


import unittest
from unittest import skip

from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow
from transformers.trainer_utils import set_seed


if is_torch_available():
			import torch

			from transformers import JukeboxModel, JukeboxPrior, JukeboxTokenizer



@require_torch
class      snake_case__	(   unittest.TestCase	):
				__lowerCAmelCase		=   (JukeboxModel,) if is_torch_available() else ()
				__lowerCAmelCase		=   '''openai/jukebox-1b-lyrics'''
				__lowerCAmelCase		=   {
				    '''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    ''',
				}
				# fmt: off
				__lowerCAmelCase		=   [
				    1_864, 1_536, 1_213, 1_870, 1_357, 1_536, 519, 880, 1_323, 789, 1_082, 534,
				    1_000, 1_445, 1_105, 1_130, 967, 515, 1_434, 1_620, 534, 1_495, 283, 1_445,
				    333, 1_307, 539, 1_631, 1_528, 375, 1_434, 673, 627, 710, 778, 1_883,
				    1_405, 1_276, 1_455, 1_228
				]

				__lowerCAmelCase		=   [
				    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653
				]

				__lowerCAmelCase		=   [
				    1_125, 1_751, 697, 1_776, 1_141, 1_476, 391, 697, 1_125, 684, 867, 416,
				    844, 1_372, 1_274, 717, 1_274, 844, 1_299, 1_419, 697, 1_370, 317, 1_125,
				    191, 1_440, 1_370, 1_440, 1_370, 282, 1_621, 1_370, 368, 349, 867, 1_872,
				    1_262, 869, 1_728, 747
				]
				__lowerCAmelCase		=   [
				    416, 416, 1_125, 1_125, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416
				]

				__lowerCAmelCase		=   [
				    1_755, 842, 307, 1_843, 1_022, 1_395, 234, 1_554, 806, 739, 1_022, 442,
				    616, 556, 268, 1_499, 933, 457, 1_440, 1_837, 755, 985, 308, 902,
				    293, 1_443, 1_671, 1_141, 1_533, 555, 1_562, 1_061, 287, 417, 1_022, 2_008,
				    1_186, 1_015, 1_777, 268
				]
				__lowerCAmelCase		=   [
				    854, 842, 1_353, 114, 1_353, 842, 185, 842, 185, 114, 591, 842,
				    185, 417, 185, 842, 307, 842, 591, 842, 185, 842, 307, 842,
				    591, 842, 1_353, 842, 185, 842, 591, 842, 591, 114, 591, 842,
				    185, 842, 591, 89
				]

