





'''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"""
       _snake_case			:  List[str]		       =					(JukeboxModel,) if is_torch_available() else ()
       _snake_case			:  Optional[int]		       =					'openai/jukebox-1b-lyrics'
       _snake_case			:  Optional[int]		       =					{
           '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
       _snake_case			:  int		       =					[
           1_8_6_4, 1_5_3_6, 1_2_1_3, 1_8_7_0, 1_3_5_7, 1_5_3_6, 5_1_9, 8_8_0, 1_3_2_3, 7_8_9, 1_0_8_2, 5_3_4,
           1_0_0_0, 1_4_4_5, 1_1_0_5, 1_1_3_0, 9_6_7, 5_1_5, 1_4_3_4, 1_6_2_0, 5_3_4, 1_4_9_5, 2_8_3, 1_4_4_5,
           3_3_3, 1_3_0_7, 5_3_9, 1_6_3_1, 1_5_2_8, 3_7_5, 1_4_3_4, 6_7_3, 6_2_7, 7_1_0, 7_7_8, 1_8_8_3,
           1_4_0_5, 1_2_7_6, 1_4_5_5, 1_2_2_8
       ]

       _snake_case			:  List[str]		       =					[
           1_4_8_9, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3
       ]

       _snake_case			:  str		       =					[
           1_1_2_5, 1_7_5_1, 6_9_7, 1_7_7_6, 1_1_4_1, 1_4_7_6, 3_9_1, 6_9_7, 1_1_2_5, 6_8_4, 8_6_7, 4_1_6,
           8_4_4, 1_3_7_2, 1_2_7_4, 7_1_7, 1_2_7_4, 8_4_4, 1_2_9_9, 1_4_1_9, 6_9_7, 1_3_7_0, 3_1_7, 1_1_2_5,
           1_9_1, 1_4_4_0, 1_3_7_0, 1_4_4_0, 1_3_7_0, 2_8_2, 1_6_2_1, 1_3_7_0, 3_6_8, 3_4_9, 8_6_7, 1_8_7_2,
           1_2_6_2, 8_6_9, 1_7_2_8, 7_4_7
       ]
       _snake_case			:  Tuple		       =					[
           4_1_6, 4_1_6, 1_1_2_5, 1_1_2_5, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6
       ]

       _snake_case			:  int		       =					[
           1_7_5_5, 8_4_2, 3_0_7, 1_8_4_3, 1_0_2_2, 1_3_9_5, 2_3_4, 1_5_5_4, 8_0_6, 7_3_9, 1_0_2_2, 4_4_2,
           6_1_6, 5_5_6, 2_6_8, 1_4_9_9, 9_3_3, 4_5_7, 1_4_4_0, 1_8_3_7, 7_5_5, 9_8_5, 3_0_8, 9_0_2,
           2_9_3, 1_4_4_3, 1_6_7_1, 1_1_4_1, 1_5_3_3, 5_5_5, 1_5_6_2, 1_0_6_1, 2_8_7, 4_1_7, 1_0_2_2, 2_0_0_8,
           1_1_8_6, 1_0_1_5, 1_7_7_7, 2_6_8
       ]
       _snake_case			:  Tuple		       =					[
           8_5_4, 8_4_2, 1_3_5_3, 1_1_4, 1_3_5_3, 8_4_2, 1_8_5, 8_4_2, 1_8_5, 1_1_4, 5_9_1, 8_4_2,
           1_8_5, 4_1_7, 1_8_5, 8_4_2, 3_0_7, 8_4_2, 5_9_1, 8_4_2, 1_8_5, 8_4_2, 3_0_7, 8_4_2,
           5_9_1, 8_4_2, 1_3_5_3, 8_4_2, 1_8_5, 8_4_2, 5_9_1, 8_4_2, 5_9_1, 1_1_4, 5_9_1, 8_4_2,
           1_8_5, 8_4_2, 5_9_1, 8_9
       ]

       _snake_case			:  int		       =					[1_0_5_8_3_0_4, 0, 7_8_6_4_3_2, 7_1_6_9, 5_0_7, 7_6, 2_7, 4_0, 3_0, 7_6]

