
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       A__  (		unittest.TestCase							):
							lowerCAmelCase__						:		str            =				(JukeboxModel,) if is_torch_available() else ()
							lowerCAmelCase__						:		List[str]            =				"openai/jukebox-1b-lyrics"
							lowerCAmelCase__						:		List[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    ",
							}
							# fmt: off
							lowerCAmelCase__						:		Any            =				[
							    1864, 1536, 1213, 1870, 1357, 1536, 519, 880, 1323, 789, 1082, 534,
							    1000, 1445, 1105, 1130, 967, 515, 1434, 1620, 534, 1495, 283, 1445,
							    333, 1307, 539, 1631, 1528, 375, 1434, 673, 627, 710, 778, 1883,
							    1405, 1276, 1455, 1228
							]

							lowerCAmelCase__						:		List[str]            =				[
							    1489, 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__						:		List[str]            =				[
							    1125, 1751, 697, 1776, 1141, 1476, 391, 697, 1125, 684, 867, 416,
							    844, 1372, 1274, 717, 1274, 844, 1299, 1419, 697, 1370, 317, 1125,
							    191, 1440, 1370, 1440, 1370, 282, 1621, 1370, 368, 349, 867, 1872,
							    1262, 869, 1728, 747
							]
							lowerCAmelCase__						:		Any            =				[
							    416, 416, 1125, 1125, 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__						:		Any            =				[
							    1755, 842, 307, 1843, 1022, 1395, 234, 1554, 806, 739, 1022, 442,
							    616, 556, 268, 1499, 933, 457, 1440, 1837, 755, 985, 308, 902,
							    293, 1443, 1671, 1141, 1533, 555, 1562, 1061, 287, 417, 1022, 2008,
							    1186, 1015, 1777, 268
							]
							lowerCAmelCase__						:		List[Any]            =				[
							    854, 842, 1353, 114, 1353, 842, 185, 842, 185, 114, 591, 842,
							    185, 417, 185, 842, 307, 842, 591, 842, 185, 842, 307, 842,
							    591, 842, 1353, 842, 185, 842, 591, 842, 591, 114, 591, 842,
							    185, 842, 591, 89
							]

							lowerCAmelCase__						:		Any            =				[1058304, 0, 786432, 7169, 507, 76, 27, 40, 30, 76]

							lowerCAmelCase__						:		Union[str, Any]            =				[
							    390, 1160, 1002, 1907, 1788, 1788, 1788, 1907, 1002, 1002, 1854, 1002,
							    1002, 1002, 1002, 1002, 1002, 1160, 1160, 1606, 596, 596, 1160, 1002,
							    1516, 596, 1002, 1002, 1002, 1907, 1788, 1788, 1788, 1854, 1788, 1907,
							    1907, 1788, 596, 1626
							]
							lowerCAmelCase__						:		Optional[Any]            =				[
							    1236, 1668, 1484, 1920, 1848, 1409, 139, 864, 1828, 1272, 1599, 824,
							    1672, 139, 555, 1484, 824, 1920, 555, 596, 1579, 1599, 1231, 1599,
							    1637, 1407, 212, 824, 1599, 116, 1433, 824, 258, 1599, 1433, 1895,
							    1063, 1433, 1433, 1599
							]
							lowerCAmelCase__						:		int            =				[
							    1684, 1873, 1119, 1189, 395, 611, 1901, 972, 890, 1337, 1392, 1927,
							    96, 972, 672, 780, 1119, 890, 158, 771, 1073, 1927, 353, 1331,
							    1269, 1459, 1333, 1645, 812, 1577, 1337, 606, 353, 981, 1466, 619,
							    197, 391, 302, 1930
							]
							lowerCAmelCase__						:		Any            =				[
							    390, 1160, 1002, 1907, 1788, 1788, 1788, 1907, 1002, 1002, 1854, 1002,
							    1002, 1002, 1002, 1002, 1002, 1160, 1160, 1606, 596, 596, 1160, 1002,
							    1516, 596, 1002, 1002, 1002, 1907, 1788, 1788, 1788, 1854, 1788, 1907,
							    1907, 1788, 596, 1626
							]
							lowerCAmelCase__						:		List[Any]            =				[
							    -0.0492, -0.0524, -0.0565, -0.0640, -0.0686, -0.0684, -0.0677, -0.0664,
							    -0.0605, -0.0490, -0.0330, -0.0168, -0.0083, -0.0075, -0.0051, 0.0025,
							    0.0136, 0.0261, 0.0386, 0.0497, 0.0580, 0.0599, 0.0583, 0.0614,
							    0.0740, 0.0889, 0.1023, 0.1162, 0.1211, 0.1212, 0.1251, 0.1336,
							    0.1502, 0.1686, 0.1883, 0.2148, 0.2363, 0.2458, 0.2507, 0.2531
							]
							lowerCAmelCase__						:		List[str]            =				[
							    0.0256, -0.0544, 0.1600, -0.0032, 0.1066, 0.0825, -0.0013, 0.3440,
							    0.0210, 0.0412, -0.1777, -0.0892, -0.0164, 0.0285, -0.0613, -0.0617,
							    -0.0137, -0.0201, -0.0175, 0.0215, -0.0627, 0.0520, -0.0730, 0.0970,
							    -0.0100, 0.0442, -0.0586, 0.0207, -0.0015, -0.0082
							]
							lowerCAmelCase__						:		int            =				[
							    0.0415, 0.0877, 0.0022, -0.0055, 0.0751, 0.0334, 0.0324, -0.0068,
							    0.0011, 0.0017, -0.0676, 0.0655, -0.0143, 0.0399, 0.0303, 0.0743,
							    -0.0168, -0.0394, -0.1113, 0.0124, 0.0442, 0.0267, -0.0003, -0.1536,
							    -0.0116, -0.1837, -0.0180, -0.1026, -0.0777, -0.0456
							]
							lowerCAmelCase__						:		Dict            =				[
							    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      a__					(					self    :  Dict							)		->						Optional[Any]:



											"""simple docstring"""


											__lowercase								=   JukeboxTokenizer.from_pretrained(self.model_id							)
											__lowercase								=   tokenizer(**self.metas							)['input_ids']
											return tokens





							@slow
							def      a__					(					self    :  Dict							)		->						int:



											"""simple docstring"""


											__lowercase								=   JukeboxModel.from_pretrained(self.model_id	,					min_duration=0							).eval()
											__lowercase								=   self.prepare_inputs()

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

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

											set_seed(0							)
											__lowercase								=   model._sample(_UpperCAmelCase	,					_UpperCAmelCase	,					[2]	,					sample_length=40 * model.priors[2].raw_to_tokens	,					save_results=_UpperCAmelCase							)
											self.assertIn(zs[2][0].detach().cpu().tolist()	,					[self.EXPECTED_OUTPUT_0, self.EXPECTED_OUTPUT_0_PT_2]							)





							@slow
							def      a__					(					self    :  Optional[int]							)		->						Dict:



											"""simple docstring"""


											__lowercase								=   False
											__lowercase								=   JukeboxModel.from_pretrained(self.model_id	,					min_duration=0							).eval()

											__lowercase								=   self.prepare_inputs()
											set_seed(0							)
											__lowercase								=   [torch.zeros(1	,					0	,					dtype=torch.long							) for _ in range(3							)]

											__lowercase								=   model.priors[0]
											__lowercase								=   0
											__lowercase								=   top_prior.get_music_tokens_conds(_UpperCAmelCase	,					start=_UpperCAmelCase	,					end=start + top_prior.n_ctx							)
											__lowercase								=   top_prior.get_metadata(labels[0].clone()	,					_UpperCAmelCase	,					1_05_83_04	,					0							)

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

											__lowercase						,   __lowercase						,   __lowercase								=   top_prior.get_cond(_UpperCAmelCase	,					_UpperCAmelCase							)
											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      a__					(					self    :  Union[str, Any]							)		->						Optional[int]:



											"""simple docstring"""


											__lowercase								=   False

											__lowercase								=   JukeboxModel.from_pretrained(self.model_id	,					min_duration=0							).eval()
											set_seed(0							)
											__lowercase								=   torch.rand((1, 51_20, 1)							)
											__lowercase								=   list(self.prepare_inputs()							)

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

											__lowercase								=   torch.cat((zs[0], torch.zeros(1	,					20_48 - zs[0].shape[-1]							))	,					dim=-1							).long()
											__lowercase								=   [upper_a, model.vqvae.encode(_UpperCAmelCase	,					start_level=1	,					bs_chunks=waveform.shape[0]							)[0], None]
											__lowercase								=   model._sample(
											    _UpperCAmelCase	,					_UpperCAmelCase	,					sample_levels=[1]	,					save_results=_UpperCAmelCase	,					sample_length=40 * model.priors[1].raw_to_tokens							)
											torch.testing.assert_allclose(zs[1][0][:40]	,					torch.tensor(self.EXPECTED_PRIMED_1							)							)

