


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							):
 SCREAMING_SNAKE_CASE__   = (JukeboxModel,) if is_torch_available() else ()
 SCREAMING_SNAKE_CASE__   = 'openai/jukebox-1b-lyrics'
 SCREAMING_SNAKE_CASE__   = {
     '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
 SCREAMING_SNAKE_CASE__   = [
     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
 ]

 SCREAMING_SNAKE_CASE__   = [
     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
 ]

 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]

 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]

 SCREAMING_SNAKE_CASE__   = [105_8304, 0, 78_6432, 7169, 507, 76, 27, 40, 30, 76]

 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     -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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Tuple											= JukeboxTokenizer.from_pretrained(self.model_id					)
       a		:List[str]											= tokenizer(**self.metas					)['''input_ids''']
       return tokens




 @slow
 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:List[Any]											= JukeboxModel.from_pretrained(self.model_id      ,						min_duration=0					).eval()
       a		:Optional[Any]											= self.prepare_inputs()

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

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

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




 @slow
 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:List[str]											= False
       a		:Union[str, Any]											= JukeboxModel.from_pretrained(self.model_id      ,						min_duration=0					).eval()

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

       a		:Tuple											= model.priors[0]
       a		:Dict											= 0
       a		:List[Any]											= top_prior.get_music_tokens_conds(_lowerCamelCase      ,						start=_lowerCamelCase      ,						end=start + top_prior.n_ctx					)
       a		:List[Any]											= top_prior.get_metadata(labels[0].clone()      ,						_lowerCamelCase      ,						105_8304      ,						0					)

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

       a							,       a							,       a		:List[Any]											= top_prior.get_cond(_lowerCamelCase      ,						_lowerCamelCase					)
       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  SCREAMING_SNAKE_CASE__       (	self					):
       a		:int											= False

       a		:List[Any]											= JukeboxModel.from_pretrained(self.model_id      ,						min_duration=0					).eval()
       set_seed(0					)
       a		:List[Any]											= torch.rand((1, 5120, 1)					)
       a		:Dict											= list(self.prepare_inputs()					)

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

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

       a		:Tuple											= torch.cat((zs[1], torch.zeros(1      ,						2048 - zs[1].shape[-1]					))      ,						dim=-1					).long()
       a		:Optional[int]											= [upper_a, upper_a, model.vqvae.encode(_lowerCamelCase      ,						start_level=0      ,						bs_chunks=waveform.shape[0]					)[0]]
       a		:Dict											= model._sample(
           _lowerCamelCase      ,						_lowerCamelCase      ,						sample_levels=[2]      ,						save_results=_lowerCamelCase      ,						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  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Union[str, Any]											= JukeboxModel.from_pretrained(self.model_id      ,						min_duration=0					).eval()
       set_seed(0					)
       a		:int											= torch.rand((1, 5120, 1)					)
       with torch.no_grad():
             a		:Tuple											= model.vqvae.encode(_lowerCamelCase      ,						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():
             a		:Dict											= model.vqvae.decode(_lowerCamelCase      ,						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							):
 SCREAMING_SNAKE_CASE__   = (JukeboxModel,) if is_torch_available() else ()
 SCREAMING_SNAKE_CASE__   = 'openai/jukebox-5b-lyrics'
 SCREAMING_SNAKE_CASE__   = {
     '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
 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]

 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]

 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]

 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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
 ]

 SCREAMING_SNAKE_CASE__   = [
     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
 ]
 SCREAMING_SNAKE_CASE__   = [
     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  SCREAMING_SNAKE_CASE__       (	self      ,						_lowerCamelCase					):
       a		:Optional[int]											= JukeboxTokenizer.from_pretrained(_lowerCamelCase					)
       a		:Tuple											= tokenizer(**self.metas					)['''input_ids''']
       return tokens