				__lowerCAmelCase		=   [1_058_304, 0, 786_432, 7_169, 507, 76, 27, 40, 30, 76]

				__lowerCAmelCase		=   [
				    390, 1_160, 1_002, 1_907, 1_788, 1_788, 1_788, 1_907, 1_002, 1_002, 1_854, 1_002,
				    1_002, 1_002, 1_002, 1_002, 1_002, 1_160, 1_160, 1_606, 596, 596, 1_160, 1_002,
				    1_516, 596, 1_002, 1_002, 1_002, 1_907, 1_788, 1_788, 1_788, 1_854, 1_788, 1_907,
				    1_907, 1_788, 596, 1_626
				]
				__lowerCAmelCase		=   [
				    1_236, 1_668, 1_484, 1_920, 1_848, 1_409, 139, 864, 1_828, 1_272, 1_599, 824,
				    1_672, 139, 555, 1_484, 824, 1_920, 555, 596, 1_579, 1_599, 1_231, 1_599,
				    1_637, 1_407, 212, 824, 1_599, 116, 1_433, 824, 258, 1_599, 1_433, 1_895,
				    1_063, 1_433, 1_433, 1_599
				]
				__lowerCAmelCase		=   [
				    1_684, 1_873, 1_119, 1_189, 395, 611, 1_901, 972, 890, 1_337, 1_392, 1_927,
				    96, 972, 672, 780, 1_119, 890, 158, 771, 1_073, 1_927, 353, 1_331,
				    1_269, 1_459, 1_333, 1_645, 812, 1_577, 1_337, 606, 353, 981, 1_466, 619,
				    197, 391, 302, 1_930
				]
				__lowerCAmelCase		=   [
				    390, 1_160, 1_002, 1_907, 1_788, 1_788, 1_788, 1_907, 1_002, 1_002, 1_854, 1_002,
				    1_002, 1_002, 1_002, 1_002, 1_002, 1_160, 1_160, 1_606, 596, 596, 1_160, 1_002,
				    1_516, 596, 1_002, 1_002, 1_002, 1_907, 1_788, 1_788, 1_788, 1_854, 1_788, 1_907,
				    1_907, 1_788, 596, 1_626
				]
				__lowerCAmelCase		=   [
				    -0.04_92, -0.05_24, -0.05_65, -0.06_40, -0.06_86, -0.06_84, -0.06_77, -0.06_64,
				    -0.06_05, -0.04_90, -0.03_30, -0.01_68, -0.00_83, -0.00_75, -0.00_51, 0.00_25,
				    0.01_36, 0.02_61, 0.03_86, 0.04_97, 0.05_80, 0.05_99, 0.05_83, 0.06_14,
				    0.07_40, 0.08_89, 0.10_23, 0.11_62, 0.12_11, 0.12_12, 0.12_51, 0.13_36,
				    0.15_02, 0.16_86, 0.18_83, 0.21_48, 0.23_63, 0.24_58, 0.25_07, 0.25_31
				]
				__lowerCAmelCase		=   [
				    0.02_56, -0.05_44, 0.16_00, -0.00_32, 0.10_66, 0.08_25, -0.00_13, 0.34_40,
				    0.02_10, 0.04_12, -0.17_77, -0.08_92, -0.01_64, 0.02_85, -0.06_13, -0.06_17,
				    -0.01_37, -0.02_01, -0.01_75, 0.02_15, -0.06_27, 0.05_20, -0.07_30, 0.09_70,
				    -0.01_00, 0.04_42, -0.05_86, 0.02_07, -0.00_15, -0.00_82
				]
				__lowerCAmelCase		=   [
				    0.04_15, 0.08_77, 0.00_22, -0.00_55, 0.07_51, 0.03_34, 0.03_24, -0.00_68,
				    0.00_11, 0.00_17, -0.06_76, 0.06_55, -0.01_43, 0.03_99, 0.03_03, 0.07_43,
				    -0.01_68, -0.03_94, -0.11_13, 0.01_24, 0.04_42, 0.02_67, -0.00_03, -0.15_36,
				    -0.01_16, -0.18_37, -0.01_80, -0.10_26, -0.07_77, -0.04_56
				]
				__lowerCAmelCase		=   [
				    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
				]
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				Dict				=   JukeboxTokenizer.from_pretrained(self.model_id   )
										__magic_name__					:				int				=   tokenizer(**self.metas   )['input_ids']
										return tokens
				@slow
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				Tuple				=   JukeboxModel.from_pretrained(self.model_id  ,   min_duration=0   ).eval()
										__magic_name__					:				int				=   self.prepare_inputs()

										set_seed(0   )
										__magic_name__					:				int				=   [torch.zeros(1  ,   0  ,   dtype=torch.long   ).cpu() for _ in range(3   )]
										__magic_name__					:				Optional[int]				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [0]  ,   sample_length=40 * model.priors[0].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										self.assertIn(zs[0][0].detach().cpu().tolist()  ,   [self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]   )

										set_seed(0   )
										__magic_name__					:				Dict				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [1]  ,   sample_length=40 * model.priors[1].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										self.assertIn(zs[1][0].detach().cpu().tolist()  ,   [self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]   )

										set_seed(0   )
										__magic_name__					:				List[Any]				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [2]  ,   sample_length=40 * model.priors[2].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										self.assertIn(zs[2][0].detach().cpu().tolist()  ,   [self.EXPECTED_OUTPUT_0, self.EXPECTED_OUTPUT_0_PT_2]   )
				@slow
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				Tuple				=   False
										__magic_name__					:				Dict				=   JukeboxModel.from_pretrained(self.model_id  ,   min_duration=0   ).eval()

										__magic_name__					:				Union[str, Any]				=   self.prepare_inputs()
										set_seed(0   )
										__magic_name__					:				Union[str, Any]				=   [torch.zeros(1  ,   0  ,   dtype=torch.long   ) for _ in range(3   )]