											__lowercase								=   torch.cat((zs[1], torch.zeros(1	,					20_48 - zs[1].shape[-1]							))	,					dim=-1							).long()
											__lowercase								=   [upper_a, upper_a, model.vqvae.encode(_UpperCAmelCase	,					start_level=0	,					bs_chunks=waveform.shape[0]							)[0]]
											__lowercase								=   model._sample(
											    _UpperCAmelCase	,					_UpperCAmelCase	,					sample_levels=[2]	,					save_results=_UpperCAmelCase	,					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      a__					(					self    :  List[str]							)		->						int:



											"""simple docstring"""


											__lowercase								=   JukeboxModel.from_pretrained(self.model_id	,					min_duration=0							).eval()
											set_seed(0							)
											__lowercase								=   torch.rand((1, 51_20, 1)							)
											with torch.no_grad():
															__lowercase								=   model.vqvae.encode(_UpperCAmelCase	,					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():
															__lowercase								=   model.vqvae.decode(_UpperCAmelCase	,					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       A__  (		unittest.TestCase							):
							lowerCAmelCase__						:		List[Any]            =				(JukeboxModel,) if is_torch_available() else ()
							lowerCAmelCase__						:		int            =				"openai/jukebox-5b-lyrics"
							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    ",
							}

							# fmt: off
							lowerCAmelCase__						:		Optional[Any]            =				[
							    1489, 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,
							    1489, 1489, 1489, 1489, 1150, 1853, 1509, 1150, 1357, 1509, 6, 1272
							]
							lowerCAmelCase__						:		Any            =				[
							    1489, 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__						:		Union[str, Any]            =				[
							    1125, 416, 1125, 1125, 1125, 1125, 1125, 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__						:		Tuple            =				[
							    416, 416, 1125, 1125, 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__						:		Any            =				[
							    1755, 1061, 234, 1755, 1061, 1755, 185, 290, 307, 307, 616, 616,
							    616, 616, 616, 616, 307, 290, 417, 1755, 234, 1755, 185, 290,
							    290, 290, 307, 616, 616, 616, 616, 616, 290, 234, 234, 1755,
							    234, 234, 1755, 234, 185, 185, 307, 616, 616, 616, 616, 290,
							    1755, 1755, 1755, 234, 234, 1755, 1572, 290, 307, 616, 34, 616
							]
							lowerCAmelCase__						:		str            =				[
							    854, 842, 1353, 114, 1353, 842, 185, 842, 185, 114, 591, 842, 185,
							    417, 185, 842, 307, 842, 591, 842, 185, 842, 185, 842, 591, 842,
							    1353, 842, 185, 842, 591, 842, 591, 114, 591, 842, 185, 842, 591,
							    89, 591, 842, 591, 842, 591, 417, 1372, 842, 1372, 842, 34, 842,
							    185, 89, 591, 842, 185, 842, 591, 632
							]

							lowerCAmelCase__						:		List[Any]            =				[
							    1489, 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__						:		Any            =				[
							    1489, 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, 1853, 1177, 1536, 1228,
							    710, 475, 1489, 1229, 1224, 231, 1224, 252, 1434, 653, 475,
							    1106, 1877, 1599, 1228, 1600, 1683, 1182, 1853, 475, 1864,
							    252, 1229, 1434, 2001
							]

							lowerCAmelCase__						:		int            =				[
							    1125, 1125, 416, 1125, 1125, 416, 1125, 1125, 416, 416, 1125, 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__						:		int            =				[
							    491, 1755, 34, 1613, 1755, 417, 992, 1613, 222, 842, 1353, 1613,
							    844, 632, 185, 1613, 844, 632, 185, 1613, 185, 842, 677, 1613,
							    185, 114, 1353, 1613, 307, 89, 844, 1613, 307, 1332, 234, 1979,
							    307, 89, 1353, 616, 34, 842, 185, 842, 34, 842, 185, 842,
							    307, 114, 185, 89, 34, 1268, 185, 89, 34, 842, 185, 89
							]





							def      a__					(					self    :  Optional[int]	,					_UpperCAmelCase    :  List[str]							)		->						Dict:



											"""simple docstring"""


											__lowercase								=   JukeboxTokenizer.from_pretrained(_UpperCAmelCase							)
											__lowercase								=   tokenizer(**self.metas							)['input_ids']
											return tokens





							@slow
							def      a__					(					self    :  List[Any]							)		->						Dict:



											"""simple docstring"""


