
'''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 				_a			(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 =					[
           18_64, 15_36, 12_13, 18_70, 13_57, 15_36, 5_19, 8_80, 13_23, 7_89, 10_82, 5_34,
           10_00, 14_45, 11_05, 11_30, 9_67, 5_15, 14_34, 16_20, 5_34, 14_95, 2_83, 14_45,
           3_33, 13_07, 5_39, 16_31, 15_28, 3_75, 14_34, 6_73, 6_27, 7_10, 7_78, 18_83,
           14_05, 12_76, 14_55, 12_28
       ]

       SCREAMING_SNAKE_CASE =					[
           14_89, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53
       ]

       SCREAMING_SNAKE_CASE =					[
           11_25, 17_51, 6_97, 17_76, 11_41, 14_76, 3_91, 6_97, 11_25, 6_84, 8_67, 4_16,
           8_44, 13_72, 12_74, 7_17, 12_74, 8_44, 12_99, 14_19, 6_97, 13_70, 3_17, 11_25,
           1_91, 14_40, 13_70, 14_40, 13_70, 2_82, 16_21, 13_70, 3_68, 3_49, 8_67, 18_72,
           12_62, 8_69, 17_28, 7_47
       ]
       SCREAMING_SNAKE_CASE =					[
           4_16, 4_16, 11_25, 11_25, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16
       ]

       SCREAMING_SNAKE_CASE =					[
           17_55, 8_42, 3_07, 18_43, 10_22, 13_95, 2_34, 15_54, 8_06, 7_39, 10_22, 4_42,
           6_16, 5_56, 2_68, 14_99, 9_33, 4_57, 14_40, 18_37, 7_55, 9_85, 3_08, 9_02,
           2_93, 14_43, 16_71, 11_41, 15_33, 5_55, 15_62, 10_61, 2_87, 4_17, 10_22, 20_08,
           11_86, 10_15, 17_77, 2_68
       ]
       SCREAMING_SNAKE_CASE =					[
           8_54, 8_42, 13_53, 1_14, 13_53, 8_42, 1_85, 8_42, 1_85, 1_14, 5_91, 8_42,
           1_85, 4_17, 1_85, 8_42, 3_07, 8_42, 5_91, 8_42, 1_85, 8_42, 3_07, 8_42,
           5_91, 8_42, 13_53, 8_42, 1_85, 8_42, 5_91, 8_42, 5_91, 1_14, 5_91, 8_42,
           1_85, 8_42, 5_91, 89
       ]

       SCREAMING_SNAKE_CASE =					[1_05_83_04, 0, 78_64_32, 71_69, 5_07, 76, 27, 40, 30, 76]

       SCREAMING_SNAKE_CASE =					[
           3_90, 11_60, 10_02, 19_07, 17_88, 17_88, 17_88, 19_07, 10_02, 10_02, 18_54, 10_02,
           10_02, 10_02, 10_02, 10_02, 10_02, 11_60, 11_60, 16_06, 5_96, 5_96, 11_60, 10_02,
           15_16, 5_96, 10_02, 10_02, 10_02, 19_07, 17_88, 17_88, 17_88, 18_54, 17_88, 19_07,
           19_07, 17_88, 5_96, 16_26
       ]
       SCREAMING_SNAKE_CASE =					[
           12_36, 16_68, 14_84, 19_20, 18_48, 14_09, 1_39, 8_64, 18_28, 12_72, 15_99, 8_24,
           16_72, 1_39, 5_55, 14_84, 8_24, 19_20, 5_55, 5_96, 15_79, 15_99, 12_31, 15_99,
           16_37, 14_07, 2_12, 8_24, 15_99, 1_16, 14_33, 8_24, 2_58, 15_99, 14_33, 18_95,
           10_63, 14_33, 14_33, 15_99
       ]
       SCREAMING_SNAKE_CASE =					[
           16_84, 18_73, 11_19, 11_89, 3_95, 6_11, 19_01, 9_72, 8_90, 13_37, 13_92, 19_27,
           96, 9_72, 6_72, 7_80, 11_19, 8_90, 1_58, 7_71, 10_73, 19_27, 3_53, 13_31,
           12_69, 14_59, 13_33, 16_45, 8_12, 15_77, 13_37, 6_06, 3_53, 9_81, 14_66, 6_19,
           1_97, 3_91, 3_02, 19_30
       ]
       SCREAMING_SNAKE_CASE =					[
           3_90, 11_60, 10_02, 19_07, 17_88, 17_88, 17_88, 19_07, 10_02, 10_02, 18_54, 10_02,
           10_02, 10_02, 10_02, 10_02, 10_02, 11_60, 11_60, 16_06, 5_96, 5_96, 11_60, 10_02,
           15_16, 5_96, 10_02, 10_02, 10_02, 19_07, 17_88, 17_88, 17_88, 18_54, 17_88, 19_07,
           19_07, 17_88, 5_96, 16_26
       ]
       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     UpperCamelCase			(							self )      ->     Dict:
          _SCREAMING_SNAKE_CASE       	=			JukeboxTokenizer.from_pretrained(self.model_id )
          _SCREAMING_SNAKE_CASE       	=			tokenizer(**self.metas )["""input_ids"""]
          return tokens






