




"""simple docstring"""

import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch

class        lowercase      (    unittest.TestCase):
				__lowerCAmelCase    :    str         =   JukeboxTokenizer
				__lowerCAmelCase    :    Union[str, 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 					a_  (							self   :					Tuple       ):



					"""simple docstring"""

					import torch

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



					"""simple docstring"""

					import torch

					A_  :				Optional[Any]	   =		JukeboxTokenizer.from_pretrained('''openai/jukebox-5b-lyrics'''       )
					A_  :				int	   =		tokenizer(**self.metas       )["input_ids"]
					# fmt: off
					A_  :				str	   =		[
					    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 requests
from bsa import BeautifulSoup

def 		lowercase_      (		_UpperCAmelCase = "https://www.worldometers.info/coronavirus"	):




	"""simple docstring"""






	A_  :				str	   =		BeautifulSoup(requests.get(_UpperCAmelCase	).text  ,      '''html.parser'''	)
	A_  :				Union[str, Any]	   =		soup.findAll('''h1'''	)
	A_  :				Union[str, Any]	   =		soup.findAll('''div'''  ,      {'''class''': '''maincounter-number'''}	)
	keys += soup.findAll('''span'''  ,      {'''class''': '''panel-title'''}	)
	values += soup.findAll('''div'''  ,      {'''class''': '''number-table-main'''}	)
	return {key.text.strip(): value.text.strip() for key, value in zip(_UpperCAmelCase  ,      _UpperCAmelCase	)}


if __name__ == "__main__":
		print('\033[1m' + 'COVID-19 Status of the World' + '\033[0m\n')
		for key, value in world_covidaa_stats().items():
				print(f'{key}\n{value}\n')