										__magic_name__					:				str				=   model.priors[0]
										__magic_name__					:				Optional[int]				=   0
										__magic_name__					:				Dict				=   top_prior.get_music_tokens_conds(__SCREAMING_SNAKE_CASE  ,   start=__SCREAMING_SNAKE_CASE  ,   end=start + top_prior.n_ctx   )
										__magic_name__					:				Any				=   top_prior.get_metadata(labels[0].clone()  ,   __SCREAMING_SNAKE_CASE  ,   105_8304  ,   0   )

										self.assertIsNone(__SCREAMING_SNAKE_CASE   )
										self.assertListEqual(metadata.numpy()[0][:10].tolist()  ,   self.EXPECTED_Y_COND   )

										__magic_name__					:				List[Any]				=   top_prior.get_cond(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE   )
										torch.testing.assert_allclose(
										    audio_conditioning[0][0][:30].detach()  ,   torch.tensor(self.EXPECTED_AUDIO_COND   )  ,   atol=1E-4  ,   rtol=1E-4   )
										torch.testing.assert_allclose(
										    metadata_conditioning[0][0][:30].detach()  ,   torch.tensor(self.EXPECTED_META_COND   )  ,   atol=1E-4  ,   rtol=1E-4   )
										torch.testing.assert_allclose(
										    lyric_tokens[0, :30].detach()  ,   torch.tensor(self.EXPECTED_LYRIC_COND   )  ,   atol=1E-4  ,   rtol=1E-4   )
				@slow
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				Union[str, Any]				=   False

										__magic_name__					:				Tuple				=   JukeboxModel.from_pretrained(self.model_id  ,   min_duration=0   ).eval()
										set_seed(0   )
										__magic_name__					:				Optional[int]				=   torch.rand((1, 5120, 1)   )
										__magic_name__					:				Any				=   list(self.prepare_inputs()   )

										__magic_name__					:				str				=   [model.vqvae.encode(__SCREAMING_SNAKE_CASE  ,   start_level=2  ,   bs_chunks=waveform.shape[0]   )[0], None, None]
										__magic_name__					:				Tuple				=   model._sample(
										    __SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   sample_levels=[0]  ,   save_results=__SCREAMING_SNAKE_CASE  ,   sample_length=40 * model.priors[0].raw_to_tokens   )
										torch.testing.assert_allclose(zs[0][0][:40]  ,   torch.tensor(self.EXPECTED_PRIMED_0   )   )

										__magic_name__					:				Tuple				=   torch.cat((zs[0], torch.zeros(1  ,   2048 - zs[0].shape[-1]   ))  ,   dim=-1   ).long()
										__magic_name__					:				Any				=   [upper_a, model.vqvae.encode(__SCREAMING_SNAKE_CASE  ,   start_level=1  ,   bs_chunks=waveform.shape[0]   )[0], None]
										__magic_name__					:				Dict				=   model._sample(
										    __SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   sample_levels=[1]  ,   save_results=__SCREAMING_SNAKE_CASE  ,   sample_length=40 * model.priors[1].raw_to_tokens   )
										torch.testing.assert_allclose(zs[1][0][:40]  ,   torch.tensor(self.EXPECTED_PRIMED_1   )   )

										__magic_name__					:				Union[str, Any]				=   torch.cat((zs[1], torch.zeros(1  ,   2048 - zs[1].shape[-1]   ))  ,   dim=-1   ).long()
										__magic_name__					:				Dict				=   [upper_a, upper_a, model.vqvae.encode(__SCREAMING_SNAKE_CASE  ,   start_level=0  ,   bs_chunks=waveform.shape[0]   )[0]]
										__magic_name__					:				List[Any]				=   model._sample(
										    __SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   sample_levels=[2]  ,   save_results=__SCREAMING_SNAKE_CASE  ,   sample_length=40 * model.priors[2].raw_to_tokens   )
										torch.testing.assert_allclose(zs[2][0][:40].cpu()  ,   torch.tensor(self.EXPECTED_PRIMED_2   )   )