       @slow
       def     UpperCamelCase			(							self )      ->     Dict:
          _SCREAMING_SNAKE_CASE       	=			JukeboxModel.from_pretrained(self.model_id    ,							min_duration=0 ).eval()
          _SCREAMING_SNAKE_CASE       	=			self.prepare_inputs()

          set_seed(0 )
          _SCREAMING_SNAKE_CASE       	=			[torch.zeros(1    ,							0    ,							dtype=torch.long ).cpu() for _ in range(3 )]
          _SCREAMING_SNAKE_CASE       	=			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 )
          _SCREAMING_SNAKE_CASE       	=			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 )
          _SCREAMING_SNAKE_CASE       	=			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     UpperCamelCase			(							self )      ->     Any:
          _SCREAMING_SNAKE_CASE       	=			False
          _SCREAMING_SNAKE_CASE       	=			JukeboxModel.from_pretrained(self.model_id    ,							min_duration=0 ).eval()

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

          _SCREAMING_SNAKE_CASE       	=			model.priors[0]
          _SCREAMING_SNAKE_CASE       	=			0
          _SCREAMING_SNAKE_CASE       	=			top_prior.get_music_tokens_conds(A__    ,							start=A__    ,							end=start + top_prior.n_ctx )
          _SCREAMING_SNAKE_CASE       	=			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 )

          _SCREAMING_SNAKE_CASE	,							_SCREAMING_SNAKE_CASE	,							_SCREAMING_SNAKE_CASE       	=			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     UpperCamelCase			(							self )      ->     Dict:
          _SCREAMING_SNAKE_CASE       	=			False

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

          _SCREAMING_SNAKE_CASE       	=			[model.vqvae.encode(A__    ,							start_level=2    ,							bs_chunks=waveform.shape[0] )[0], None, None]
          _SCREAMING_SNAKE_CASE       	=			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 ) )

          _SCREAMING_SNAKE_CASE       	=			torch.cat((zs[0], torch.zeros(1    ,							20_48 - zs[0].shape[-1] ))    ,							dim=-1 ).long()
          _SCREAMING_SNAKE_CASE       	=			[upper_a, model.vqvae.encode(A__    ,							start_level=1    ,							bs_chunks=waveform.shape[0] )[0], None]
          _SCREAMING_SNAKE_CASE       	=			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 ) )

          _SCREAMING_SNAKE_CASE       	=			torch.cat((zs[1], torch.zeros(1    ,							20_48 - zs[1].shape[-1] ))    ,							dim=-1 ).long()
          _SCREAMING_SNAKE_CASE       	=			[upper_a, upper_a, model.vqvae.encode(A__    ,							start_level=0    ,							bs_chunks=waveform.shape[0] )[0]]
          _SCREAMING_SNAKE_CASE       	=			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     UpperCamelCase			(							self )      ->     Any:
          _SCREAMING_SNAKE_CASE       	=			JukeboxModel.from_pretrained(self.model_id    ,							min_duration=0 ).eval()
          set_seed(0 )
          _SCREAMING_SNAKE_CASE       	=			torch.rand((1, 51_20, 1) )
          with torch.no_grad():
             _SCREAMING_SNAKE_CASE       	=			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():
             _SCREAMING_SNAKE_CASE       	=			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 				_a			(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 =					[
           14_89, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           14_89, 14_89, 14_89, 14_89, 11_50, 18_53, 15_09, 11_50, 13_57, 15_09, 6, 12_72
       ]
       SCREAMING_SNAKE_CASE =					[
           14_89, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53
       ]

