






"""simple docstring"""







from ...processing_utils import ProcessorMixin





class   UpperCamelCase_ (       a_  ):
  _A       :					Union[str, Any]				=	'SpeechT5FeatureExtractor'
  _A       :					Any				=	'SpeechT5Tokenizer'



  def __init__(      self ,		snake_case__ ,		snake_case__				)			->			Dict:



         """simple docstring"""





         super().__init__(snake_case__ ,		snake_case__				)



  def __call__(      self ,		*snake_case__ ,		**snake_case__				)			->			Dict:



         """simple docstring"""





         UpperCAmelCase	    =			kwargs.pop("""audio""" ,		snake_case__				)
         UpperCAmelCase	    =			kwargs.pop("""text""" ,		snake_case__				)
         UpperCAmelCase	    =			kwargs.pop("""text_target""" ,		snake_case__				)
         UpperCAmelCase	    =			kwargs.pop("""audio_target""" ,		snake_case__				)
         UpperCAmelCase	    =			kwargs.pop("""sampling_rate""" ,		snake_case__				)

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

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

         if inputs is None:
                return targets

         if targets is not None:
                UpperCAmelCase	    =			labels

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

         return inputs



  def 		UpperCamelCase_				(      self ,		*snake_case__ ,		**snake_case__				)			->			Dict:



         """simple docstring"""





         UpperCAmelCase	    =			kwargs.pop("""input_values""" ,		snake_case__				)
         UpperCAmelCase	    =			kwargs.pop("""input_ids""" ,		snake_case__				)
         UpperCAmelCase	    =			kwargs.pop("""labels""" ,		snake_case__				)

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

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

         if inputs is None:
                return targets

         if targets is not None:
                UpperCAmelCase	    =			labels

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

         return inputs



  def 		UpperCamelCase_				(      self ,		*snake_case__ ,		**snake_case__				)			->			Tuple:



         """simple docstring"""





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



  def 		UpperCamelCase_				(      self ,		*snake_case__ ,		**snake_case__				)			->			List[Any]:



         """simple docstring"""





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








"""simple docstring"""







def       _lowerCAmelCase       (      lowerCAmelCase		):







       '''simple docstring'''
       UpperCAmelCase	    =			0
       UpperCAmelCase	    =			len(lowerCAmelCase		)

       for i in range(n - 1		):
              for j in range(i + 1	,      lowerCAmelCase		):
                     if arr[i] > arr[j]:
                            num_inversions += 1

       return num_inversions






def       _lowerCAmelCase       (      lowerCAmelCase		):







       '''simple docstring'''
       if len(lowerCAmelCase		) <= 1:
              return arr, 0
       UpperCAmelCase	    =			len(lowerCAmelCase		) // 2
       UpperCAmelCase	    =			arr[0:mid]
       UpperCAmelCase	    =			arr[mid:]

       UpperCAmelCase    ,       UpperCAmelCase	    =			count_inversions_recursive(lowerCAmelCase		)
       UpperCAmelCase    ,       UpperCAmelCase	    =			count_inversions_recursive(lowerCAmelCase		)
       UpperCAmelCase    ,       UpperCAmelCase	    =			_count_cross_inversions(lowerCAmelCase	,      lowerCAmelCase		)

       UpperCAmelCase	    =			inversion_p + inversions_q + cross_inversions
       return c, num_inversions






def       _lowerCAmelCase       (      lowerCAmelCase	,      lowerCAmelCase		):







       '''simple docstring'''
       UpperCAmelCase	    =			[]
       UpperCAmelCase	    =			UpperCAmelCase	    =			UpperCAmelCase	    =			0
       while i < len(lowerCAmelCase		) and j < len(lowerCAmelCase		):
              if p[i] > q[j]:
                     # if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
                     # These are all inversions. The claim emerges from the
                     # property that P is sorted.
                     num_inversion += len(lowerCAmelCase		) - i
                     r.append(q[j]		)
                     j += 1
              else:
                     r.append(p[i]		)
                     i += 1

       if i < len(lowerCAmelCase		):
              r.extend(p[i:]		)
       else:
              r.extend(q[j:]		)

       return r, num_inversion






def       _lowerCAmelCase       (      ):







       '''simple docstring'''
       UpperCAmelCase	    =			[10, 2, 1, 5, 5, 2, 11]

       # this arr has 8 inversions:
       # (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

       UpperCAmelCase	    =			count_inversions_bf(lowerCAmelCase		)
       UpperCAmelCase    ,       UpperCAmelCase	    =			count_inversions_recursive(lowerCAmelCase		)

       assert num_inversions_bf == num_inversions_recursive == 8

       print("""number of inversions = """	,      lowerCAmelCase		)

       # testing an array with zero inversion (a sorted arr_1)

       arr_a.sort()
       UpperCAmelCase	    =			count_inversions_bf(lowerCAmelCase		)
       UpperCAmelCase    ,       UpperCAmelCase	    =			count_inversions_recursive(lowerCAmelCase		)

       assert num_inversions_bf == num_inversions_recursive == 0
       print("""number of inversions = """	,      lowerCAmelCase		)

       # an empty list should also have zero inversions
       UpperCAmelCase	    =			[]
       UpperCAmelCase	    =			count_inversions_bf(lowerCAmelCase		)
       UpperCAmelCase    ,       UpperCAmelCase	    =			count_inversions_recursive(lowerCAmelCase		)

       assert num_inversions_bf == num_inversions_recursive == 0
       print("""number of inversions = """	,      lowerCAmelCase		)


if __name__ == "__main__":
 main()
