




from typing import List, Optional

import numpy as np

from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class 						_A (  _lowerCamelCase				):
  _UpperCamelCase       :      Union[str, Any]			=      '''EncodecFeatureExtractor'''
  _UpperCamelCase       :      Optional[Any]			=      ('''T5Tokenizer''', '''T5TokenizerFast''')






  def __init__(  self		:     List[str]				,						_A		:     Optional[int]				,						_A		:     int				)		->   Union[str, Any]:






       """simple docstring"""







       super().__init__(_A				,						_A				)
       lowercase :       List[Any]       =			self.feature_extractor
       lowercase :       Optional[int]       =			False






  def  __a      (  self		:     List[Any]				,						_A		:     List[Any]=None				,						_A		:     Tuple=None				,						_A		:     Any=True				)		->   Any:






       """simple docstring"""







       return self.tokenizer.get_decoder_prompt_ids(task=_A				,						language=_A				,						no_timestamps=_A				)






  def __call__(  self		:     Tuple				,						*_A		:     Optional[int]				,						**_A		:     Any				)		->   int:






       """simple docstring"""







       if self._in_target_context_manager:
            return self.current_processor(*_A				,						**_A				)

       lowercase :       Union[str, Any]       =			kwargs.pop('''audio'''				,						_A				)
       lowercase :       List[str]       =			kwargs.pop('''sampling_rate'''				,						_A				)
       lowercase :       List[Any]       =			kwargs.pop('''text'''				,						_A				)
       if len(_A				) > 0:
            lowercase :       Dict       =			args[0]
            lowercase :       int       =			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 text is not None:
            lowercase :       str       =			self.tokenizer(_A				,						**_A				)

       if audio is not None:
            lowercase :       List[str]       =			self.feature_extractor(_A				,						*_A				,						sampling_rate=_A				,						**_A				)

       if audio is None:
            return inputs

       elif text is None:
            return audio_inputs

       else:
            lowercase :       Tuple       =			audio_inputs['''input_values''']
            if "padding_mask" in audio_inputs:
                 lowercase :       int       =			audio_inputs['''padding_mask''']
            return inputs






  def  __a      (  self		:     Optional[Any]				,						*_A		:     List[Any]				,						**_A		:     Tuple				)		->   int:






       """simple docstring"""







       lowercase :       Optional[Any]       =			kwargs.pop('''audio'''				,						_A				)
       lowercase :       int       =			kwargs.pop('''padding_mask'''				,						_A				)

       if len(_A				) > 0:
            lowercase :       int       =			args[0]
            lowercase :       List[Any]       =			args[1:]

       if audio_values is not None:
            return self._decode_audio(_A				,						padding_mask=_A				)
       else:
            return self.tokenizer.batch_decode(*_A				,						**_A				)






  def  __a      (  self		:     Tuple				,						*_A		:     Dict				,						**_A		:     List[str]				)		->   str:






       """simple docstring"""







       return self.tokenizer.decode(*_A				,						**_A				)






  def  __a      (  self		:     Dict				,						_A		:     str				,						_A		:     Optional = None				)		->   List[np.ndarray]:






       """simple docstring"""







       lowercase :       Tuple       =			to_numpy(_A				)
       lowercase      ,	lowercase      ,	lowercase :       Dict       =			audio_values.shape

       if padding_mask is None:
            return list(_A				)

       lowercase :       List[str]       =			to_numpy(_A				)

       # match the sequence length of the padding mask to the generated audio arrays by padding with the **non-padding**
       # token (so that the generated audio values are **not** treated as padded tokens)
       lowercase :       Dict       =			seq_len - padding_mask.shape[-1]
       lowercase :       Dict       =			1 - self.feature_extractor.padding_value
       lowercase :       Union[str, Any]       =			np.pad(_A				,						((0, 0), (0, difference))				,						'''constant'''				,						constant_values=_A				)

       lowercase :       Union[str, Any]       =			audio_values.tolist()
       for i in range(_A				):
            lowercase :       List[str]       =			np.asarray(audio_values[i]				)[
                padding_mask[i][None, :] != self.feature_extractor.padding_value
            ]
            lowercase :       Optional[Any]       =			sliced_audio.reshape(_A				,						-1				)

       return audio_values





lowerCAmelCase_						=			range(2, 20 + 1)
lowerCAmelCase_						=			[10**k for k in range(ks[-1] + 1)]
lowerCAmelCase_						=			{}






def  snake_case(    __magic_name__			,		__magic_name__			,		__magic_name__			,		__magic_name__   )			->							Any:





