

def        UpperCAmelCase_     (		_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[]
     for data in source_data:
          for i, el in enumerate(_A       ):
               if len(_A       ) < i + 1:
                    data_lists.append([]       )
               data_lists[i].append(float(_A       )       )
     return data_lists
def        UpperCAmelCase_     (		_A   ,	_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[]
     for dlist, weight in zip(_A   ,	_A       ):
          SCREAMING_SNAKE_CASE__					=					min(_A       )
          SCREAMING_SNAKE_CASE__					=					max(_A       )

          SCREAMING_SNAKE_CASE__					=					[]
          # for weight 0 score is 1 - actual score
          if weight == 0:
               for item in dlist:
                    try:
                         score.append(1 - ((item - mind) / (maxd - mind))       )
                    except ZeroDivisionError:
                         score.append(1       )

          elif weight == 1:
               for item in dlist:
                    try:
                         score.append((item - mind) / (maxd - mind)       )
                    except ZeroDivisionError:
                         score.append(0       )

        # weight not 0 or 1
          else:
               SCREAMING_SNAKE_CASE__					=					F'''Invalid weight of {weight:f} provided'''
               raise ValueError(_A       )

          score_lists.append(_A       )

     return score_lists
def        UpperCAmelCase_     (		_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[0 for i in range(len(score_lists[0]       )       )]

     for slist in score_lists:
          for j, ele in enumerate(_A       ):
               SCREAMING_SNAKE_CASE__					=					final_scores[j] + ele

     return final_scores







def        UpperCAmelCase_     (		_A   ,	_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					get_data(_A       )
     SCREAMING_SNAKE_CASE__					=					calculate_each_score(_A   ,	_A       )
     SCREAMING_SNAKE_CASE__					=					generate_final_scores(_A       )

     # append scores to source data
     for i, ele in enumerate(_A       ):
          source_data[i].append(_A       )

     return source_data





from typing import List

import datasets
from datasets.tasks import AudioClassification

from ..folder_based_builder import folder_based_builder


_SCREAMING_SNAKE_CASE  :						Optional[Any]         =    datasets.utils.logging.get_logger(__name__)






class  UpperCAmelCase__	( folder_based_builder.FolderBasedBuilderConfig ):






  """simple docstring"""


  a     =      None
  a     =      None






class  UpperCAmelCase__	( folder_based_builder.FolderBasedBuilder ):






  """simple docstring"""


  a     =      datasets.Audio()
  a     =      "audio"
  a     =      AudioFolderConfig
  a     =      42  # definition at the bottom of the script
  a     =      AudioClassification(audio_column="audio"		,  label_column="label" )



_SCREAMING_SNAKE_CASE  :						str         =    [
    '''.aiff''',
    '''.au''',
    '''.avr''',
    '''.caf''',
    '''.flac''',
    '''.htk''',
    '''.svx''',
    '''.mat4''',
    '''.mat5''',
    '''.mpc2k''',
    '''.ogg''',
    '''.paf''',
    '''.pvf''',
    '''.raw''',
    '''.rf64''',
    '''.sd2''',
    '''.sds''',
    '''.ircam''',
    '''.voc''',
    '''.w64''',
    '''.wav''',
    '''.nist''',
    '''.wavex''',
    '''.wve''',
    '''.xi''',
    '''.mp3''',
    '''.opus''',
]
_SCREAMING_SNAKE_CASE  :						List[Any]         =    AUDIO_EXTENSIONS