       _snake_case			:  Optional[Any]		       =					[
           3_9_0, 1_1_6_0, 1_0_0_2, 1_9_0_7, 1_7_8_8, 1_7_8_8, 1_7_8_8, 1_9_0_7, 1_0_0_2, 1_0_0_2, 1_8_5_4, 1_0_0_2,
           1_0_0_2, 1_0_0_2, 1_0_0_2, 1_0_0_2, 1_0_0_2, 1_1_6_0, 1_1_6_0, 1_6_0_6, 5_9_6, 5_9_6, 1_1_6_0, 1_0_0_2,
           1_5_1_6, 5_9_6, 1_0_0_2, 1_0_0_2, 1_0_0_2, 1_9_0_7, 1_7_8_8, 1_7_8_8, 1_7_8_8, 1_8_5_4, 1_7_8_8, 1_9_0_7,
           1_9_0_7, 1_7_8_8, 5_9_6, 1_6_2_6
       ]
       _snake_case			:  List[str]		       =					[
           1_2_3_6, 1_6_6_8, 1_4_8_4, 1_9_2_0, 1_8_4_8, 1_4_0_9, 1_3_9, 8_6_4, 1_8_2_8, 1_2_7_2, 1_5_9_9, 8_2_4,
           1_6_7_2, 1_3_9, 5_5_5, 1_4_8_4, 8_2_4, 1_9_2_0, 5_5_5, 5_9_6, 1_5_7_9, 1_5_9_9, 1_2_3_1, 1_5_9_9,
           1_6_3_7, 1_4_0_7, 2_1_2, 8_2_4, 1_5_9_9, 1_1_6, 1_4_3_3, 8_2_4, 2_5_8, 1_5_9_9, 1_4_3_3, 1_8_9_5,
           1_0_6_3, 1_4_3_3, 1_4_3_3, 1_5_9_9
       ]
       _snake_case			:  Any		       =					[
           1_6_8_4, 1_8_7_3, 1_1_1_9, 1_1_8_9, 3_9_5, 6_1_1, 1_9_0_1, 9_7_2, 8_9_0, 1_3_3_7, 1_3_9_2, 1_9_2_7,
           9_6, 9_7_2, 6_7_2, 7_8_0, 1_1_1_9, 8_9_0, 1_5_8, 7_7_1, 1_0_7_3, 1_9_2_7, 3_5_3, 1_3_3_1,
           1_2_6_9, 1_4_5_9, 1_3_3_3, 1_6_4_5, 8_1_2, 1_5_7_7, 1_3_3_7, 6_0_6, 3_5_3, 9_8_1, 1_4_6_6, 6_1_9,
           1_9_7, 3_9_1, 3_0_2, 1_9_3_0
       ]
       _snake_case			:  str		       =					[
           3_9_0, 1_1_6_0, 1_0_0_2, 1_9_0_7, 1_7_8_8, 1_7_8_8, 1_7_8_8, 1_9_0_7, 1_0_0_2, 1_0_0_2, 1_8_5_4, 1_0_0_2,
           1_0_0_2, 1_0_0_2, 1_0_0_2, 1_0_0_2, 1_0_0_2, 1_1_6_0, 1_1_6_0, 1_6_0_6, 5_9_6, 5_9_6, 1_1_6_0, 1_0_0_2,
           1_5_1_6, 5_9_6, 1_0_0_2, 1_0_0_2, 1_0_0_2, 1_9_0_7, 1_7_8_8, 1_7_8_8, 1_7_8_8, 1_8_5_4, 1_7_8_8, 1_9_0_7,
           1_9_0_7, 1_7_8_8, 5_9_6, 1_6_2_6
       ]
       _snake_case			:  Union[str, Any]		       =					[
           -0.04_92, -0.05_24, -0.05_65, -0.06_40, -0.06_86, -0.06_84, -0.06_77, -0.06_64,
           -0.06_05, -0.04_90, -0.03_30, -0.01_68, -0.00_83, -0.00_75, -0.00_51, 0.00_25,
           0.01_36, 0.02_61, 0.03_86, 0.04_97, 0.05_80, 0.05_99, 0.05_83, 0.06_14,
           0.07_40, 0.08_89, 0.10_23, 0.11_62, 0.12_11, 0.12_12, 0.12_51, 0.13_36,
           0.15_02, 0.16_86, 0.18_83, 0.21_48, 0.23_63, 0.24_58, 0.25_07, 0.25_31
       ]
       _snake_case			:  Tuple		       =					[
           0.02_56, -0.05_44, 0.16_00, -0.00_32, 0.10_66, 0.08_25, -0.00_13, 0.34_40,
           0.02_10, 0.04_12, -0.17_77, -0.08_92, -0.01_64, 0.02_85, -0.06_13, -0.06_17,
           -0.01_37, -0.02_01, -0.01_75, 0.02_15, -0.06_27, 0.05_20, -0.07_30, 0.09_70,
           -0.01_00, 0.04_42, -0.05_86, 0.02_07, -0.00_15, -0.00_82
       ]
       _snake_case			:  Dict		       =					[
           0.04_15, 0.08_77, 0.00_22, -0.00_55, 0.07_51, 0.03_34, 0.03_24, -0.00_68,
           0.00_11, 0.00_17, -0.06_76, 0.06_55, -0.01_43, 0.03_99, 0.03_03, 0.07_43,
           -0.01_68, -0.03_94, -0.11_13, 0.01_24, 0.04_42, 0.02_67, -0.00_03, -0.15_36,
           -0.01_16, -0.18_37, -0.01_80, -0.10_26, -0.07_77, -0.04_56
       ]
       _snake_case			:  List[str]		       =					[
           7_6, 2_7, 4_0, 3_0, 7_6, 4_6, 4_4, 4_7, 4_0, 3_7, 3_8, 3_1, 4_5, 4_5, 7_6, 3_8, 3_1, 3_3,
           4_5, 7_6, 4_1, 3_2, 7_6, 4_5, 4_6, 4_1, 4_0, 3_1, 7_8, 7_6
       ]





