



from typing import List

import datasets
from datasets.tasks import AudioClassification

from ..folder_based_builder import folder_based_builder


__snake_case		:Any   	=  datasets.utils.logging.get_logger(__name__)

class 					_A (			folder_based_builder.FolderBasedBuilderConfig					):
       UpperCamelCase__						:					bool		      =		None
       UpperCamelCase__						:					bool		      =		None


class 					_A (			folder_based_builder.FolderBasedBuilder					):
       UpperCamelCase__						:					Optional[int]		      =		datasets.Audio()
       UpperCamelCase__						:					int		      =		'''audio'''
       UpperCamelCase__						:					Optional[int]		      =		AudioFolderConfig
       UpperCamelCase__						:					List[str]  # definition at the bottom of the script
       UpperCamelCase__						:					str		      =		AudioClassification(audio_column='''audio'''   ,label_column='''label'''					)


__snake_case		:Optional[int]   	=  [
    '''.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''',
]
__snake_case		:Dict   	=  AUDIO_EXTENSIONS










from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset

class 					_A (			__UpperCAmelCase					):



       def 	_lowerCamelCase    (	self							:  int):


           '''simple docstring'''

           return [
               {"col_1": 3, "col_2": "a"},
               {"col_1": 2, "col_2": "b"},
               {"col_1": 1, "col_2": "c"},
               {"col_1": 0, "col_2": "d"},
           ]



       def 	_lowerCamelCase    (	self							:  Tuple):


           '''simple docstring'''

           __a		 =       {'''col_1''': [3, 2, 1, 0], '''col_2''': ['''a''', '''b''', '''c''', '''d''']}
           return Dataset.from_dict(__SCREAMING_SNAKE_CASE)



       def 	_lowerCamelCase    (	self							:  Any):


           '''simple docstring'''

           __a		 =       self._create_example_records()
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertListEqual(dset.column_names  ,	['''col_1''', '''col_2'''])
           for i, r in enumerate(__SCREAMING_SNAKE_CASE):
               self.assertDictEqual(__SCREAMING_SNAKE_CASE  ,	example_records[i])



       def 	_lowerCamelCase    (	self							:  Optional[Any]):


           '''simple docstring'''

           __a		 =       self._create_example_records()
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           __a		 =       Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]})
           self.assertEqual(dset.info  ,	dset_from_dict.info)



       def 	_lowerCamelCase    (	self							:  int):  # checks what happens with missing columns


           '''simple docstring'''

           __a		 =       [{'''col_1''': 1}, {'''col_2''': '''x'''}]
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertDictEqual(dset[0]  ,	{'''col_1''': 1})
           self.assertDictEqual(dset[1]  ,	{'''col_1''': None})  # NB: first record is used for columns



       def 	_lowerCamelCase    (	self							:  Optional[Any]):  # checks if the type can be inferred from the second record


           '''simple docstring'''

           __a		 =       [{'''col_1''': []}, {'''col_1''': [1, 2]}]
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertEqual(dset.info.features['''col_1''']  ,	Sequence(Value('''int64''')))





       def 	_lowerCamelCase    (	self							:  List[Any]):


           '''simple docstring'''

           __a		 =       Dataset.from_list([])
           self.assertEqual(len(__SCREAMING_SNAKE_CASE)  ,	0)
           self.assertListEqual(dset.column_names  ,	[])





