




'''simple docstring'''


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							):







  '''simple docstring'''

  UpperCamelCase_			:      Dict										=				(JukeboxModel,) if is_torch_available() else ()
  UpperCamelCase_			:      List[str]										=				"""openai/jukebox-1b-lyrics"""
  UpperCamelCase_			:      Tuple										=				{
      """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
  UpperCamelCase_			:      List[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
  ]

  UpperCamelCase_			:      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
  ]

  UpperCamelCase_			:      Any										=				[
      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
  ]
  UpperCamelCase_			:      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
  ]

  UpperCamelCase_			:      Tuple										=				[
      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
  ]
  UpperCamelCase_			:      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
  ]

  UpperCamelCase_			:      int										=				[105_8304, 0, 78_6432, 7169, 507, 76, 27, 40, 30, 76]

  UpperCamelCase_			:      str										=				[
      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
  ]
  UpperCamelCase_			:      List[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
  ]
  UpperCamelCase_			:      str										=				[
      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
  ]
  UpperCamelCase_			:      Tuple										=				[
      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
  ]
  UpperCamelCase_			:      List[Any]										=				[
      -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
  ]
  UpperCamelCase_			:      Optional[Any]										=				[
      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
  ]
  UpperCamelCase_			:      int										=				[
      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
  ]
  UpperCamelCase_			:      int										=				[
      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 					_snake_case     ( self				:							Optional[int]	)			->		int:







       '''simple docstring'''



       A:		Optional[Any]          =		JukeboxTokenizer.from_pretrained(self.model_id	)
       A:		List[str]          =		tokenizer(**self.metas	)['input_ids']
       return tokens



  @slow
  def 					_snake_case     ( self				:							Any	)			->		int:







       '''simple docstring'''



       A:		str          =		JukeboxModel.from_pretrained(self.model_id					,  min_duration=0	).eval()
       A:		Dict          =		self.prepare_inputs()

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

       set_seed(0	)
       A:		Any          =		model._sample(__a					,  __a					,  [1]					,  sample_length=40 * model.priors[1].raw_to_tokens					,  save_results=__a	)
       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(__a					,  __a					,  [2]					,  sample_length=40 * model.priors[2].raw_to_tokens					,  save_results=__a	)
       self.assertIn(zs[2][0].detach().cpu().tolist()					,  [self.EXPECTED_OUTPUT_0, self.EXPECTED_OUTPUT_0_PT_2]	)



  @slow
  def 					_snake_case     ( self				:							Union[str, Any]	)			->		int:







       '''simple docstring'''



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

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

       A:		Union[str, Any]          =		model.priors[0]
       A:		int          =		0
       A:		Optional[int]          =		top_prior.get_music_tokens_conds(__a					,  start=__a					,  end=start + top_prior.n_ctx	)
       A:		Optional[Any]          =		top_prior.get_metadata(labels[0].clone()					,  __a					,  1_05_83_04					,  0	)

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

       A:		Dict          =		top_prior.get_cond(__a					,  __a	)
       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 					_snake_case     ( self				:							int	)			->		List[str]:







       '''simple docstring'''



       A:		Union[str, Any]          =		False

       A:		List[str]          =		JukeboxModel.from_pretrained(self.model_id					,  min_duration=0	).eval()
       set_seed(0	)
       A:		List[str]          =		torch.rand((1, 51_20, 1)	)
       A:		List[str]          =		list(self.prepare_inputs()	)

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

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

       A:		Any          =		torch.cat((zs[1], torch.zeros(1					,  20_48 - zs[1].shape[-1]	))					,  dim=-1	).long()
       A:		Union[str, Any]          =		[upper_a, upper_a, model.vqvae.encode(__a					,  start_level=0					,  bs_chunks=waveform.shape[0]	)[0]]
       A:		Optional[int]          =		model._sample(
           __a					,  __a					,  sample_levels=[2]					,  save_results=__a					,  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 					_snake_case     ( self				:							Optional[int]	)			->		str:







       '''simple docstring'''



