



'''simple docstring'''



import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class 	lowerCamelCase_							(					unittest.TestCase			):
						_lowerCAmelCase     :   List[str]	     =				JukeboxTokenizer
						_lowerCAmelCase     :   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 					__lowercase    (  self   :      Optional[int]				):

													"""simple docstring"""
													import torch

													SCREAMING_SNAKE_CASE					:      Dict     					=			JukeboxTokenizer.from_pretrained('''openai/jukebox-1b-lyrics'''				)
													SCREAMING_SNAKE_CASE					:      int     					=			tokenizer(**self.metas				)["input_ids"]
													# fmt: off
													SCREAMING_SNAKE_CASE					:      List[str]     					=			[
													    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 					__lowercase    (  self   :      List[Any]				):

													"""simple docstring"""
													import torch

													SCREAMING_SNAKE_CASE					:      Tuple     					=			JukeboxTokenizer.from_pretrained('''openai/jukebox-5b-lyrics'''				)
													SCREAMING_SNAKE_CASE					:      Tuple     					=			tokenizer(**self.metas				)["input_ids"]
													# fmt: off
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			[
													    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 string
from math import logaa
def 					UpperCAmelCase   (						A  :				str					,		A  :				str				):
							SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			document.translate(
							    str.maketrans(''''''					,		''''''					,		string.punctuation				)				).replace('''\n'''					,		''''''				)
							SCREAMING_SNAKE_CASE					:      Tuple     					=			document_without_punctuation.split(''' '''				)  # word tokenization
							return len([word for word in tokenize_document if word.lower() == term.lower()]				)
def 					UpperCAmelCase   (						A  :				str					,		A  :				str				):
							SCREAMING_SNAKE_CASE					:      int     					=			corpus.lower().translate(
							    str.maketrans(''''''					,		''''''					,		string.punctuation				)				)  # strip all punctuation and replace it with ''
							SCREAMING_SNAKE_CASE					:      Any     					=			corpus_without_punctuation.split('''\n'''				)
							SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			term.lower()
							return (len([doc for doc in docs if term in doc]				), len(A				))
def 					UpperCAmelCase   (						A  :				int					,		A  :				int					,		A  :				str=False				):
							if smoothing:
														if n == 0:
																					raise ValueError('''log10(0) is undefined.'''				)
														return round(1 + logaa(n / (1 + df)				)					,		3				)

							if df == 0:
														raise ZeroDivisionError('''df must be > 0'''				)
							elif n == 0:
														raise ValueError('''log10(0) is undefined.'''				)
							return round(logaa(n / df				)					,		3				)






def 					UpperCAmelCase   (						A  :				int					,		A  :				int				):
							return round(tf * idf					,		3				)