				@slow
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				Any				=   JukeboxModel.from_pretrained(self.model_id  ,   min_duration=0   ).eval()
										set_seed(0   )
										__magic_name__					:				Dict				=   torch.rand((1, 5120, 1)   )
										with torch.no_grad():
																__magic_name__					:				List[Any]				=   model.vqvae.encode(__SCREAMING_SNAKE_CASE  ,   start_level=2  ,   bs_chunks=x.shape[0]   )
										torch.testing.assert_allclose(zs[0][0]  ,   torch.tensor(self.EXPECTED_VQVAE_ENCODE   )   )

										with torch.no_grad():
																__magic_name__					:				str				=   model.vqvae.decode(__SCREAMING_SNAKE_CASE  ,   start_level=2  ,   bs_chunks=x.shape[0]   )
										torch.testing.assert_allclose(x[0, :40, 0]  ,   torch.tensor(self.EXPECTED_VQVAE_DECODE   )  ,   atol=1E-4  ,   rtol=1E-4   )






@require_torch
class      snake_case__	(   unittest.TestCase	):
				__lowerCAmelCase		=   (JukeboxModel,) if is_torch_available() else ()
				__lowerCAmelCase		=   '''openai/jukebox-5b-lyrics'''
				__lowerCAmelCase		=   {
				    '''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    ''',
				}

				# fmt: off
				__lowerCAmelCase		=   [
				    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    1_489, 1_489, 1_489, 1_489, 1_150, 1_853, 1_509, 1_150, 1_357, 1_509, 6, 1_272
				]
				__lowerCAmelCase		=   [
				    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653
				]

				__lowerCAmelCase		=   [
				    1_125, 416, 1_125, 1_125, 1_125, 1_125, 1_125, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416
				]
				__lowerCAmelCase		=   [
				    416, 416, 1_125, 1_125, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416
				]

				__lowerCAmelCase		=   [
				    1_755, 1_061, 234, 1_755, 1_061, 1_755, 185, 290, 307, 307, 616, 616,
				    616, 616, 616, 616, 307, 290, 417, 1_755, 234, 1_755, 185, 290,
				    290, 290, 307, 616, 616, 616, 616, 616, 290, 234, 234, 1_755,
				    234, 234, 1_755, 234, 185, 185, 307, 616, 616, 616, 616, 290,
				    1_755, 1_755, 1_755, 234, 234, 1_755, 1_572, 290, 307, 616, 34, 616
				]
				__lowerCAmelCase		=   [
				    854, 842, 1_353, 114, 1_353, 842, 185, 842, 185, 114, 591, 842, 185,
				    417, 185, 842, 307, 842, 591, 842, 185, 842, 185, 842, 591, 842,
				    1_353, 842, 185, 842, 591, 842, 591, 114, 591, 842, 185, 842, 591,
				    89, 591, 842, 591, 842, 591, 417, 1_372, 842, 1_372, 842, 34, 842,
				    185, 89, 591, 842, 185, 842, 591, 632
				]

				__lowerCAmelCase		=   [
				    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653
				]
				__lowerCAmelCase		=   [
				    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
				    653, 653, 653, 653, 653, 653, 653, 1_853, 1_177, 1_536, 1_228,
				    710, 475, 1_489, 1_229, 1_224, 231, 1_224, 252, 1_434, 653, 475,
				    1_106, 1_877, 1_599, 1_228, 1_600, 1_683, 1_182, 1_853, 475, 1_864,
				    252, 1_229, 1_434, 2_001
				]

				__lowerCAmelCase		=   [
				    1_125, 1_125, 416, 1_125, 1_125, 416, 1_125, 1_125, 416, 416, 1_125, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
				    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416
				]
				__lowerCAmelCase		=   [
				    491, 1_755, 34, 1_613, 1_755, 417, 992, 1_613, 222, 842, 1_353, 1_613,
				    844, 632, 185, 1_613, 844, 632, 185, 1_613, 185, 842, 677, 1_613,
				    185, 114, 1_353, 1_613, 307, 89, 844, 1_613, 307, 1_332, 234, 1_979,
				    307, 89, 1_353, 616, 34, 842, 185, 842, 34, 842, 185, 842,
				    307, 114, 185, 89, 34, 1_268, 185, 89, 34, 842, 185, 89
				]
				def 			UpperCamelCase_    (	self  ,   _UpperCAmelCase   ):




										"""simple docstring"""