     '''simple docstring'''


     lowercase :       str       =			sum(a_i[j] for j in range(__magic_name__			,		len(__magic_name__   )   )   )
     lowercase :       Any       =			sum(a_i[j] * base[j] for j in range(min(len(__magic_name__   )			,		__magic_name__   )   )   )

     lowercase      ,	lowercase :       Optional[int]       =			0, 0
     lowercase :       str       =			n - i

     lowercase :       Optional[int]       =			memo.get(__magic_name__   )

     if sub_memo is not None:
          lowercase :       List[str]       =			sub_memo.get(__magic_name__   )

          if jumps is not None and len(__magic_name__   ) > 0:
               # find and make the largest jump without going over
               lowercase :       Dict       =			-1
               for _k in range(len(__magic_name__   ) - 1			,		-1			,		-1   ):
                    if jumps[_k][2] <= k and jumps[_k][1] <= max_dn:
                         lowercase :       Any       =			_k
                         break

               if max_jump >= 0:
                    lowercase      ,	lowercase      ,	lowercase :       List[str]       =			jumps[max_jump]
                    # since the difference between jumps is cached, add c
                    lowercase :       str       =			diff + c
                    for j in range(min(__magic_name__			,		len(__magic_name__   )   )   ):
                         lowercase      ,	lowercase :       Optional[Any]       =			divmod(__magic_name__			,		10   )
                    if new_c > 0:
                         add(__magic_name__			,		__magic_name__			,		__magic_name__   )

          else:
               lowercase :       Dict       =			[]
     else:
          lowercase :       Union[str, Any]       =			{c: []}
          lowercase :       Optional[Any]       =			sub_memo

     if dn >= max_dn or c + diff >= base[k]:
          return diff, dn

     if k > ks[0]:
          while True:
               # keep doing smaller jumps
               lowercase      ,	lowercase :       str       =			next_term(__magic_name__			,		k - 1			,		i + dn			,		__magic_name__   )
               diff += _diff
               dn += terms_jumped

               if dn >= max_dn or c + diff >= base[k]:
                    break
     else:
          # would be too small a jump, just compute sequential terms instead
          lowercase      ,	lowercase :       Optional[Any]       =			compute(__magic_name__			,		__magic_name__			,		i + dn			,		__magic_name__   )
          diff += _diff
          dn += terms_jumped

     lowercase :       Optional[Any]       =			sub_memo[c]

     # keep jumps sorted by # of terms skipped
     lowercase :       List[Any]       =			0
     while j < len(__magic_name__   ):
          if jumps[j][1] > dn:
               break
          j += 1

     # cache the jump for this value digitsum(b) and c
     sub_memo[c].insert(__magic_name__			,		(diff, dn, k)   )
     return (diff, dn)






def  snake_case(    __magic_name__			,		__magic_name__			,		__magic_name__			,		__magic_name__   )			->							Optional[int]:





     '''simple docstring'''


     if i >= n:
          return 0, i
     if k > len(__magic_name__   ):
          a_i.extend([0 for _ in range(k - len(__magic_name__   )   )]   )

     # note: a_i -> b * 10^k + c
     # ds_b -> digitsum(b)
     # ds_c -> digitsum(c)
     lowercase :       Optional[Any]       =			i
     lowercase      ,	lowercase      ,	lowercase :       List[str]       =			0, 0, 0
     for j in range(len(__magic_name__   )   ):
          if j >= k:
               ds_b += a_i[j]
          else:
               ds_c += a_i[j]

     while i < n:
          i += 1
          lowercase :       List[str]       =			ds_c + ds_b
          diff += addend
          lowercase :       Tuple       =			0
          for j in range(__magic_name__   ):
               lowercase :       int       =			a_i[j] + addend
               lowercase      ,	lowercase :       Any       =			divmod(__magic_name__			,		10   )

               ds_c += a_i[j]

          if addend > 0:
               break

     if addend > 0:
          add(__magic_name__			,		__magic_name__			,		__magic_name__   )
     return diff, i - start_i






def  snake_case(    __magic_name__			,		__magic_name__			,		__magic_name__   )			->							Tuple:





     '''simple docstring'''


     for j in range(__magic_name__			,		len(__magic_name__   )   ):
          lowercase :       Any       =			digits[j] + addend
          if s >= 10:
               lowercase      ,	lowercase :       List[str]       =			divmod(__magic_name__			,		10   )
               lowercase :       List[str]       =			addend // 10 + quotient
          else:
               lowercase :       Optional[Any]       =			s
               lowercase :       Tuple       =			addend // 10

          if addend == 0:
               break

     while addend > 0:
          lowercase      ,	lowercase :       str       =			divmod(__magic_name__			,		10   )
          digits.append(__magic_name__   )






def  snake_case(    __magic_name__ = 10**15   )			->							int:





     '''simple docstring'''


     lowercase :       List[Any]       =			[1]
     lowercase :       List[Any]       =			1
     lowercase :       str       =			0
     while True:
          lowercase      ,	lowercase :       str       =			next_term(__magic_name__			,		20			,		i + dn			,		__magic_name__   )
          dn += terms_jumped
          if dn == n - i:
               break

     lowercase :       str       =			0
     for j in range(len(__magic_name__   )   ):
          a_n += digits[j] * 10**j
     return a_n


if __name__ == "__main__":
 print(f'''{solution() = }''')