 @slow
 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Optional[Any]											= JukeboxModel.from_pretrained(self.model_id      ,						min_duration=0					).eval()
       a		:List[str]											= self.prepare_inputs(self.model_id					)

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

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

       set_seed(0					)
       a		:Tuple											= model._sample(_lowerCamelCase      ,						_lowerCamelCase      ,						[2]      ,						sample_length=60 * model.priors[2].raw_to_tokens      ,						save_results=_lowerCamelCase					)
       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  SCREAMING_SNAKE_CASE__       (	self					):
       a		:List[str]											= JukeboxModel.from_pretrained(self.model_id      ,						min_duration=0					).eval()
       a		:Optional[int]											= [i.cuda() for i in self.prepare_inputs(self.model_id					)]

       set_seed(0					)
       model.priors[0].cuda()
       a		:List[Any]											= [torch.zeros(1      ,						0      ,						dtype=torch.long					).cuda() for _ in range(3					)]
       a		:str											= model._sample(_lowerCamelCase      ,						_lowerCamelCase      ,						[0]      ,						sample_length=60 * model.priors[0].raw_to_tokens      ,						save_results=_lowerCamelCase					)
       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()
       a		:Dict											= model._sample(_lowerCamelCase      ,						_lowerCamelCase      ,						[1]      ,						sample_length=60 * model.priors[1].raw_to_tokens      ,						save_results=_lowerCamelCase					)
       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()
       a		:Optional[Any]											= model._sample(_lowerCamelCase      ,						_lowerCamelCase      ,						[2]      ,						sample_length=60 * model.priors[2].raw_to_tokens      ,						save_results=_lowerCamelCase					)
       torch.testing.assert_allclose(zs[2][0].cpu()      ,						torch.tensor(self.EXPECTED_GPU_OUTPUTS_0					)					)




 @slow
 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Dict											= '''ArthurZ/jukebox_prior_0'''
       a		:Tuple											= JukeboxPrior.from_pretrained(_lowerCamelCase      ,						min_duration=0					).eval().half().to('''cuda'''					)

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









import copy
from typing import Dict

from ...generation.configuration_utils import GenerationConfig
from ...utils import logging


snake_case       :					Dict        =  logging.get_logger(__name__)







class 	_snake_case						(   _snake_case							):
 SCREAMING_SNAKE_CASE__   = 'semantic'




 def __init__(	self      ,						_lowerCamelCase=1_0000      ,						_lowerCamelCase=True      ,						_lowerCamelCase=768      ,						_lowerCamelCase=False      ,						_lowerCamelCase=False      ,						_lowerCamelCase=False      ,						_lowerCamelCase=False      ,						_lowerCamelCase=0.7      ,						_lowerCamelCase=True      ,						_lowerCamelCase=1_0048      ,						_lowerCamelCase=12_9595      ,						_lowerCamelCase=12_9599      ,						_lowerCamelCase=1_0000      ,						_lowerCamelCase=256      ,						_lowerCamelCase=49.9      ,						**_lowerCamelCase      ,						):
       super().__init__(
           temperature=_lowerCamelCase      ,						do_sample=_lowerCamelCase      ,						eos_token_id=_lowerCamelCase      ,						renormalize_logits=_lowerCamelCase      ,						max_new_tokens=_lowerCamelCase      ,						output_scores=_lowerCamelCase      ,						return_dict_in_generate=_lowerCamelCase      ,						output_hidden_states=_lowerCamelCase      ,						output_attentions=_lowerCamelCase      ,						**_lowerCamelCase      ,						)

       a		:Dict											= text_encoding_offset
       a		:Any											= text_pad_token
       a		:List[Any]											= eos_token_id
       a		:str											= semantic_infer_token
       a		:Any											= semantic_vocab_size
       a		:Any											= max_input_semantic_length
       a		:Dict											= semantic_rate_hz







class 	_snake_case						(   _snake_case							):
 SCREAMING_SNAKE_CASE__   = 'coarse_acoustics'




