



'''simple docstring'''

import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch

class       __magic_name__		(       unittest.TestCase  ):
							lowerCAmelCase			:       Dict  							=   JukeboxTokenizer
							lowerCAmelCase			:       Optional[int]  							=   {
							    'artist': 'Zac Brown Band',
							    'genres': 'Country',
							    'lyrics': 'I met a traveller from an antique land,\n        Who said "Two vast and trunkless legs of stone\n        Stand in the desert. . . . Near them, on the sand,\n        Half sunk a shattered visage lies, whose frown,\n        And wrinkled lip, and sneer of cold command,\n        Tell that its sculptor well those passions read\n        Which yet survive, stamped on these lifeless things,\n        The hand that mocked them, and the heart that fed;\n        And on the pedestal, these words appear:\n        My name is Ozymandias, King of Kings;\n        Look on my Works, ye Mighty, and despair!\n        Nothing beside remains. Round the decay\n        Of that colossal Wreck, boundless and bare\n        The lone and level sands stretch far away\n        ',
							}







							@require_torch
							def 				__lowercase     (				self   :			Optional[Any]						):
									import torch

									_a	: str								=				JukeboxTokenizer.from_pretrained('openai/jukebox-1b-lyrics'						)
									_a	: Tuple								=				tokenizer(**self.metas						)['''input_ids''']
									# fmt: off
									_a	: Any								=				[
									    torch.tensor([[
									        0, 0, 0, 7169, 507, 9, 76, 39, 31, 46, 76, 27,
									        76, 46, 44, 27, 48, 31, 38, 38, 31, 44, 76, 32,
									        44, 41, 39, 76, 27, 40, 76, 27, 40, 46, 35, 43,
									        47, 31, 76, 38, 27, 40, 30, 64, 78, 76, 76, 76,
									        76, 76, 76, 76, 76, 23, 34, 41, 76, 45, 27, 35,
									        30, 76, 71, 20, 49, 41, 76, 48, 27, 45, 46, 76,
									        27, 40, 30, 76, 46, 44, 47, 40, 37, 38, 31, 45,
									        45, 76, 38, 31, 33, 45, 76, 41, 32, 76, 45, 46,
									        41, 40, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
									        19, 46, 27, 40, 30, 76, 35, 40, 76, 46, 34, 31,
									        76, 30, 31, 45, 31, 44, 46, 63, 76, 63, 76, 63,
									        76, 63, 76, 14, 31, 27, 44, 76, 46, 34, 31, 39,
									        64, 76, 41, 40, 76, 46, 34, 31, 76, 45, 27, 40,
									        30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76, 8,
									        27, 38, 32, 76, 45, 47, 40, 37, 76, 27, 76, 45,
									        34, 27, 46, 46, 31, 44, 31, 30, 76, 48, 35, 45,
									        27, 33, 31, 76, 38, 35, 31, 45, 64, 76, 49, 34,
									        41, 45, 31, 76, 32, 44, 41, 49, 40, 64, 78, 76,
									        76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76, 49,
									        44, 35, 40, 37, 38, 31, 30, 76, 38, 35, 42, 64,
									        76, 27, 40, 30, 76, 45, 40, 31, 31, 44, 76, 41,
									        32, 76, 29, 41, 38, 30, 76, 29, 41, 39, 39, 27,
									        40, 30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76,
									        20, 31, 38, 38, 76, 46, 34, 27, 46, 76, 35, 46,
									        45, 76, 45, 29, 47, 38, 42, 46, 41, 44, 76, 49,
									        31, 38, 38, 76, 46, 34, 41, 45, 31, 76, 42, 27,
									        45, 45, 35, 41, 40, 45, 76, 44, 31, 27, 30, 78,
									        76, 76, 76, 76, 76, 76, 76, 76, 23, 34, 35, 29,
									        34, 76, 51, 31, 46, 76, 45, 47, 44, 48, 35, 48,
									        31, 64, 76, 45, 46, 27, 39, 42, 31, 30, 76, 41,
									        40, 76, 46, 34, 31, 45, 31, 76, 38, 35, 32, 31,
									        38, 31, 45, 45, 76, 46, 34, 35, 40, 33, 45, 64,
									        78, 76, 76, 76, 76, 76, 76, 76, 76, 20, 34, 31,
									        76, 34, 27, 40, 30, 76, 46, 34, 27, 46, 76, 39,
									        41, 29, 37, 31, 30, 76, 46, 34, 31, 39, 64, 76,
									        27, 40, 30, 76, 46, 34, 31, 76, 34, 31, 27, 44,
									        46, 76, 46, 34, 27, 46, 76, 32, 31, 30, 66, 78,
									        76, 76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76,
									        41, 40, 76, 46, 34, 31, 76, 42, 31, 30, 31, 45,
									        46, 27, 38, 64, 76, 46, 34, 31, 45, 31, 76, 49,
									        41, 44, 30, 45, 76, 27, 42, 42, 31, 27, 44, 65,
									        78, 76, 76, 76, 76, 76, 76, 76, 76, 13, 51, 76,
									        40, 27, 39, 31, 76, 35, 45, 76, 15, 52, 51, 39,
									        27, 40, 30, 35, 27, 45, 64, 76, 11, 35, 40, 33,
									        76, 41, 32, 76, 11, 35, 40, 33, 45, 66, 78, 76,
									        76, 76, 76, 76, 76, 76, 76, 12, 41, 41, 37, 76,
									        41, 40, 76, 39, 51, 76, 23, 41, 44, 37, 45, 64,
									        76, 51, 31, 76, 13, 35, 33, 34, 46, 51, 64, 76,
									        27, 40, 30, 76, 30, 31, 45, 42, 27, 35, 44, 67,
									        78, 76, 76, 76, 76, 76, 76, 76, 76, 14, 41, 46,
									        34, 35, 40, 33, 76, 28, 31, 45, 35, 30, 31, 76,
									        44, 31, 39, 27, 35, 40, 45, 63, 76, 18, 41, 47,
									        40, 30, 76, 46, 34, 31, 76, 30, 31, 29, 27, 51,
									        78, 76, 76, 76, 76, 76, 76, 76, 76, 15, 32, 76,
									        46, 34, 27, 46, 76, 29, 41, 38, 41, 45, 45, 27,
									        38, 76, 23, 44, 31, 29, 37, 64, 76, 28, 41, 47,
									        40, 30, 38, 31, 45, 45, 76, 27, 40, 30, 76, 28,
									        27, 44, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
									        20, 34, 31, 76, 38, 41, 40, 31, 76, 27, 40, 30,
									        76, 38, 31, 48, 31, 38, 76, 45, 27, 40, 30, 45,
									        76, 45, 46, 44, 31, 46, 29, 34, 76, 32, 27, 44,
									        76, 27, 49, 27, 51, 78, 76, 76, 76, 76, 76, 76,
									        76, 76]]						),
									    torch.tensor([[0, 0, 0, 1069, 11]]						),
									    torch.tensor([[0, 0, 0, 1069, 11]]						),
									]
									# fmt: on
									self.assertTrue(torch.allclose(tokens[0]      ,EXPECTED_OUTPUT[0]						)						)
									self.assertTrue(torch.allclose(tokens[1]      ,EXPECTED_OUTPUT[1]						)						)
									self.assertTrue(torch.allclose(tokens[2]      ,EXPECTED_OUTPUT[2]						)						)