       def snake_case__		(							self     :	Optional[int]  )					->  Union[str, Any]:

            '''simple docstring'''




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





       @slow
       def snake_case__		(							self     :	str  )					->  str:

            '''simple docstring'''




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

            set_seed(0  )
            _UpperCamelCase       					= [torch.zeros(1 ,				0 ,				dtype=torch.long  ).cpu() for _ in range(3  )]
            _UpperCamelCase       					= 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  )
            _UpperCamelCase       					= 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  )
            _UpperCamelCase       					= 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 snake_case__		(							self     :	List[str]  )					->  Optional[Any]:

            '''simple docstring'''




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

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

            _UpperCamelCase       					= model.priors[0]
            _UpperCamelCase       					= 0
            _UpperCamelCase       					= top_prior.get_music_tokens_conds(lowerCAmelCase__ ,				start=lowerCAmelCase__ ,				end=start + top_prior.n_ctx  )
            _UpperCamelCase       					= top_prior.get_metadata(labels[0].clone() ,				lowerCAmelCase__ ,				1058304 ,				0  )

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

            _UpperCamelCase					,       _UpperCamelCase					,       _UpperCamelCase       					= 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 snake_case__		(							self     :	Union[str, Any]  )					->  Dict:

            '''simple docstring'''




            _UpperCamelCase       					= False

            _UpperCamelCase       					= JukeboxModel.from_pretrained(self.model_id ,				min_duration=0  ).eval()
            set_seed(0  )
            _UpperCamelCase       					= torch.rand((1, 5120, 1)  )
            _UpperCamelCase       					= list(self.prepare_inputs()  )

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

            _UpperCamelCase       					= torch.cat((zs[0], torch.zeros(1 ,				2048 - zs[0].shape[-1]  )) ,				dim=-1  ).long()
            _UpperCamelCase       					= [upper_a, model.vqvae.encode(lowerCAmelCase__ ,				start_level=1 ,				bs_chunks=waveform.shape[0]  )[0], None]
            _UpperCamelCase       					= 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  )  )

            _UpperCamelCase       					= torch.cat((zs[1], torch.zeros(1 ,				2048 - zs[1].shape[-1]  )) ,				dim=-1  ).long()
            _UpperCamelCase       					= [upper_a, upper_a, model.vqvae.encode(lowerCAmelCase__ ,				start_level=0 ,				bs_chunks=waveform.shape[0]  )[0]]
            _UpperCamelCase       					= 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 snake_case__		(							self     :	List[Any]  )					->  List[Any]:

            '''simple docstring'''




            _UpperCamelCase       					= JukeboxModel.from_pretrained(self.model_id ,				min_duration=0  ).eval()
            set_seed(0  )
            _UpperCamelCase       					= torch.rand((1, 5120, 1)  )
            with torch.no_grad():
                 _UpperCamelCase       					= 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():
                 _UpperCamelCase       					= 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        __lowerCAmelCase  (					unittest.TestCase				):






