

def 	__a     (      A__			:  str			,  A__			:  str = " "       ):
    SCREAMING_SNAKE_CASE										=   []

    SCREAMING_SNAKE_CASE										=   0
    for index, char in enumerate(A__       ):
        if char == separator:
            split_words.append(string[last_index:index]       )
            SCREAMING_SNAKE_CASE										=   index + 1
        elif index + 1 == len(A__       ):
            split_words.append(string[last_index : index + 1]       )
    return split_words


if __name__ == "__main__":
    from doctest import testmod

    testmod()




'''simple docstring'''





import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch


class 					snake_case			(unittest.TestCase ):
       lowerCAmelCase__	:Dict     =       JukeboxTokenizer
       lowerCAmelCase__	:List[str]     =       {
           "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 				_a   (					self   )	->				Dict:
           import torch

           lowercase__									=    JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics"   )
           lowercase__									=    tokenizer(**self.metas   )["input_ids"]
           # fmt: off
           lowercase__									=    [
               torch.tensor([[
                   0, 0, 0, 7_169, 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, 1_069, 11]]   ),
               torch.tensor([[0, 0, 0, 1_069, 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 				_a   (					self   )	->				Optional[Any]:
           import torch

           lowercase__									=    JukeboxTokenizer.from_pretrained("openai/jukebox-5b-lyrics"   )
           lowercase__									=    tokenizer(**self.metas   )["input_ids"]
           # fmt: off
           lowercase__									=    [
               torch.tensor([[
                   0, 0, 0, 1_069, 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, 1_069, 11, -1, -1, -1, -1]]   ),
               torch.tensor([[0, 0, 0, 1_069, 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]   )   )




