from __future__ import annotations

from collections.abc import Iterator
from typing import Any







class __snake_case       :




   def __init__(					self    :       Union[str, Any] ,			_lowercase    :       Any   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   data
     SCREAMING_SNAKE_CASE__    							=   None







class __snake_case       :




   def __init__(					self    :       List[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   None
     SCREAMING_SNAKE_CASE__    							=   None




   def __iter__(					self    :       Tuple   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self.head
     while self.head:
       yield node.data
       SCREAMING_SNAKE_CASE__    							=   node.next
       if node == self.head:
         break




   def __len__(					self    :       int   ):



     """simple docstring"""






     return sum(1 for _ in self   )




   def __repr__(					self    :       Optional[int]   ):



     """simple docstring"""






     return "->".join(str(_lowercase   ) for item in iter(self   )   )




   def 			__a		(					self    :       Optional[int] ,			_lowercase    :       Any   ):



     """simple docstring"""






     self.insert_nth(len(self   ) ,			_lowercase   )




   def 			__a		(					self    :       Tuple ,			_lowercase    :       Any   ):



     """simple docstring"""






     self.insert_nth(0 ,			_lowercase   )




   def 			__a		(					self    :       Tuple ,			_lowercase    :       int ,			_lowercase    :       Any   ):



     """simple docstring"""






     if index < 0 or index > len(self   ):
       raise IndexError("""list index out of range."""   )
     SCREAMING_SNAKE_CASE__    							=   Node(_lowercase   )
     if self.head is None:
       SCREAMING_SNAKE_CASE__    							=   new_node  # first node points itself
       SCREAMING_SNAKE_CASE__    							=   SCREAMING_SNAKE_CASE__    							=   new_node
     elif index == 0:  # insert at head
       SCREAMING_SNAKE_CASE__    							=   self.head
       SCREAMING_SNAKE_CASE__    							=   SCREAMING_SNAKE_CASE__    							=   new_node
     else:
       SCREAMING_SNAKE_CASE__    							=   self.head
       for _ in range(index - 1   ):
         SCREAMING_SNAKE_CASE__    							=   temp.next
       SCREAMING_SNAKE_CASE__    							=   temp.next
       SCREAMING_SNAKE_CASE__    							=   new_node
       if index == len(self   ) - 1:  # insert at tail
         SCREAMING_SNAKE_CASE__    							=   new_node




   def 			__a		(					self    :       Dict   ):



     """simple docstring"""






     return self.delete_nth(0   )




   def 			__a		(					self    :       str   ):



     """simple docstring"""






     return self.delete_nth(len(self   ) - 1   )




   def 			__a		(					self    :       str ,			_lowercase    :       int = 0   ):



     """simple docstring"""






     if not 0 <= index < len(self   ):
       raise IndexError("""list index out of range."""   )
     SCREAMING_SNAKE_CASE__    							=   self.head
     if self.head == self.tail:  # just one node
       SCREAMING_SNAKE_CASE__    							=   SCREAMING_SNAKE_CASE__    							=   None
     elif index == 0:  # delete head node
       SCREAMING_SNAKE_CASE__    							=   self.tail.next.next
       SCREAMING_SNAKE_CASE__    							=   self.head.next
     else:
       SCREAMING_SNAKE_CASE__    							=   self.head
       for _ in range(index - 1   ):
         SCREAMING_SNAKE_CASE__    							=   temp.next
       SCREAMING_SNAKE_CASE__    							=   temp.next
       SCREAMING_SNAKE_CASE__    							=   temp.next.next
       if index == len(self   ) - 1:  # delete at tail
         SCREAMING_SNAKE_CASE__    							=   temp
     return delete_node.data




   def 			__a		(					self    :       Optional[int]   ):



     """simple docstring"""






     return len(self   ) == 0





def 			__SCREAMING_SNAKE_CASE						(      )							->      None:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__    							=   CircularLinkedList()
  assert len(__UpperCamelCase			) == 0
  assert circular_linked_list.is_empty() is True
  assert str(__UpperCamelCase			) == ""

  try:
    circular_linked_list.delete_front()
    raise AssertionError  # This should not happen
  except IndexError:
    assert True  # This should happen

  try:
    circular_linked_list.delete_tail()
    raise AssertionError  # This should not happen
  except IndexError:
    assert True  # This should happen

  try:
    circular_linked_list.delete_nth(-1			)
    raise AssertionError
  except IndexError:
    assert True

  try:
    circular_linked_list.delete_nth(0			)
    raise AssertionError
  except IndexError:
    assert True

