from ...processing_utils import ProcessorMixin







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"SpeechT5FeatureExtractor"
   lowerCAmelCase_														=							"SpeechT5Tokenizer"




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



     """simple docstring"""






     super().__init__(_lowercase ,			_lowercase   )




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



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""audio""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""text""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""text_target""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""audio_target""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""sampling_rate""" ,			_lowercase   )

     if audio is not None and text is not None:
       raise ValueError(
           """Cannot process both `audio` and `text` inputs. Did you mean `audio_target` or `text_target`?"""   )
     if audio_target is not None and text_target is not None:
       raise ValueError(
           """Cannot process both `audio_target` and `text_target` inputs. Did you mean `audio` or `text`?"""   )
     if audio is None and audio_target is None and text is None and text_target is None:
       raise ValueError(
           """You need to specify either an `audio`, `audio_target`, `text`, or `text_target` input to process."""   )

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

     if audio_target is not None:
       SCREAMING_SNAKE_CASE__    							=   self.feature_extractor(audio_target=_lowercase ,			*_lowercase ,			sampling_rate=_lowercase ,			**_lowercase   )
       SCREAMING_SNAKE_CASE__    							=   targets["""input_values"""]
     elif text_target is not None:
       SCREAMING_SNAKE_CASE__    							=   self.tokenizer(_lowercase ,			**_lowercase   )
       SCREAMING_SNAKE_CASE__    							=   targets["""input_ids"""]
     else:
       SCREAMING_SNAKE_CASE__    							=   None

     if inputs is None:
       return targets

     if targets is not None:
       SCREAMING_SNAKE_CASE__    							=   labels

       SCREAMING_SNAKE_CASE__    							=   targets.get("""attention_mask"""   )
       if decoder_attention_mask is not None:
         SCREAMING_SNAKE_CASE__    							=   decoder_attention_mask

     return inputs




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



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""input_values""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""input_ids""" ,			_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   kwargs.pop("""labels""" ,			_lowercase   )

     if input_values is not None and input_ids is not None:
       raise ValueError("""Cannot process both `input_values` and `input_ids` inputs."""   )
     if input_values is None and input_ids is None and labels is None:
       raise ValueError(
           """You need to specify either an `input_values`, `input_ids`, or `labels` input to be padded."""   )

     if input_values is not None:
       SCREAMING_SNAKE_CASE__    							=   self.feature_extractor.pad(_lowercase ,			*_lowercase ,			**_lowercase   )
     elif input_ids is not None:
       SCREAMING_SNAKE_CASE__    							=   self.tokenizer.pad(_lowercase ,			**_lowercase   )
     else:
       SCREAMING_SNAKE_CASE__    							=   None

     if labels is not None:
       if "input_ids" in labels or (isinstance(_lowercase ,			_lowercase   ) and "input_ids" in labels[0]):
         SCREAMING_SNAKE_CASE__    							=   self.tokenizer.pad(_lowercase ,			**_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   targets["""input_ids"""]
       else:
         SCREAMING_SNAKE_CASE__    							=   self.feature_extractor.feature_size
         SCREAMING_SNAKE_CASE__    							=   self.feature_extractor.num_mel_bins
         SCREAMING_SNAKE_CASE__    							=   self.feature_extractor.pad(_lowercase ,			*_lowercase ,			**_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   feature_size_hack
         SCREAMING_SNAKE_CASE__    							=   targets["""input_values"""]
     else:
       SCREAMING_SNAKE_CASE__    							=   None

     if inputs is None:
       return targets

     if targets is not None:
       SCREAMING_SNAKE_CASE__    							=   labels

       SCREAMING_SNAKE_CASE__    							=   targets.get("""attention_mask"""   )
       if decoder_attention_mask is not None:
         SCREAMING_SNAKE_CASE__    							=   decoder_attention_mask

     return inputs




   def 			__a		(					self    :       int ,			*_lowercase    :       Dict ,			**_lowercase    :       Union[str, Any]   ):



     """simple docstring"""






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




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



     """simple docstring"""






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

from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

__lowerCamelCase    :				List[str]							     =	TypeVar('''KEY''')
__lowerCamelCase    :				int							     =	TypeVar('''VAL''')







@dataclass(frozen=lowerCamelCase_     ,	slots=lowerCamelCase_	)
class __snake_case       (		Generic[KEY, VAL]	):
   lowerCAmelCase_														=							42
   lowerCAmelCase_														=							42







class __snake_case       (		_Item	):




   def __init__(					self    :       List[Any]   ):



