


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  lowerCamelCase__  (			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,
    Who said "Two vast and trunkless legs of stone
    Stand in the desert. . . . Near them, on the sand,
    Half sunk a shattered visage lies, whose frown,
    And wrinkled lip, and sneer of cold command,
    Tell that its sculptor well those passions read
    Which yet survive, stamped on these lifeless things,
    The hand that mocked them, and the heart that fed;
    And on the pedestal, these words appear:
    My name is Ozymandias, King of Kings;
    Look on my Works, ye Mighty, and despair!
    Nothing beside remains. Round the decay
    Of that colossal Wreck, boundless and bare
    The lone and level sands stretch far away
    ''',
     }
     # 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__      =     [1058304, 0, 786432, 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__      =     [
         -0.0_492, -0.0_524, -0.0_565, -0.0_640, -0.0_686, -0.0_684, -0.0_677, -0.0_664,
         -0.0_605, -0.0_490, -0.0_330, -0.0_168, -0.0_083, -0.0_075, -0.0_051, 0.0_025,
         0.0_136, 0.0_261, 0.0_386, 0.0_497, 0.0_580, 0.0_599, 0.0_583, 0.0_614,
         0.0_740, 0.0_889, 0.1_023, 0.1_162, 0.1_211, 0.1_212, 0.1_251, 0.1_336,
         0.1_502, 0.1_686, 0.1_883, 0.2_148, 0.2_363, 0.2_458, 0.2_507, 0.2_531
     ]
     SCREAMING_SNAKE_CASE__      =     [
         0.0_256, -0.0_544, 0.1_600, -0.0_032, 0.1_066, 0.0_825, -0.0_013, 0.3_440,
         0.0_210, 0.0_412, -0.1_777, -0.0_892, -0.0_164, 0.0_285, -0.0_613, -0.0_617,
         -0.0_137, -0.0_201, -0.0_175, 0.0_215, -0.0_627, 0.0_520, -0.0_730, 0.0_970,
         -0.0_100, 0.0_442, -0.0_586, 0.0_207, -0.0_015, -0.0_082
     ]
     SCREAMING_SNAKE_CASE__      =     [
         0.0_415, 0.0_877, 0.0_022, -0.0_055, 0.0_751, 0.0_334, 0.0_324, -0.0_068,
         0.0_011, 0.0_017, -0.0_676, 0.0_655, -0.0_143, 0.0_399, 0.0_303, 0.0_743,
         -0.0_168, -0.0_394, -0.1_113, 0.0_124, 0.0_442, 0.0_267, -0.0_003, -0.1_536,
         -0.0_116, -0.1_837, -0.0_180, -0.1_026, -0.0_777, -0.0_456
     ]
     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 	__A   (self			)	->  Optional[Any]:
      _lowercase				 =JukeboxTokenizer.from_pretrained(self.model_id			)
      _lowercase				 =tokenizer(**self.metas			)['''input_ids''']
      return tokens





     @slow
     def 	__A   (self			)	->  Any:
      _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=4_0 * 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=4_0 * 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=4_0 * 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			)	->  Any:
      _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_0_5_8_3_0_4						,	0			)

      self.assertIsNone(UpperCAmelCase			)
      self.assertListEqual(metadata.numpy()[0][:1_0].tolist()						,	self.EXPECTED_Y_COND			)

      _lowercase ,       _lowercase ,       _lowercase				 =top_prior.get_cond(UpperCAmelCase						,	UpperCAmelCase			)
      torch.testing.assert_allclose(
          audio_conditioning[0][0][:3_0].detach()						,	torch.tensor(self.EXPECTED_AUDIO_COND			)						,	atol=1e-4						,	rtol=1e-4			)
      torch.testing.assert_allclose(
          metadata_conditioning[0][0][:3_0].detach()						,	torch.tensor(self.EXPECTED_META_COND			)						,	atol=1e-4						,	rtol=1e-4			)
      torch.testing.assert_allclose(
          lyric_tokens[0, :3_0].detach()						,	torch.tensor(self.EXPECTED_LYRIC_COND			)						,	atol=1e-4						,	rtol=1e-4			)





     @slow
     def 	__A   (self			)	->  Tuple:
      _lowercase				 =False

      _lowercase				 =JukeboxModel.from_pretrained(self.model_id						,	min_duration=0			).eval()
      set_seed(0			)
      _lowercase				 =torch.rand((1, 5_1_2_0, 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=4_0 * model.priors[0].raw_to_tokens			)
      torch.testing.assert_allclose(zs[0][0][:4_0]						,	torch.tensor(self.EXPECTED_PRIMED_0			)			)