       """simple docstring"""
       _snake_case			:  List[Any]		       =					(JukeboxModel,) if is_torch_available() else ()
       _snake_case			:  Union[str, Any]		       =					'openai/jukebox-5b-lyrics'
       _snake_case			:  Optional[Any]		       =					{
           'artist': 'Zac Brown Band',
           'genres': 'Country',
           'lyrics': 'I met a traveller from an antique land,\n    Who said "Two vast and trunkless legs of stone\n    Stand in the desert. . . . Near them, on the sand,\n    Half sunk a shattered visage lies, whose frown,\n    And wrinkled lip, and sneer of cold command,\n    Tell that its sculptor well those passions read\n    Which yet survive, stamped on these lifeless things,\n    The hand that mocked them, and the heart that fed;\n    And on the pedestal, these words appear:\n    My name is Ozymandias, King of Kings;\n    Look on my Works, ye Mighty, and despair!\n    Nothing beside remains. Round the decay\n    Of that colossal Wreck, boundless and bare\n    The lone and level sands stretch far away\n    ',
       }

       # fmt: off
       _snake_case			:  Optional[Any]		       =					[
           1_4_8_9, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           1_4_8_9, 1_4_8_9, 1_4_8_9, 1_4_8_9, 1_1_5_0, 1_8_5_3, 1_5_0_9, 1_1_5_0, 1_3_5_7, 1_5_0_9, 6, 1_2_7_2
       ]
       _snake_case			:  int		       =					[
           1_4_8_9, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3
       ]

       _snake_case			:  Dict		       =					[
           1_1_2_5, 4_1_6, 1_1_2_5, 1_1_2_5, 1_1_2_5, 1_1_2_5, 1_1_2_5, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6
       ]
       _snake_case			:  Optional[Any]		       =					[
           4_1_6, 4_1_6, 1_1_2_5, 1_1_2_5, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6
       ]

       _snake_case			:  Optional[Any]		       =					[
           1_7_5_5, 1_0_6_1, 2_3_4, 1_7_5_5, 1_0_6_1, 1_7_5_5, 1_8_5, 2_9_0, 3_0_7, 3_0_7, 6_1_6, 6_1_6,
           6_1_6, 6_1_6, 6_1_6, 6_1_6, 3_0_7, 2_9_0, 4_1_7, 1_7_5_5, 2_3_4, 1_7_5_5, 1_8_5, 2_9_0,
           2_9_0, 2_9_0, 3_0_7, 6_1_6, 6_1_6, 6_1_6, 6_1_6, 6_1_6, 2_9_0, 2_3_4, 2_3_4, 1_7_5_5,
           2_3_4, 2_3_4, 1_7_5_5, 2_3_4, 1_8_5, 1_8_5, 3_0_7, 6_1_6, 6_1_6, 6_1_6, 6_1_6, 2_9_0,
           1_7_5_5, 1_7_5_5, 1_7_5_5, 2_3_4, 2_3_4, 1_7_5_5, 1_5_7_2, 2_9_0, 3_0_7, 6_1_6, 3_4, 6_1_6
       ]
       _snake_case			:  Tuple		       =					[
           8_5_4, 8_4_2, 1_3_5_3, 1_1_4, 1_3_5_3, 8_4_2, 1_8_5, 8_4_2, 1_8_5, 1_1_4, 5_9_1, 8_4_2, 1_8_5,
           4_1_7, 1_8_5, 8_4_2, 3_0_7, 8_4_2, 5_9_1, 8_4_2, 1_8_5, 8_4_2, 1_8_5, 8_4_2, 5_9_1, 8_4_2,
           1_3_5_3, 8_4_2, 1_8_5, 8_4_2, 5_9_1, 8_4_2, 5_9_1, 1_1_4, 5_9_1, 8_4_2, 1_8_5, 8_4_2, 5_9_1,
           8_9, 5_9_1, 8_4_2, 5_9_1, 8_4_2, 5_9_1, 4_1_7, 1_3_7_2, 8_4_2, 1_3_7_2, 8_4_2, 3_4, 8_4_2,
           1_8_5, 8_9, 5_9_1, 8_4_2, 1_8_5, 8_4_2, 5_9_1, 6_3_2
       ]