  assert circular_linked_list.is_empty() is True
  for i in range(5			):
    assert len(__UpperCamelCase			) == i
    circular_linked_list.insert_nth(__UpperCamelCase				,  i + 1			)
  assert str(__UpperCamelCase			) == "->".join(str(__UpperCamelCase			) for i in range(1				,  6			)			)

  circular_linked_list.insert_tail(6			)
  assert str(__UpperCamelCase			) == "->".join(str(__UpperCamelCase			) for i in range(1				,  7			)			)
  circular_linked_list.insert_head(0			)
  assert str(__UpperCamelCase			) == "->".join(str(__UpperCamelCase			) for i in range(0				,  7			)			)

  assert circular_linked_list.delete_front() == 0
  assert circular_linked_list.delete_tail() == 6
  assert str(__UpperCamelCase			) == "->".join(str(__UpperCamelCase			) for i in range(1				,  6			)			)
  assert circular_linked_list.delete_nth(2			) == 3

  circular_linked_list.insert_nth(2				,  3			)
  assert str(__UpperCamelCase			) == "->".join(str(__UpperCamelCase			) for i in range(1				,  6			)			)

  assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
   import doctest

   doctest.testmod()

from typing import List, Optional

import numpy as np

from ...processing_utils import ProcessorMixin
from ...utils import to_numpy







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"EncodecFeatureExtractor"
   lowerCAmelCase_														=							("T5Tokenizer", "T5TokenizerFast")




   def __init__(					self    :       List[Any] ,			_lowercase    :       int ,			_lowercase    :       Any   ):



     """simple docstring"""






     super().__init__(_lowercase ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   self.feature_extractor
     SCREAMING_SNAKE_CASE__    							=   False




   def 			__a		(					self    :       Tuple ,			_lowercase    :       str=None ,			_lowercase    :       int=None ,			_lowercase    :       Any=True   ):



     """simple docstring"""






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




   def __call__(					self    :       Tuple ,			*_lowercase    :       Tuple ,			**_lowercase    :       Union[str, Any]   ):



     """simple docstring"""






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

     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""audio""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""sampling_rate""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""text""" ,			_lowercase   )
     if len(_lowercase   ) > 0:
       SCREAMING_SNAKE_CASE__    							=   args[0]
       SCREAMING_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 text is not None:
       SCREAMING_SNAKE_CASE__    							=   self.tokenizer(_lowercase ,			**_lowercase   )

     if audio is not None:
       SCREAMING_SNAKE_CASE__    							=   self.feature_extractor(_lowercase ,			*_lowercase ,			sampling_rate=_lowercase ,			**_lowercase   )

     if audio is None:
       return inputs

     elif text is None:
       return audio_inputs

     else:
       SCREAMING_SNAKE_CASE__    							=   audio_inputs["""input_values"""]
       if "padding_mask" in audio_inputs:
         SCREAMING_SNAKE_CASE__    							=   audio_inputs["""padding_mask"""]
       return inputs




   def 			__a		(					self    :       Dict ,			*_lowercase    :       Any ,			**_lowercase    :       Optional[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""audio""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""padding_mask""" ,			_lowercase   )

     if len(_lowercase   ) > 0:
       SCREAMING_SNAKE_CASE__    							=   args[0]
       SCREAMING_SNAKE_CASE__    							=   args[1:]

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




   def 			__a		(					self    :       List[str] ,			*_lowercase    :       Tuple ,			**_lowercase    :       Optional[Any]   ):



     """simple docstring"""






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




   def 			__a		(					self    :       List[str] ,			_lowercase    :       Tuple ,			_lowercase    :       Optional = None   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   to_numpy(_lowercase   )
     SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__    							=   audio_values.shape

     if padding_mask is None:
       return list(_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   to_numpy(_lowercase   )

     # 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)
     SCREAMING_SNAKE_CASE__    							=   seq_len - padding_mask.shape[-1]
     SCREAMING_SNAKE_CASE__    							=   1 - self.feature_extractor.padding_value
     SCREAMING_SNAKE_CASE__    							=   np.pad(_lowercase ,			((0, 0), (0, difference)) ,			"""constant""" ,			constant_values=_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   audio_values.tolist()
     for i in range(_lowercase   ):
       SCREAMING_SNAKE_CASE__    							=   np.asarray(audio_values[i]   )[
           padding_mask[i][None, :] != self.feature_extractor.padding_value
       ]
       SCREAMING_SNAKE_CASE__    							=   sliced_audio.reshape(_lowercase ,			-1   )

     return audio_values
