


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch







class        lowerCamelCase__	(							unittest.TestCase      ):






			"""simple docstring"""






			_UpperCamelCase		:					str    =		JukeboxTokenizer
			_UpperCamelCase		:					Optional[Any]    =		{
			    '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 				snake_case__				(							self     ):

						'''simple docstring'''


						import torch

						UpperCamelCase__					=       JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics"     )
						UpperCamelCase__					=       tokenizer(**self.metas     )["input_ids"]
						# fmt: off
						UpperCamelCase__					=       [
						    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 				snake_case__				(							self     ):

						'''simple docstring'''


						import torch

						UpperCamelCase__					=       JukeboxTokenizer.from_pretrained("openai/jukebox-5b-lyrics"     )
						UpperCamelCase__					=       tokenizer(**self.metas     )["input_ids"]
						# fmt: off
						UpperCamelCase__					=       [
						    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]     )     )






def        UpperCamelCase_(				_A   :int				,     _A   :int  )->		str:
			if number < 0 or shift_amount < 0:
						raise ValueError("both inputs must be positive integers"  )

			UpperCamelCase__					=       str(bin(_A  )  )
			binary_number += "0" * shift_amount
			return binary_number
def        UpperCamelCase_(				_A   :int				,     _A   :int  )->		str:
			if number < 0 or shift_amount < 0:
						raise ValueError("both inputs must be positive integers"  )

			UpperCamelCase__					=       str(bin(_A  )  )[2:]
			if shift_amount >= len(_A  ):
						return "0b0"
			UpperCamelCase__					=       binary_number[: len(_A  ) - shift_amount]
			return "0b" + shifted_binary_number
def        UpperCamelCase_(				_A   :int				,     _A   :int  )->		str:
			if number >= 0:  # Get binary representation of positive number
						UpperCamelCase__					=       "0" + str(bin(_A  )  ).strip("-"  )[2:]
			else:  # Get binary (2's complement) representation of negative number
						UpperCamelCase__					=       len(bin(_A  )[3:]  )  # Find 2's complement of number
						UpperCamelCase__					=       bin(abs(_A  ) - (1 << binary_number_length)  )[3:]
						UpperCamelCase__					=       (
						    "1" + "0" * (binary_number_length - len(_A  )) + binary_number
						)

			if shift_amount >= len(_A  ):
						return "0b" + binary_number[0] * len(_A  )
			return (
			    "0b"
			    + binary_number[0] * shift_amount
			    + binary_number[: len(_A  ) - shift_amount]
			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()