      _lowercase				 =torch.cat((zs[0], torch.zeros(1						,	2_0_4_8 - 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=4_0 * model.priors[1].raw_to_tokens			)
      torch.testing.assert_allclose(zs[1][0][:4_0]						,	torch.tensor(self.EXPECTED_PRIMED_1			)			)

      _lowercase				 =torch.cat((zs[1], torch.zeros(1						,	2_0_4_8 - 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=4_0 * model.priors[2].raw_to_tokens			)
      torch.testing.assert_allclose(zs[2][0][:4_0].cpu()						,	torch.tensor(self.EXPECTED_PRIMED_2			)			)





     @slow
     def 	__A   (self			)	->  Any:
      _lowercase				 =JukeboxModel.from_pretrained(self.model_id						,	min_duration=0			).eval()
      set_seed(0			)
      _lowercase				 =torch.rand((1, 5_1_2_0, 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, :4_0, 0]						,	torch.tensor(self.EXPECTED_VQVAE_DECODE			)						,	atol=1e-4						,	rtol=1e-4			)







@require_torch
class  lowerCamelCase__  (			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,
    Who said "Two vast and trunkless legs of stone
    Stand in the desert. . . . Near them, on the sand,
    Half sunk a shattered visage lies, whose frown,
    And wrinkled lip, and sneer of cold command,
    Tell that its sculptor well those passions read
    Which yet survive, stamped on these lifeless things,
    The hand that mocked them, and the heart that fed;
    And on the pedestal, these words appear:
    My name is Ozymandias, King of Kings;
    Look on my Works, ye Mighty, and despair!
    Nothing beside remains. Round the decay
    Of that colossal Wreck, boundless and bare
    The lone and level sands stretch far away
    ''',
     }

     # 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 	__A   (self						,	UpperCAmelCase			)	->  List[Any]:
      _lowercase				 =JukeboxTokenizer.from_pretrained(UpperCAmelCase			)
      _lowercase				 =tokenizer(**self.metas			)['''input_ids''']
      return tokens





     @slow
     def 	__A   (self			)	->  Any:
      _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=6_0 * 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=6_0 * 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=6_0 * 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			)	->  Any:
      _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=6_0 * 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=6_0 * 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=6_0 * 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			)	->  Tuple:
      _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						,	7_6_8_0						,	0			)
      set_seed(0			)
      _lowercase				 =model.sample(1						,	metadata=UpperCAmelCase						,	sample_tokens=6_0			)
      self.assertIn(outputs[0].cpu().tolist()						,	[self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]			)





from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import PNDMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput







class  lowerCamelCase__  (			lowerCAmelCase):
     SCREAMING_SNAKE_CASE__      =     42
     SCREAMING_SNAKE_CASE__      =     42





     def __init__(self						,	UpperCAmelCase						,	UpperCAmelCase			)	->  Tuple:
      super().__init__()

      _lowercase				 =PNDMScheduler.from_config(scheduler.config			)

      self.register_modules(unet=UpperCAmelCase						,	scheduler=UpperCAmelCase			)





     @torch.no_grad()
     def __call__(self						,	UpperCAmelCase = 1						,	UpperCAmelCase = 5_0						,	UpperCAmelCase = None						,	UpperCAmelCase = "pil"						,	UpperCAmelCase = True						,	**UpperCAmelCase						,	)	->  Union[ImagePipelineOutput, Tuple]:
      _lowercase				 =randn_tensor(
          (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)						,	generator=UpperCAmelCase						,	device=self.device						,	)

      self.scheduler.set_timesteps(UpperCAmelCase			)
      for t in self.progress_bar(self.scheduler.timesteps			):
       _lowercase				 =self.unet(UpperCAmelCase						,	UpperCAmelCase			).sample

       _lowercase				 =self.scheduler.step(UpperCAmelCase						,	UpperCAmelCase						,	UpperCAmelCase			).prev_sample

      _lowercase				 =(image / 2 + 0.5).clamp(0						,	1			)
      _lowercase				 =image.cpu().permute(0						,	2						,	3						,	1			).numpy()
      if output_type == "pil":
       _lowercase				 =self.numpy_to_pil(UpperCAmelCase			)

      if not return_dict:
       return (image,)

      return ImagePipelineOutput(images=UpperCAmelCase			)