											__lowercase								=   JukeboxModel.from_pretrained(self.model_id	,					min_duration=0							).eval()
											__lowercase								=   self.prepare_inputs(self.model_id							)

											set_seed(0							)
											__lowercase								=   [torch.zeros(1	,					0	,					dtype=torch.long							).cpu() for _ in range(3							)]
											__lowercase								=   model._sample(_UpperCAmelCase	,					_UpperCAmelCase	,					[0]	,					sample_length=60 * model.priors[0].raw_to_tokens	,					save_results=_UpperCAmelCase							)
											self.assertIn(zs[0][0].detach().cpu().tolist()	,					[self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]							)

											set_seed(0							)
											__lowercase								=   model._sample(_UpperCAmelCase	,					_UpperCAmelCase	,					[1]	,					sample_length=60 * model.priors[1].raw_to_tokens	,					save_results=_UpperCAmelCase							)
											self.assertIn(zs[1][0].detach().cpu().tolist()	,					[self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]							)

											set_seed(0							)
											__lowercase								=   model._sample(_UpperCAmelCase	,					_UpperCAmelCase	,					[2]	,					sample_length=60 * model.priors[2].raw_to_tokens	,					save_results=_UpperCAmelCase							)
											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      a__					(					self    :  int							)		->						Tuple:



											"""simple docstring"""


											__lowercase								=   JukeboxModel.from_pretrained(self.model_id	,					min_duration=0							).eval()
											__lowercase								=   [i.cuda() for i in self.prepare_inputs(self.model_id							)]

											set_seed(0							)
											model.priors[0].cuda()
											__lowercase								=   [torch.zeros(1	,					0	,					dtype=torch.long							).cuda() for _ in range(3							)]
											__lowercase								=   model._sample(_UpperCAmelCase	,					_UpperCAmelCase	,					[0]	,					sample_length=60 * model.priors[0].raw_to_tokens	,					save_results=_UpperCAmelCase							)
											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()
											__lowercase								=   model._sample(_UpperCAmelCase	,					_UpperCAmelCase	,					[1]	,					sample_length=60 * model.priors[1].raw_to_tokens	,					save_results=_UpperCAmelCase							)
											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()
											__lowercase								=   model._sample(_UpperCAmelCase	,					_UpperCAmelCase	,					[2]	,					sample_length=60 * model.priors[2].raw_to_tokens	,					save_results=_UpperCAmelCase							)
											torch.testing.assert_allclose(zs[2][0].cpu()	,					torch.tensor(self.EXPECTED_GPU_OUTPUTS_0							)							)





							@slow
							def      a__					(					self    :  Union[str, Any]							)		->						Optional[Any]:



											"""simple docstring"""


											__lowercase								=   'ArthurZ/jukebox_prior_0'
											__lowercase								=   JukeboxPrior.from_pretrained(_UpperCAmelCase	,					min_duration=0							).eval().half().to('cuda'							)

											__lowercase								=   self.prepare_inputs(_UpperCAmelCase							)[0].cuda()
											__lowercase								=   model.get_metadata(_UpperCAmelCase	,					0	,					76_80	,					0							)
											set_seed(0							)
											__lowercase								=   model.sample(1	,					metadata=_UpperCAmelCase	,					sample_tokens=60							)
											self.assertIn(outputs[0].cpu().tolist()	,					[self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]							)







# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__				=							{
    """agents""": ["""Agent""", """AzureOpenAiAgent""", """HfAgent""", """LocalAgent""", """OpenAiAgent"""],
    """base""": ["""PipelineTool""", """RemoteTool""", """Tool""", """launch_gradio_demo""", """load_tool"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__				=							["""DocumentQuestionAnsweringTool"""]
							SCREAMING_SNAKE_CASE__				=							["""ImageCaptioningTool"""]
							SCREAMING_SNAKE_CASE__				=							["""ImageQuestionAnsweringTool"""]
							SCREAMING_SNAKE_CASE__				=							["""ImageSegmentationTool"""]
							SCREAMING_SNAKE_CASE__				=							["""SpeechToTextTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TextClassificationTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TextQuestionAnsweringTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TextSummarizationTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TextToSpeechTool"""]
							SCREAMING_SNAKE_CASE__				=							["""TranslationTool"""]

if TYPE_CHECKING:
							from .agents import Agent, AzureOpenAiAgent, HfAgent, LocalAgent, OpenAiAgent
							from .base import PipelineTool, RemoteTool, Tool, launch_gradio_demo, load_tool

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .document_question_answering import DocumentQuestionAnsweringTool
														from .image_captioning import ImageCaptioningTool
														from .image_question_answering import ImageQuestionAnsweringTool
														from .image_segmentation import ImageSegmentationTool
														from .speech_to_text import SpeechToTextTool
														from .text_classification import TextClassificationTool
														from .text_question_answering import TextQuestionAnsweringTool
														from .text_summarization import TextSummarizationTool
														from .text_to_speech import TextToSpeechTool
														from .translation import TranslationTool
else:
							import sys

							SCREAMING_SNAKE_CASE__				=							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