       SCREAMING_SNAKE_CASE =					[
           11_25, 4_16, 11_25, 11_25, 11_25, 11_25, 11_25, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16
       ]
       SCREAMING_SNAKE_CASE =					[
           4_16, 4_16, 11_25, 11_25, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16
       ]

       SCREAMING_SNAKE_CASE =					[
           17_55, 10_61, 2_34, 17_55, 10_61, 17_55, 1_85, 2_90, 3_07, 3_07, 6_16, 6_16,
           6_16, 6_16, 6_16, 6_16, 3_07, 2_90, 4_17, 17_55, 2_34, 17_55, 1_85, 2_90,
           2_90, 2_90, 3_07, 6_16, 6_16, 6_16, 6_16, 6_16, 2_90, 2_34, 2_34, 17_55,
           2_34, 2_34, 17_55, 2_34, 1_85, 1_85, 3_07, 6_16, 6_16, 6_16, 6_16, 2_90,
           17_55, 17_55, 17_55, 2_34, 2_34, 17_55, 15_72, 2_90, 3_07, 6_16, 34, 6_16
       ]
       SCREAMING_SNAKE_CASE =					[
           8_54, 8_42, 13_53, 1_14, 13_53, 8_42, 1_85, 8_42, 1_85, 1_14, 5_91, 8_42, 1_85,
           4_17, 1_85, 8_42, 3_07, 8_42, 5_91, 8_42, 1_85, 8_42, 1_85, 8_42, 5_91, 8_42,
           13_53, 8_42, 1_85, 8_42, 5_91, 8_42, 5_91, 1_14, 5_91, 8_42, 1_85, 8_42, 5_91,
           89, 5_91, 8_42, 5_91, 8_42, 5_91, 4_17, 13_72, 8_42, 13_72, 8_42, 34, 8_42,
           1_85, 89, 5_91, 8_42, 1_85, 8_42, 5_91, 6_32
       ]

       SCREAMING_SNAKE_CASE =					[
           14_89, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53
       ]
       SCREAMING_SNAKE_CASE =					[
           14_89, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 18_53, 11_77, 15_36, 12_28,
           7_10, 4_75, 14_89, 12_29, 12_24, 2_31, 12_24, 2_52, 14_34, 6_53, 4_75,
           11_06, 18_77, 15_99, 12_28, 16_00, 16_83, 11_82, 18_53, 4_75, 18_64,
           2_52, 12_29, 14_34, 20_01
       ]

       SCREAMING_SNAKE_CASE =					[
           11_25, 11_25, 4_16, 11_25, 11_25, 4_16, 11_25, 11_25, 4_16, 4_16, 11_25, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16,
           4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16, 4_16
       ]
       SCREAMING_SNAKE_CASE =					[
           4_91, 17_55, 34, 16_13, 17_55, 4_17, 9_92, 16_13, 2_22, 8_42, 13_53, 16_13,
           8_44, 6_32, 1_85, 16_13, 8_44, 6_32, 1_85, 16_13, 1_85, 8_42, 6_77, 16_13,
           1_85, 1_14, 13_53, 16_13, 3_07, 89, 8_44, 16_13, 3_07, 13_32, 2_34, 19_79,
           3_07, 89, 13_53, 6_16, 34, 8_42, 1_85, 8_42, 34, 8_42, 1_85, 8_42,
           3_07, 1_14, 1_85, 89, 34, 12_68, 1_85, 89, 34, 8_42, 1_85, 89
       ]






       def     UpperCamelCase			(							self    ,							A__ )      ->     List[Any]:
          _SCREAMING_SNAKE_CASE       	=			JukeboxTokenizer.from_pretrained(A__ )
          _SCREAMING_SNAKE_CASE       	=			tokenizer(**self.metas )["""input_ids"""]
          return tokens






