."""  )
          snake_case_					= kwargs.pop("""raw_speech"""  )
        else:
          snake_case_					= kwargs.pop("""audio"""				,    lowerCamelCase  )
        snake_case_					= kwargs.pop("""sampling_rate"""				,    lowerCamelCase  )
        snake_case_					= kwargs.pop("""text"""				,    lowerCamelCase  )
        if len(lowerCamelCase  ) > 0:
          snake_case_					= args[0]
          snake_case_					= args[1:]

        if audio is None and text is None:
          raise ValueError("""You need to specify either an `audio` or `text` input to process."""  )

        if audio is not None:
          snake_case_					= self.feature_extractor(lowerCamelCase				,    *lowerCamelCase				,    sampling_rate=lowerCamelCase				,    **lowerCamelCase  )
        if text is not None:
          snake_case_					= self.tokenizer(lowerCamelCase				,    **lowerCamelCase  )

        if text is None:
          return inputs
        elif audio is None:
          return encodings
        else:
          snake_case_					= encodings["""input_ids"""]
          return inputs







      def       lowerCAmelCase_       (	self				,    *lowerCamelCase				,    **lowerCamelCase  )		->			int:
        return self.tokenizer.batch_decode(*lowerCamelCase				,    **lowerCamelCase  )







      def       lowerCAmelCase_       (	self				,    *lowerCamelCase				,    **lowerCamelCase  )		->			Union[str, Any]:
        return self.tokenizer.decode(*lowerCamelCase				,    **lowerCamelCase  )







      @contextmanager
      def       lowerCAmelCase_       (	self  )		->			Any:
        warnings.warn(
            """`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your """
            """labels by using the argument `text` of the regular `__call__` method (either in the same call as """
            """your audio inputs, or in a separate call."""  )
        snake_case_					= True
        snake_case_					= self.tokenizer
        yield
        snake_case_					= self.feature_extractor
        snake_case_					= False