


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class 			_lowercase (     unittest.TestCase			):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__							:     int         =						JukeboxTokenizer
				SCREAMING_SNAKE_CASE__							:     List[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 						__magic_name__(			self     :Dict      )						->     str:
										import torch

										__SCREAMING_SNAKE_CASE		:	Optional[int]						     =						JukeboxTokenizer.from_pretrained('''openai/jukebox-1b-lyrics'''      )
										__SCREAMING_SNAKE_CASE		:	Optional[int]						     =						tokenizer(**self.metas      )['''input_ids''']
										# fmt: off
										__SCREAMING_SNAKE_CASE		:	int						     =						[
										    torch.tensor([[
										        0, 0, 0, 7_169, 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, 1_069, 11]]      ),
										    torch.tensor([[0, 0, 0, 1_069, 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 						__magic_name__(			self     :int      )						->     Dict:
										import torch

										__SCREAMING_SNAKE_CASE		:	Tuple						     =						JukeboxTokenizer.from_pretrained('''openai/jukebox-5b-lyrics'''      )
										__SCREAMING_SNAKE_CASE		:	Dict						     =						tokenizer(**self.metas      )['''input_ids''']
										# fmt: off
										__SCREAMING_SNAKE_CASE		:	List[Any]						     =						[
										    torch.tensor([[
										        0, 0, 0, 1_069, 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, 1_069, 11, -1, -1, -1, -1]]      ),
										    torch.tensor([[0, 0, 0, 1_069, 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'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase									=   {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase									=   [
		    'SEW_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'SEWForCTC',
		    'SEWForSequenceClassification',
		    'SEWModel',
		    'SEWPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_sew import (
				    SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SEWForCTC,
				    SEWForSequenceClassification,
				    SEWModel,
				    SEWPreTrainedModel,
				)


else:
		import sys

		__lowerCAmelCase									=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