       _snake_case			:  int		       =					[
           1_4_8_9, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3
       ]
       _snake_case			:  Tuple		       =					[
           1_4_8_9, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3,
           6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 6_5_3, 1_8_5_3, 1_1_7_7, 1_5_3_6, 1_2_2_8,
           7_1_0, 4_7_5, 1_4_8_9, 1_2_2_9, 1_2_2_4, 2_3_1, 1_2_2_4, 2_5_2, 1_4_3_4, 6_5_3, 4_7_5,
           1_1_0_6, 1_8_7_7, 1_5_9_9, 1_2_2_8, 1_6_0_0, 1_6_8_3, 1_1_8_2, 1_8_5_3, 4_7_5, 1_8_6_4,
           2_5_2, 1_2_2_9, 1_4_3_4, 2_0_0_1
       ]

       _snake_case			:  List[str]		       =					[
           1_1_2_5, 1_1_2_5, 4_1_6, 1_1_2_5, 1_1_2_5, 4_1_6, 1_1_2_5, 1_1_2_5, 4_1_6, 4_1_6, 1_1_2_5, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6,
           4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6, 4_1_6
       ]
       _snake_case			:  Any		       =					[
           4_9_1, 1_7_5_5, 3_4, 1_6_1_3, 1_7_5_5, 4_1_7, 9_9_2, 1_6_1_3, 2_2_2, 8_4_2, 1_3_5_3, 1_6_1_3,
           8_4_4, 6_3_2, 1_8_5, 1_6_1_3, 8_4_4, 6_3_2, 1_8_5, 1_6_1_3, 1_8_5, 8_4_2, 6_7_7, 1_6_1_3,
           1_8_5, 1_1_4, 1_3_5_3, 1_6_1_3, 3_0_7, 8_9, 8_4_4, 1_6_1_3, 3_0_7, 1_3_3_2, 2_3_4, 1_9_7_9,
           3_0_7, 8_9, 1_3_5_3, 6_1_6, 3_4, 8_4_2, 1_8_5, 8_4_2, 3_4, 8_4_2, 1_8_5, 8_4_2,
           3_0_7, 1_1_4, 1_8_5, 8_9, 3_4, 1_2_6_8, 1_8_5, 8_9, 3_4, 8_4_2, 1_8_5, 8_9
       ]





       def snake_case__		(							self     :	Tuple ,				lowerCAmelCase__     :	List[str]  )					->  int:

            '''simple docstring'''




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





       @slow
       def snake_case__		(							self     :	int  )					->  str:

            '''simple docstring'''




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

            set_seed(0  )
            _UpperCamelCase       					= [torch.zeros(1 ,				0 ,				dtype=torch.long  ).cpu() for _ in range(3  )]
            _UpperCamelCase       					= 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  )
            _UpperCamelCase       					= 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  )
            _UpperCamelCase       					= 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 snake_case__		(							self     :	Optional[Any]  )					->  Union[str, Any]:

            '''simple docstring'''




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

            set_seed(0  )
            model.priors[0].cuda()
            _UpperCamelCase       					= [torch.zeros(1 ,				0 ,				dtype=torch.long  ).cuda() for _ in range(3  )]
            _UpperCamelCase       					= 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()
            _UpperCamelCase       					= 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()
            _UpperCamelCase       					= 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 snake_case__		(							self     :	Union[str, Any]  )					->  Dict:

            '''simple docstring'''




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

            _UpperCamelCase       					= self.prepare_inputs(lowerCAmelCase__  )[0].cuda()
            _UpperCamelCase       					= model.get_metadata(lowerCAmelCase__ ,				0 ,				7680 ,				0  )
            set_seed(0  )
            _UpperCamelCase       					= 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]  )










'''simple docstring'''

from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowercase__		:    Union[str, Any] =       {
    'configuration_retribert': ['RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RetriBertConfig'],
    'tokenization_retribert': ['RetriBertTokenizer'],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__		:    Dict =       ['RetriBertTokenizerFast']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__		:    Tuple =       [
       'RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'RetriBertModel',
       'RetriBertPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_retribert import RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RetriBertConfig
   from .tokenization_retribert import RetriBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_retribert_fast import RetriBertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_retribert import (
          RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          RetriBertModel,
          RetriBertPreTrainedModel,
      )

else:
   import sys

   lowercase__		:    Optional[Any] =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



