
'''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 			UpperCamelCase__	(     unittest.TestCase):
 UpperCAmelCase__     :     Optional[int]    					=       (JukeboxModel,) if is_torch_available() else ()
 UpperCAmelCase__     :     str    					=       'openai/jukebox-1b-lyrics'
 UpperCAmelCase__     :     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
 UpperCAmelCase__     :     List[str]    					=       [
     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
 ]

 UpperCAmelCase__     :     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
 ]

 UpperCAmelCase__     :     Dict    					=       [
     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
 ]
 UpperCAmelCase__     :     List[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
 ]

 UpperCAmelCase__     :     str    					=       [
     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
 ]
 UpperCAmelCase__     :     Optional[Any]    					=       [
     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
 ]

 UpperCAmelCase__     :     Any    					=       [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]

 UpperCAmelCase__     :     int    					=       [
     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
 ]
 UpperCAmelCase__     :     Optional[int]    					=       [
     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
 ]
 UpperCAmelCase__     :     int    					=       [
     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
 ]
 UpperCAmelCase__     :     Optional[int]    					=       [
     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
 ]
 UpperCAmelCase__     :     Any    					=       [
     -0.0_4_9_2, -0.0_5_2_4, -0.0_5_6_5, -0.0_6_4_0, -0.0_6_8_6, -0.0_6_8_4, -0.0_6_7_7, -0.0_6_6_4,
     -0.0_6_0_5, -0.0_4_9_0, -0.0_3_3_0, -0.0_1_6_8, -0.0_0_8_3, -0.0_0_7_5, -0.0_0_5_1, 0.0_0_2_5,
     0.0_1_3_6, 0.0_2_6_1, 0.0_3_8_6, 0.0_4_9_7, 0.0_5_8_0, 0.0_5_9_9, 0.0_5_8_3, 0.0_6_1_4,
     0.0_7_4_0, 0.0_8_8_9, 0.1_0_2_3, 0.1_1_6_2, 0.1_2_1_1, 0.1_2_1_2, 0.1_2_5_1, 0.1_3_3_6,
     0.1_5_0_2, 0.1_6_8_6, 0.1_8_8_3, 0.2_1_4_8, 0.2_3_6_3, 0.2_4_5_8, 0.2_5_0_7, 0.2_5_3_1
 ]
 UpperCAmelCase__     :     Dict    					=       [
     0.0_2_5_6, -0.0_5_4_4, 0.1_6_0_0, -0.0_0_3_2, 0.1_0_6_6, 0.0_8_2_5, -0.0_0_1_3, 0.3_4_4_0,
     0.0_2_1_0, 0.0_4_1_2, -0.1_7_7_7, -0.0_8_9_2, -0.0_1_6_4, 0.0_2_8_5, -0.0_6_1_3, -0.0_6_1_7,
     -0.0_1_3_7, -0.0_2_0_1, -0.0_1_7_5, 0.0_2_1_5, -0.0_6_2_7, 0.0_5_2_0, -0.0_7_3_0, 0.0_9_7_0,
     -0.0_1_0_0, 0.0_4_4_2, -0.0_5_8_6, 0.0_2_0_7, -0.0_0_1_5, -0.0_0_8_2
 ]
 UpperCAmelCase__     :     List[str]    					=       [
     0.0_4_1_5, 0.0_8_7_7, 0.0_0_2_2, -0.0_0_5_5, 0.0_7_5_1, 0.0_3_3_4, 0.0_3_2_4, -0.0_0_6_8,
     0.0_0_1_1, 0.0_0_1_7, -0.0_6_7_6, 0.0_6_5_5, -0.0_1_4_3, 0.0_3_9_9, 0.0_3_0_3, 0.0_7_4_3,
     -0.0_1_6_8, -0.0_3_9_4, -0.1_1_1_3, 0.0_1_2_4, 0.0_4_4_2, 0.0_2_6_7, -0.0_0_0_3, -0.1_5_3_6,
     -0.0_1_1_6, -0.1_8_3_7, -0.0_1_8_0, -0.1_0_2_6, -0.0_7_7_7, -0.0_4_5_6
 ]
 UpperCAmelCase__     :     Optional[Any]    					=       [
     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 						lowercase_    (      self	:Tuple      )					->      List[Any]:







       '''simple docstring'''



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






 @slow
 def 						lowercase_    (      self	:Tuple      )					->      int:







       '''simple docstring'''



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

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







       '''simple docstring'''



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

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

       __A													=      model.priors[0]
       __A													=      0
       __A													=      top_prior.get_music_tokens_conds(_A						,					start=_A						,					end=start + top_prior.n_ctx      )
       __A													=      top_prior.get_metadata(labels[0].clone()						,					_A						,					1_058_304						,					0      )

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

       __A						,   __A						,   __A													=      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 						lowercase_    (      self	:Dict      )					->      Union[str, Any]:







       '''simple docstring'''



       __A													=      False

       __A													=      JukeboxModel.from_pretrained(self.model_id						,					min_duration=0      ).eval()
       set_seed(0      )
       __A													=      torch.rand((1, 5_120, 1)      )
       __A													=      list(self.prepare_inputs()      )