 def __init__(	self      ,						_lowerCamelCase=True      ,						_lowerCamelCase=False      ,						_lowerCamelCase=False      ,						_lowerCamelCase=False      ,						_lowerCamelCase=False      ,						_lowerCamelCase=0.7      ,						_lowerCamelCase=True      ,						_lowerCamelCase=1_2048      ,						_lowerCamelCase=75      ,						_lowerCamelCase=2      ,						_lowerCamelCase=1_2050      ,						_lowerCamelCase=256      ,						_lowerCamelCase = 630      ,						_lowerCamelCase = 60      ,						**_lowerCamelCase      ,						):
       super().__init__(
           temperature=_lowerCamelCase      ,						do_sample=_lowerCamelCase      ,						renormalize_logits=_lowerCamelCase      ,						output_scores=_lowerCamelCase      ,						return_dict_in_generate=_lowerCamelCase      ,						output_hidden_states=_lowerCamelCase      ,						output_attentions=_lowerCamelCase      ,						**_lowerCamelCase      ,						)

       a		:Optional[Any]											= coarse_semantic_pad_token
       a		:Dict											= coarse_rate_hz
       a		:List[str]											= n_coarse_codebooks
       a		:List[Any]											= coarse_infer_token
       a		:Optional[Any]											= max_coarse_input_length
       a		:Any											= max_coarse_history
       a		:Optional[int]											= sliding_window_len







class 	_snake_case						(   _snake_case							):
 SCREAMING_SNAKE_CASE__   = 'fine_acoustics'




 def __init__(	self      ,						_lowerCamelCase=0.5      ,						_lowerCamelCase=512      ,						_lowerCamelCase=1024      ,						_lowerCamelCase=8      ,						**_lowerCamelCase      ,						):
       super().__init__(temperature=_lowerCamelCase					)

       a		:Union[str, Any]											= max_fine_history_length
       a		:int											= max_fine_input_length
       a		:str											= n_fine_codebooks







class 	_snake_case						(   _snake_case							):
 SCREAMING_SNAKE_CASE__   = 'bark'
 SCREAMING_SNAKE_CASE__   = True




 def __init__(	self      ,						_lowerCamelCase = None      ,						_lowerCamelCase = None      ,						_lowerCamelCase = None      ,						_lowerCamelCase=2_4000      ,						_lowerCamelCase=1024      ,						**_lowerCamelCase      ,						):
       if semantic_config is None:
             a		:str											= {}
             logger.info('''semantic_config is None. initializing the semantic model with default values.'''					)

       if coarse_acoustics_config is None:
             a		:List[str]											= {}
             logger.info('''coarse_acoustics_config is None. initializing the coarse model with default values.'''					)

       if fine_acoustics_config is None:
             a		:Any											= {}
             logger.info('''fine_acoustics_config is None. initializing the fine model with default values.'''					)

       a		:Any											= BarkSemanticGenerationConfig(**_lowerCamelCase					)
       a		:int											= BarkCoarseGenerationConfig(**_lowerCamelCase					)
       a		:Optional[int]											= BarkFineGenerationConfig(**_lowerCamelCase					)

       a		:Tuple											= sample_rate
       a		:Dict											= codebook_size




 @classmethod
 def  SCREAMING_SNAKE_CASE__       (	cls      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						**_lowerCamelCase      ,						):
       return cls(
           semantic_config=semantic_config.to_dict()      ,						coarse_acoustics_config=coarse_acoustics_config.to_dict()      ,						fine_acoustics_config=fine_acoustics_config.to_dict()      ,						**_lowerCamelCase      ,						)




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:int											= copy.deepcopy(self.__dict__					)

       a		:List[Any]											= self.semantic_config.to_dict()
       a		:Union[str, Any]											= self.coarse_acoustics_config.to_dict()
       a		:int											= self.fine_acoustics_config.to_dict()

       a		:Tuple											= self.__class__.model_type
       return output