							@require_torch
							def 				__lowercase     (				self   :			Union[str, Any]						):
									import torch

									_a	: int								=				JukeboxTokenizer.from_pretrained('openai/jukebox-5b-lyrics'						)
									_a	: str								=				tokenizer(**self.metas						)['''input_ids''']
									# fmt: off
									_a	: List[Any]								=				[
									    torch.tensor([[
									        0, 0, 0, 1069, 11, -1, -1, -1, -1, 9, 77, 39,
									        31, 46, 77, 27, 77, 46, 44, 27, 48, 31, 38, 38,
									        31, 44, 77, 32, 44, 41, 39, 77, 27, 40, 77, 27,
									        40, 46, 35, 43, 47, 31, 77, 38, 27, 40, 30, 64,
									        79, 77, 77, 77, 77, 77, 77, 77, 77, 23, 34, 41,
									        77, 45, 27, 35, 30, 77, 72, 20, 49, 41, 77, 48,
									        27, 45, 46, 77, 27, 40, 30, 77, 46, 44, 47, 40,
									        37, 38, 31, 45, 45, 77, 38, 31, 33, 45, 77, 41,
									        32, 77, 45, 46, 41, 40, 31, 79, 77, 77, 77, 77,
									        77, 77, 77, 77, 19, 46, 27, 40, 30, 77, 35, 40,
									        77, 46, 34, 31, 77, 30, 31, 45, 31, 44, 46, 63,
									        77, 63, 77, 63, 77, 63, 77, 14, 31, 27, 44, 77,
									        46, 34, 31, 39, 64, 77, 41, 40, 77, 46, 34, 31,
									        77, 45, 27, 40, 30, 64, 79, 77, 77, 77, 77, 77,
									        77, 77, 77, 8, 27, 38, 32, 77, 45, 47, 40, 37,
									        77, 27, 77, 45, 34, 27, 46, 46, 31, 44, 31, 30,
									        77, 48, 35, 45, 27, 33, 31, 77, 38, 35, 31, 45,
									        64, 77, 49, 34, 41, 45, 31, 77, 32, 44, 41, 49,
									        40, 64, 79, 77, 77, 77, 77, 77, 77, 77, 77, 1,
									        40, 30, 77, 49, 44, 35, 40, 37, 38, 31, 30, 77,
									        38, 35, 42, 64, 77, 27, 40, 30, 77, 45, 40, 31,
									        31, 44, 77, 41, 32, 77, 29, 41, 38, 30, 77, 29,
									        41, 39, 39, 27, 40, 30, 64, 79, 77, 77, 77, 77,
									        77, 77, 77, 77, 20, 31, 38, 38, 77, 46, 34, 27,
									        46, 77, 35, 46, 45, 77, 45, 29, 47, 38, 42, 46,
									        41, 44, 77, 49, 31, 38, 38, 77, 46, 34, 41, 45,
									        31, 77, 42, 27, 45, 45, 35, 41, 40, 45, 77, 44,
									        31, 27, 30, 79, 77, 77, 77, 77, 77, 77, 77, 77,
									        23, 34, 35, 29, 34, 77, 51, 31, 46, 77, 45, 47,
									        44, 48, 35, 48, 31, 64, 77, 45, 46, 27, 39, 42,
									        31, 30, 77, 41, 40, 77, 46, 34, 31, 45, 31, 77,
									        38, 35, 32, 31, 38, 31, 45, 45, 77, 46, 34, 35,
									        40, 33, 45, 64, 79, 77, 77, 77, 77, 77, 77, 77,
									        77, 20, 34, 31, 77, 34, 27, 40, 30, 77, 46, 34,
									        27, 46, 77, 39, 41, 29, 37, 31, 30, 77, 46, 34,
									        31, 39, 64, 77, 27, 40, 30, 77, 46, 34, 31, 77,
									        34, 31, 27, 44, 46, 77, 46, 34, 27, 46, 77, 32,
									        31, 30, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77,
									        1, 40, 30, 77, 41, 40, 77, 46, 34, 31, 77, 42,
									        31, 30, 31, 45, 46, 27, 38, 64, 77, 46, 34, 31,