       A:		Tuple          =		JukeboxModel.from_pretrained(self.model_id					,  min_duration=0	).eval()
       set_seed(0	)
       A:		List[str]          =		torch.rand((1, 51_20, 1)	)
       with torch.no_grad():
            A:		Tuple          =		model.vqvae.encode(__a					,  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:		Optional[Any]          =		model.vqvae.decode(__a					,  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 						lowerCAmelCase_	(       unittest.TestCase							):







  '''simple docstring'''

  UpperCamelCase_			:      Optional[Any]										=				(JukeboxModel,) if is_torch_available() else ()
  UpperCamelCase_			:      Any										=				"""openai/jukebox-5b-lyrics"""
  UpperCamelCase_			:      List[str]										=				{
      """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
  UpperCamelCase_			:      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,
      1489, 1489, 1489, 1489, 1150, 1853, 1509, 1150, 1357, 1509, 6, 1272
  ]
  UpperCamelCase_			:      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
  ]

  UpperCamelCase_			:      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
  ]
  UpperCamelCase_			:      Union[str, 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, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
      416, 416, 416, 416, 416, 416, 416, 416
  ]

  UpperCamelCase_			:      Optional[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
  ]
  UpperCamelCase_			:      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
  ]

  UpperCamelCase_			:      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, 653, 653, 653, 653, 653, 653, 653, 653,
      653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653
  ]
  UpperCamelCase_			:      int										=				[
      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
  ]

  UpperCamelCase_			:      Dict										=				[
      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
  ]
  UpperCamelCase_			:      Dict										=				[
      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 					_snake_case     ( self				:							Tuple					,  SCREAMING_SNAKE_CASE_				:							str	)			->		List[str]:







       '''simple docstring'''



       A:		Optional[Any]          =		JukeboxTokenizer.from_pretrained(__a	)
       A:		List[str]          =		tokenizer(**self.metas	)['input_ids']
       return tokens



  @slow
  def 					_snake_case     ( self				:							Tuple	)			->		Any:







       '''simple docstring'''



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

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

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

       set_seed(0	)
       A:		List[Any]          =		model._sample(__a					,  __a					,  [2]					,  sample_length=60 * model.priors[2].raw_to_tokens					,  save_results=__a	)
       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 					_snake_case     ( self				:							Union[str, Any]	)			->		str:







       '''simple docstring'''



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

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




  @slow
  def 					_snake_case     ( self				:							Any	)			->		str:







       '''simple docstring'''



       A:		Union[str, Any]          =		'ArthurZ/jukebox_prior_0'
       A:		List[Any]          =		JukeboxPrior.from_pretrained(__a					,  min_duration=0	).eval().half().to('''cuda'''	)

       A:		Tuple          =		self.prepare_inputs(__a	)[0].cuda()
       A:		str          =		model.get_metadata(__a					,  0					,  76_80					,  0	)
       set_seed(0	)
       A:		Optional[Any]          =		model.sample(1					,  metadata=__a					,  sample_tokens=60	)
       self.assertIn(outputs[0].cpu().tolist()					,  [self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]	)














'''simple docstring'''






def 							_SCREAMING_SNAKE_CASE	(					)     ->			int:







   """simple docstring"""

   for a in range(3_00	):
      for b in range(a + 1	,		4_00	):
         for c in range(b + 1	,		5_00	):
            if (a + b + c) == 10_00 and (a**2) + (b**2) == (c**2):
               return a * b * c

   return -1




def 							_SCREAMING_SNAKE_CASE	(					)     ->			int:







   """simple docstring"""

   for a in range(3_00	):
      for b in range(4_00	):
         __snake_case					:   Optional[Any]  				=			10_00 - a - b
         if a < b < c and (a**2) + (b**2) == (c**2):
            return a * b * c

   return -1




def 							_SCREAMING_SNAKE_CASE	(					)     ->			None:







   """simple docstring"""
   import timeit

   print(
       timeit.timeit('solution()'	,		setup='from __main__ import solution'	,		number=10_00	)	)
   print(
       timeit.timeit(
           'solution_fast()'	,		setup='from __main__ import solution_fast'	,		number=10_00	)	)


if __name__ == "__main__":
      print(f'''{solution() = }''')