





'''simple docstring'''







from ...processing_utils import ProcessorMixin
class 			_lowercase						(       a__					):
     _UpperCAmelCase										=					"SpeechT5FeatureExtractor"
     _UpperCAmelCase										=					"SpeechT5Tokenizer"







     def __init__( self    ,   A__    ,   A__    ) ->	Optional[Any]:
      super().__init__(lowerCamelCase_    ,   lowerCamelCase_    )







     def __call__( self    ,   *A__    ,   **A__    ) ->	Dict:
      snake_case				=			kwargs.pop('''audio'''    ,   lowerCamelCase_    )
      snake_case				=			kwargs.pop('''text'''    ,   lowerCamelCase_    )
      snake_case				=			kwargs.pop('''text_target'''    ,   lowerCamelCase_    )
      snake_case				=			kwargs.pop('''audio_target'''    ,   lowerCamelCase_    )
      snake_case				=			kwargs.pop('''sampling_rate'''    ,   lowerCamelCase_    )

      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:
       snake_case				=			self.feature_extractor(lowerCamelCase_    ,   *lowerCamelCase_    ,   sampling_rate=lowerCamelCase_    ,   **lowerCamelCase_    )
      elif text is not None:
       snake_case				=			self.tokenizer(lowerCamelCase_    ,   **lowerCamelCase_    )
      else:
       snake_case				=			None

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

      if inputs is None:
       return targets

      if targets is not None:
       snake_case				=			labels

       snake_case				=			targets.get('''attention_mask'''    )
       if decoder_attention_mask is not None:
        snake_case				=			decoder_attention_mask

      return inputs







     def     UpperCamelCase			( self    ,   *A__    ,   **A__    ) ->	Union[str, Any]:
      snake_case				=			kwargs.pop('''input_values'''    ,   lowerCamelCase_    )
      snake_case				=			kwargs.pop('''input_ids'''    ,   lowerCamelCase_    )
      snake_case				=			kwargs.pop('''labels'''    ,   lowerCamelCase_    )

      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:
       snake_case				=			self.feature_extractor.pad(lowerCamelCase_    ,   *lowerCamelCase_    ,   **lowerCamelCase_    )
      elif input_ids is not None:
       snake_case				=			self.tokenizer.pad(lowerCamelCase_    ,   **lowerCamelCase_    )
      else:
       snake_case				=			None

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

      if inputs is None:
       return targets

      if targets is not None:
       snake_case				=			labels

       snake_case				=			targets.get('''attention_mask'''    )
       if decoder_attention_mask is not None:
        snake_case				=			decoder_attention_mask

      return inputs







     def     UpperCamelCase			( self    ,   *A__    ,   **A__    ) ->	Dict:
      return self.tokenizer.batch_decode(*lowerCamelCase_    ,   **lowerCamelCase_    )







     def     UpperCamelCase			( self    ,   *A__    ,   **A__    ) ->	Union[str, Any]:
      return self.tokenizer.decode(*lowerCamelCase_    ,   **lowerCamelCase_    )








'''simple docstring'''







def    __UpperCamelCase	(	a    : int					,   a    : int     ) ->int:
 while b:
  snake_case				,		snake_case				=			b, a % b
 return a

def    __UpperCamelCase	(	a    : int					,   a    : int     ) ->int:
 return a if b == 0 else euclidean_gcd_recursive(a					,   a % b     )

def    __UpperCamelCase	(	) ->Optional[Any]:
 print(f"""euclidean_gcd(3, 5) = {euclidean_gcd(3					,   5     )}"""     )
 print(f"""euclidean_gcd(5, 3) = {euclidean_gcd(5					,   3     )}"""     )
 print(f"""euclidean_gcd(1, 3) = {euclidean_gcd(1					,   3     )}"""     )
 print(f"""euclidean_gcd(3, 6) = {euclidean_gcd(3					,   6     )}"""     )
 print(f"""euclidean_gcd(6, 3) = {euclidean_gcd(6					,   3     )}"""     )

 print(f"""euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3					,   5     )}"""     )
 print(f"""euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5					,   3     )}"""     )
 print(f"""euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1					,   3     )}"""     )
 print(f"""euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3					,   6     )}"""     )
 print(f"""euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6					,   3     )}"""     )


if __name__ == "__main__":
   main()

