


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch






class     _lowerCamelCase					(   unittest.TestCase     ):




       """simple docstring"""
       snake_case    =       JukeboxTokenizer
       snake_case    =       {
           "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						)->List[Any]:




         '''simple docstring'''





         import torch

         A_ :							str							=   JukeboxTokenizer.from_pretrained('''openai/jukebox-1b-lyrics'''						)
         A_ :							Any							=   tokenizer(**self.metas						)['input_ids']
         # fmt: off
         A_ :							Optional[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 			_snake_case			( self						)->Optional[Any]:




         '''simple docstring'''





         import torch

         A_ :							List[Any]							=   JukeboxTokenizer.from_pretrained('''openai/jukebox-5b-lyrics'''						)
         A_ :							Any							=   tokenizer(**self.metas						)['input_ids']
         # fmt: off
         A_ :							Union[str, 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]						)						)











__UpperCamelCase:	str = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}

__UpperCamelCase:	Tuple = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : dict[int, list[int]]   ,    _lowercase     : int   ,    _lowercase     : list[bool]			)   ->							list[int]:




		'''simple docstring'''
		lowercase__					:      str      =		True
		lowercase__					:      int      =		[]

		for neighbour in graph[vert]:
				if not visited[neighbour]:
						order += topology_sort(_lowercase   ,    _lowercase   ,    _lowercase			)

		order.append(_lowercase			)

		return order


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : dict[int, list[int]]   ,    _lowercase     : int   ,    _lowercase     : list[bool]			)   ->							list[int]:




		'''simple docstring'''
		lowercase__					:      Union[str, Any]      =		True
		lowercase__					:      Optional[Any]      =		[vert]

		for neighbour in reversed_graph[vert]:
				if not visited[neighbour]:
						component += find_components(_lowercase   ,    _lowercase   ,    _lowercase			)

		return component





def       SCREAMING_SNAKE_CASE__  (       _lowercase     : dict[int, list[int]]			)   ->							list[list[int]]:




		'''simple docstring'''
		lowercase__					:      Optional[int]      =		len(_lowercase			) * [False]
		lowercase__					:      dict[int, list[int]]      =		{vert: [] for vert in range(len(_lowercase			)			)}

		for vert, neighbours in graph.items():
				for neighbour in neighbours:
						reversed_graph[neighbour].append(_lowercase			)

		lowercase__					:      Dict      =		[]
		for i, was_visited in enumerate(_lowercase			):
				if not was_visited:
						order += topology_sort(_lowercase   ,    _lowercase   ,    _lowercase			)

		lowercase__					:      Dict      =		[]
		lowercase__					:      Optional[Any]      =		len(_lowercase			) * [False]

		for i in range(len(_lowercase			)			):
				lowercase__					:      List[Any]      =		order[len(_lowercase			) - i - 1]
				if not visited[vert]:
						lowercase__					:      Tuple      =		find_components(_lowercase   ,    _lowercase   ,    _lowercase			)
						components_list.append(_lowercase			)

		return components_list