     """simple docstring"""






     super().__init__(_lowercase ,			_lowercase   )




   def __bool__(					self    :       List[str]   ):



     """simple docstring"""






     return False





__lowerCamelCase    :				str							     =	_DeletedItem()







class __snake_case       (		MutableMapping[KEY, VAL]	):




   def __init__(					self    :       Optional[int] ,			_lowercase    :       int = 8 ,			_lowercase    :       float = 0.75   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   initial_block_size
     SCREAMING_SNAKE_CASE__    							=   [None] * initial_block_size
     assert 0.0 < capacity_factor < 1.0
     SCREAMING_SNAKE_CASE__    							=   capacity_factor
     SCREAMING_SNAKE_CASE__    							=   0




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



     """simple docstring"""






     return hash(_lowercase   ) % len(self._buckets   )




   def 			__a		(					self    :       List[str] ,			_lowercase    :       int   ):



     """simple docstring"""






     return (ind + 1) % len(self._buckets   )




   def 			__a		(					self    :       Union[str, Any] ,			_lowercase    :       int ,			_lowercase    :       KEY ,			_lowercase    :       VAL   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self._buckets[ind]
     if not stored:
       SCREAMING_SNAKE_CASE__    							=   _Item(_lowercase ,			_lowercase   )
       self._len += 1
       return True
     elif stored.key == key:
       SCREAMING_SNAKE_CASE__    							=   _Item(_lowercase ,			_lowercase   )
       return True
     else:
       return False




   def 			__a		(					self    :       List[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   len(self._buckets   ) * self._capacity_factor
     return len(self   ) >= int(_lowercase   )




   def 			__a		(					self    :       Dict   ):



     """simple docstring"""






     if len(self._buckets   ) <= self._initial_block_size:
       return False
     SCREAMING_SNAKE_CASE__    							=   len(self._buckets   ) * self._capacity_factor / 2
     return len(self   ) < limit




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



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self._buckets
     SCREAMING_SNAKE_CASE__    							=   [None] * new_size
     SCREAMING_SNAKE_CASE__    							=   0
     for item in old_buckets:
       if item:
         self._add_item(item.key ,			item.val   )




   def 			__a		(					self    :       Tuple   ):



     """simple docstring"""






     self._resize(len(self._buckets   ) * 2   )




   def 			__a		(					self    :       Tuple   ):



     """simple docstring"""






     self._resize(len(self._buckets   ) // 2   )




   def 			__a		(					self    :       List[str] ,			_lowercase    :       KEY   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   self._get_bucket_index(_lowercase   )
     for _ in range(len(self._buckets   )   ):
       yield ind
       SCREAMING_SNAKE_CASE__    							=   self._get_next_ind(_lowercase   )




   def 			__a		(					self    :       List[str] ,			_lowercase    :       KEY ,			_lowercase    :       VAL   ):



     """simple docstring"""






     for ind in self._iterate_buckets(_lowercase   ):
       if self._try_set(_lowercase ,			_lowercase ,			_lowercase   ):
         break




   def __setitem__(					self    :       List[str] ,			_lowercase    :       KEY ,			_lowercase    :       VAL   ):



     """simple docstring"""






     if self._is_full():
       self._size_up()

     self._add_item(_lowercase ,			_lowercase   )




   def __delitem__(					self    :       Tuple ,			_lowercase    :       KEY   ):



     """simple docstring"""






     for ind in self._iterate_buckets(_lowercase   ):
       SCREAMING_SNAKE_CASE__    							=   self._buckets[ind]
       if item is None:
         raise KeyError(_lowercase   )
       if item is _deleted:
         continue
       if item.key == key:
         SCREAMING_SNAKE_CASE__    							=   _deleted
         self._len -= 1
         break
     if self._is_sparse():
       self._size_down()




   def __getitem__(					self    :       Tuple ,			_lowercase    :       KEY   ):



     """simple docstring"""






     for ind in self._iterate_buckets(_lowercase   ):
       SCREAMING_SNAKE_CASE__    							=   self._buckets[ind]
       if item is None:
         break
       if item is _deleted:
         continue
       if item.key == key:
         return item.val
     raise KeyError(_lowercase   )




   def __len__(					self    :       List[Any]   ):



     """simple docstring"""






     return self._len




   def __iter__(					self    :       List[str]   ):



     """simple docstring"""






     yield from (item.key for item in self._buckets if item)




   def __repr__(					self    :       Optional[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   """ ,""".join(
         f"""{item.key}: {item.val}""" for item in self._buckets if item   )
     return f"""HashMap({val_string})"""
