


"""simple docstring"""


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class snake_case      (  unittest.TestCase):
		__UpperCamelCase           =			JukeboxTokenizer
		__UpperCamelCase           =			{
		    '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      :       Any		)       ->						Optional[int]:





						'''simple docstring'''







						import torch

						_A					  =			JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics"		)
						_A					  =			tokenizer(**self.metas		)["input_ids"]
						# fmt: off
						_A					  =			[
						    torch.tensor([[
						        0, 0, 0, 71_69, 5_07, 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, 10_69, 11]]		),
						    torch.tensor([[0, 0, 0, 10_69, 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      :       List[Any]		)       ->						Union[str, Any]:





						'''simple docstring'''







						import torch

						_A					  =			JukeboxTokenizer.from_pretrained("openai/jukebox-5b-lyrics"		)
						_A					  =			tokenizer(**self.metas		)["input_ids"]
						# fmt: off
						_A					  =			[
						    torch.tensor([[
						        0, 0, 0, 10_69, 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, 10_69, 11, -1, -1, -1, -1]]		),
						    torch.tensor([[0, 0, 0, 10_69, 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"""


import random






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	Optional[Any]:
				_A					  =			a[left_index]
				_A					  =			left_index + 1
				for j in range(left_index + 1     ,			__lowercase   ):
								if a[j] < pivot:
												_A  ,		_A					  =			a[i], a[j]
												i += 1
				_A  ,		_A					  =			a[i - 1], a[left_index]
				return i - 1






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	int:
				if left < right:
								_A					  =			random.randint(__lowercase     ,			right - 1   )
								_A  ,		_A					  =			(
								    a[left],
								    a[pivot],
								)  # switches the pivot with the left most bound
								_A					  =			partition(__lowercase     ,			__lowercase     ,			__lowercase   )
								quick_sort_random(
								    __lowercase     ,			__lowercase     ,			__lowercase   )  # recursive quicksort to the left of the pivot point
								quick_sort_random(
								    __lowercase     ,			pivot_index + 1     ,			__lowercase   )  # recursive quicksort to the right of the pivot point






def      a__ (				)	->	Dict:
				_A					  =			input("Enter numbers separated by a comma:\n"   ).strip()
				_A					  =			[int(__lowercase   ) for item in user_input.split(","   )]

				quick_sort_random(__lowercase     ,			0     ,			len(__lowercase   )   )

				print(__lowercase   )


if __name__ == "__main__":
		main()