									        45, 31, 77, 49, 41, 44, 30, 45, 77, 27, 42, 42,
									        31, 27, 44, 65, 79, 77, 77, 77, 77, 77, 77, 77,
									        77, 13, 51, 77, 40, 27, 39, 31, 77, 35, 45, 77,
									        15, 52, 51, 39, 27, 40, 30, 35, 27, 45, 64, 77,
									        11, 35, 40, 33, 77, 41, 32, 77, 11, 35, 40, 33,
									        45, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77, 12,
									        41, 41, 37, 77, 41, 40, 77, 39, 51, 77, 23, 41,
									        44, 37, 45, 64, 77, 51, 31, 77, 13, 35, 33, 34,
									        46, 51, 64, 77, 27, 40, 30, 77, 30, 31, 45, 42,
									        27, 35, 44, 67, 79, 77, 77, 77, 77, 77, 77, 77,
									        77, 14, 41, 46, 34, 35, 40, 33, 77, 28, 31, 45,
									        35, 30, 31, 77, 44, 31, 39, 27, 35, 40, 45, 63,
									        77, 18, 41, 47, 40, 30, 77, 46, 34, 31, 77, 30,
									        31, 29, 27, 51, 79, 77, 77, 77, 77, 77, 77, 77,
									        77, 15, 32, 77, 46, 34, 27, 46, 77, 29, 41, 38,
									        41, 45, 45, 27, 38, 77, 23, 44, 31, 29, 37, 64,
									        77, 28, 41, 47, 40, 30, 38, 31, 45, 45, 77, 27,
									        40, 30, 77, 28, 27, 44, 31, 79, 77, 77, 77, 77,
									        77, 77, 77, 77, 20, 34, 31, 77, 38, 41, 40, 31,
									        77, 27, 40, 30, 77, 38, 31, 48, 31, 38, 77, 45,
									        27, 40, 30, 45, 77, 45, 46, 44, 31, 46, 29, 34,
									        77, 32, 27, 44, 77, 27, 49, 27, 51, 79, 77, 77,
									        77, 77, 77, 77, 77, 77]]						),
									    torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]						),
									    torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]						),
									]
									# fmt: on
									self.assertTrue(torch.allclose(tokens[0]      ,EXPECTED_OUTPUT[0]						)						)
									self.assertTrue(torch.allclose(tokens[1]      ,EXPECTED_OUTPUT[1]						)						)
									self.assertTrue(torch.allclose(tokens[2]      ,EXPECTED_OUTPUT[2]						)						)






'''simple docstring'''




lowercase     :							dict[str, float]       						=     {
    "joule": 1.0,
    "kilojoule": 10_00,
    "megajoule": 1_00_00_00,
    "gigajoule": 10_00_00_00_00,
    "wattsecond": 1.0,
    "watthour": 36_00,
    "kilowatthour": 3_60_00_00,
    "newtonmeter": 1.0,
    "calorie_nutr": 41_86.8,
    "kilocalorie_nutr": 4_18_68_00.00,
    "electronvolt": 1.6_02_17_66_34e-19,
    "britishthermalunit_it": 10_55.0_55_85,
    "footpound": 1.35_58_18,
}







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__						,							snake_case__		):




    '''simple docstring'''



    if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
        A			:  int   =		(
            F'Incorrect \'from_type\' or \'to_type\' value: {from_type!r}, {to_type!r}\n'
            F'Valid values are: {", ".join(snake_case__		)}'
        )
        raise ValueError(snake_case__		)
    return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
      import doctest

      doctest.testmod()