										__magic_name__					:				List[Any]				=   JukeboxTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE   )
										__magic_name__					:				Tuple				=   tokenizer(**self.metas   )['input_ids']
										return tokens
				@slow
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				Optional[Any]				=   JukeboxModel.from_pretrained(self.model_id  ,   min_duration=0   ).eval()
										__magic_name__					:				Dict				=   self.prepare_inputs(self.model_id   )

										set_seed(0   )
										__magic_name__					:				Dict				=   [torch.zeros(1  ,   0  ,   dtype=torch.long   ).cpu() for _ in range(3   )]
										__magic_name__					:				Union[str, Any]				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [0]  ,   sample_length=60 * model.priors[0].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										self.assertIn(zs[0][0].detach().cpu().tolist()  ,   [self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]   )

										set_seed(0   )
										__magic_name__					:				Optional[Any]				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [1]  ,   sample_length=60 * model.priors[1].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										self.assertIn(zs[1][0].detach().cpu().tolist()  ,   [self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]   )

										set_seed(0   )
										__magic_name__					:				Union[str, Any]				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [2]  ,   sample_length=60 * model.priors[2].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										self.assertIn(zs[2][0].detach().cpu().tolist()  ,   [self.EXPECTED_OUTPUT_0, self.EXPECTED_OUTPUT_0_PT_2]   )
				@slow
				@skip('Not enough GPU memory on CI runners'   )
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				Any				=   JukeboxModel.from_pretrained(self.model_id  ,   min_duration=0   ).eval()
										__magic_name__					:				Dict				=   [i.cuda() for i in self.prepare_inputs(self.model_id   )]

										set_seed(0   )
										model.priors[0].cuda()
										__magic_name__					:				Dict				=   [torch.zeros(1  ,   0  ,   dtype=torch.long   ).cuda() for _ in range(3   )]
										__magic_name__					:				Union[str, Any]				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [0]  ,   sample_length=60 * model.priors[0].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										torch.testing.assert_allclose(zs[0][0].cpu()  ,   torch.tensor(self.EXPECTED_GPU_OUTPUTS_2   )   )
										model.priors[0].cpu()

										set_seed(0   )
										model.priors[1].cuda()
										__magic_name__					:				Tuple				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [1]  ,   sample_length=60 * model.priors[1].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										torch.testing.assert_allclose(zs[1][0].cpu()  ,   torch.tensor(self.EXPECTED_GPU_OUTPUTS_1   )   )
										model.priors[1].cpu()

										set_seed(0   )
										model.priors[2].cuda()
										__magic_name__					:				Dict				=   model._sample(__SCREAMING_SNAKE_CASE  ,   __SCREAMING_SNAKE_CASE  ,   [2]  ,   sample_length=60 * model.priors[2].raw_to_tokens  ,   save_results=__SCREAMING_SNAKE_CASE   )
										torch.testing.assert_allclose(zs[2][0].cpu()  ,   torch.tensor(self.EXPECTED_GPU_OUTPUTS_0   )   )





				@slow
				def 			UpperCamelCase_    (	self   ):




										"""simple docstring"""




										__magic_name__					:				Any				=   'ArthurZ/jukebox_prior_0'
										__magic_name__					:				Any				=   JukeboxPrior.from_pretrained(__SCREAMING_SNAKE_CASE  ,   min_duration=0   ).eval().half().to('cuda'   )

										__magic_name__					:				Optional[Any]				=   self.prepare_inputs(__SCREAMING_SNAKE_CASE   )[0].cuda()
										__magic_name__					:				int				=   model.get_metadata(__SCREAMING_SNAKE_CASE  ,   0  ,   7680  ,   0   )
										set_seed(0   )
										__magic_name__					:				List[Any]				=   model.sample(1  ,   metadata=__SCREAMING_SNAKE_CASE  ,   sample_tokens=60   )
										self.assertIn(outputs[0].cpu().tolist()  ,   [self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]   )




'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase												=   {'configuration_sew_d': ['SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWDConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase												=   [
       'SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST',
       'SEWDForCTC',
       'SEWDForSequenceClassification',
       'SEWDModel',
       'SEWDPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_sew_d import (
          SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
          SEWDForCTC,
          SEWDForSequenceClassification,
          SEWDModel,
          SEWDPreTrainedModel,
      )


else:
   import sys

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