       @slow
       def     UpperCamelCase			(							self )      ->     Optional[Any]:
          _SCREAMING_SNAKE_CASE       	=			JukeboxModel.from_pretrained(self.model_id    ,							min_duration=0 ).eval()
          _SCREAMING_SNAKE_CASE       	=			self.prepare_inputs(self.model_id )

          set_seed(0 )
          _SCREAMING_SNAKE_CASE       	=			[torch.zeros(1    ,							0    ,							dtype=torch.long ).cpu() for _ in range(3 )]
          _SCREAMING_SNAKE_CASE       	=			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 )
          _SCREAMING_SNAKE_CASE       	=			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 )
          _SCREAMING_SNAKE_CASE       	=			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     UpperCamelCase			(							self )      ->     Optional[Any]:
          _SCREAMING_SNAKE_CASE       	=			JukeboxModel.from_pretrained(self.model_id    ,							min_duration=0 ).eval()
          _SCREAMING_SNAKE_CASE       	=			[i.cuda() for i in self.prepare_inputs(self.model_id )]

          set_seed(0 )
          model.priors[0].cuda()
          _SCREAMING_SNAKE_CASE       	=			[torch.zeros(1    ,							0    ,							dtype=torch.long ).cuda() for _ in range(3 )]
          _SCREAMING_SNAKE_CASE       	=			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()
          _SCREAMING_SNAKE_CASE       	=			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()
          _SCREAMING_SNAKE_CASE       	=			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     UpperCamelCase			(							self )      ->     int:
          _SCREAMING_SNAKE_CASE       	=			"""ArthurZ/jukebox_prior_0"""
          _SCREAMING_SNAKE_CASE       	=			JukeboxPrior.from_pretrained(A__    ,							min_duration=0 ).eval().half().to("""cuda""" )

          _SCREAMING_SNAKE_CASE       	=			self.prepare_inputs(A__ )[0].cuda()
          _SCREAMING_SNAKE_CASE       	=			model.get_metadata(A__    ,							0    ,							76_80    ,							0 )
          set_seed(0 )
          _SCREAMING_SNAKE_CASE       	=			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'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__ :						int    							=					logging.get_logger(__name__)

UpperCamelCase__ :						Any    							=					{
    "openbmb/cpm-ant-10b": "https://huggingface.co/openbmb/cpm-ant-10b/blob/main/config.json"
    # See all CPMAnt models at https://huggingface.co/models?filter=cpmant
}

class 				_a			(_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE =					'cpmant'






       def __init__(							self    ,							A__ = 3_07_20    ,							A__ = 40_96    ,							A__ = 32    ,							A__ = 1_28    ,							A__ = 1_02_40    ,							A__ = 48    ,							A__ = 0.0    ,							A__ = 5_12    ,							A__ = 20_48    ,							A__ = 1E-6    ,							A__ = 1.0    ,							A__ = 32    ,							A__ = 32    ,							A__ = 32    ,							A__ = True    ,							**A__    ,							)      ->     List[Any]:
          super().__init__(**A__ )
          _SCREAMING_SNAKE_CASE       	=			prompt_types
          _SCREAMING_SNAKE_CASE       	=			prompt_length
          _SCREAMING_SNAKE_CASE       	=			segment_types
          _SCREAMING_SNAKE_CASE       	=			hidden_size
          _SCREAMING_SNAKE_CASE       	=			num_attention_heads
          _SCREAMING_SNAKE_CASE       	=			dim_head
          _SCREAMING_SNAKE_CASE       	=			dim_ff
          _SCREAMING_SNAKE_CASE       	=			num_hidden_layers
          _SCREAMING_SNAKE_CASE       	=			position_bias_num_buckets
          _SCREAMING_SNAKE_CASE       	=			position_bias_max_distance
          _SCREAMING_SNAKE_CASE       	=			dropout_p
          _SCREAMING_SNAKE_CASE       	=			eps
          _SCREAMING_SNAKE_CASE       	=			use_cache
          _SCREAMING_SNAKE_CASE       	=			vocab_size
          _SCREAMING_SNAKE_CASE       	=			init_std