       __A													=      [model.vqvae.encode(_A						,					start_level=2						,					bs_chunks=waveform.shape[0]      )[0], None, None]
       __A													=      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													=      torch.cat((zs[0], torch.zeros(1						,					2_048 - zs[0].shape[-1]      ))						,					dim=-1      ).long()
       __A													=      [upper_a, model.vqvae.encode(_A						,					start_level=1						,					bs_chunks=waveform.shape[0]      )[0], None]
       __A													=      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													=      torch.cat((zs[1], torch.zeros(1						,					2_048 - zs[1].shape[-1]      ))						,					dim=-1      ).long()
       __A													=      [upper_a, upper_a, model.vqvae.encode(_A						,					start_level=0						,					bs_chunks=waveform.shape[0]      )[0]]
       __A													=      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 						lowercase_    (      self	:Union[str, Any]      )					->      str:







       '''simple docstring'''



       __A													=      JukeboxModel.from_pretrained(self.model_id						,					min_duration=0      ).eval()
       set_seed(0      )
       __A													=      torch.rand((1, 5_120, 1)      )
       with torch.no_grad():
             __A													=      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													=      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 			UpperCamelCase__	(     unittest.TestCase):
 UpperCAmelCase__     :     int    					=       (JukeboxModel,) if is_torch_available() else ()
 UpperCAmelCase__     :     Optional[int]    					=       'openai/jukebox-5b-lyrics'
 UpperCAmelCase__     :     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
 UpperCAmelCase__     :     Union[str, 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
 ]
 UpperCAmelCase__     :     Dict    					=       [
     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
 ]

 UpperCAmelCase__     :     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
 ]
 UpperCAmelCase__     :     Optional[int]    					=       [
     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
 ]

 UpperCAmelCase__     :     List[str]    					=       [
     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
 ]
 UpperCAmelCase__     :     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
 ]

 UpperCAmelCase__     :     List[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,
     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
 ]
 UpperCAmelCase__     :     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, 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
 ]

 UpperCAmelCase__     :     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
 ]
 UpperCAmelCase__     :     List[str]    					=       [
     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 						lowercase_    (      self	:Tuple						,					_A	:Union[str, Any]      )					->      Union[str, Any]:







       '''simple docstring'''



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






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







       '''simple docstring'''



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

       set_seed(0      )
       __A													=      [torch.zeros(1						,					0						,					dtype=torch.long      ).cpu() for _ in range(3      )]
       __A													=      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													=      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													=      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 						lowercase_    (      self	:Tuple      )					->      Tuple:







       '''simple docstring'''



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

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







       '''simple docstring'''



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

       __A													=      self.prepare_inputs(_A      )[0].cuda()
       __A													=      model.get_metadata(_A						,					0						,					7_680						,					0      )
       set_seed(0      )
       __A													=      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]      )









from __future__ import annotations

from collections.abc import Iterator
from typing import Any

class 					__UpperCamelCase					:







	def __init__( self:			Optional[Any]	,			__UpperCamelCase:			Any   ):

						'''simple docstring'''





						__magic_name__				=     data
						__magic_name__				=     None







	def __str__( self:			Optional[int]   ):

						'''simple docstring'''





						return F'{self.data}'




class 					__UpperCamelCase					:







	def __init__( self:			List[Any]   ):

						'''simple docstring'''





						__magic_name__				=     None
						__magic_name__				=     None







	def __iter__( self:			str   ):

						'''simple docstring'''





						__magic_name__				=     self.front
						while node:
											yield node.data
											__magic_name__				=     node.next







	def __len__( self:			Any   ):

						'''simple docstring'''





						return len(tuple(iter(self   )   )   )







	def __str__( self:			List[str]   ):

						'''simple docstring'''





						return " <- ".join(str(__UpperCamelCase   ) for item in self   )







	def 						_SCREAMING_SNAKE_CASE				( self:			Any   ):

						'''simple docstring'''





						return len(self   ) == 0







	def 						_SCREAMING_SNAKE_CASE				( self:			Any	,			__UpperCamelCase:			Any   ):

						'''simple docstring'''





						__magic_name__				=     Node(__UpperCamelCase   )
						if self.is_empty():
											__magic_name__				=     __magic_name__				=     node
						else:
											assert isinstance(self.rear	,			__UpperCamelCase   )
											__magic_name__				=     node
											__magic_name__				=     node







	def 						_SCREAMING_SNAKE_CASE				( self:			Any   ):

						'''simple docstring'''





						if self.is_empty():
											raise IndexError('dequeue from empty queue'   )
						assert isinstance(self.front	,			__UpperCamelCase   )
						__magic_name__				=     self.front
						__magic_name__				=     self.front.next
						if self.front is None:
											__magic_name__				=     None
						return node.data







	def 						_SCREAMING_SNAKE_CASE				( self:			Tuple   ):

						'''simple docstring'''





						__magic_name__				=     __magic_name__				=     None


if __name__ == "__main__":
						from doctest import testmod

						testmod()




