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 	_lowercase		(      unittest.TestCase ):
 lowercase         =     (JukeboxModel,) if is_torch_available() else ()
 lowercase         =     'openai/jukebox-1b-lyrics'
 lowercase         =     {
     '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
 lowercase         =     [
     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
 ]

 lowercase         =     [
     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
 ]

 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]

 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]

 lowercase         =     [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]

 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]
 lowercase         =     [
     -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
 ]
 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]
 lowercase         =     [
     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 		SCREAMING_SNAKE_CASE__     (				self			:							Any    )     ->		Optional[int]:

  """simple docstring"""





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

 @slow
 def 		SCREAMING_SNAKE_CASE__     (				self			:							Optional[int]    )     ->		Tuple:

  """simple docstring"""





  UpperCamelCase_      :		Tuple				=      JukeboxModel.from_pretrained(self.model_id     ,   min_duration=0    ).eval()
  UpperCamelCase_      :		Any				=      self.prepare_inputs()

  set_seed(0    )
  UpperCamelCase_      :		Any				=      [torch.zeros(1     ,   0     ,   dtype=torch.long    ).cpu() for _ in range(3    )]
  UpperCamelCase_      :		int				=      model._sample(snake_case     ,   snake_case     ,   [0]     ,   sample_length=4_0 * model.priors[0].raw_to_tokens     ,   save_results=snake_case    )
  self.assertIn(zs[0][0].detach().cpu().tolist()     ,   [self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]    )

  set_seed(0    )
  UpperCamelCase_      :		str				=      model._sample(snake_case     ,   snake_case     ,   [1]     ,   sample_length=4_0 * model.priors[1].raw_to_tokens     ,   save_results=snake_case    )
  self.assertIn(zs[1][0].detach().cpu().tolist()     ,   [self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]    )

  set_seed(0    )
  UpperCamelCase_      :		Tuple				=      model._sample(snake_case     ,   snake_case     ,   [2]     ,   sample_length=4_0 * model.priors[2].raw_to_tokens     ,   save_results=snake_case    )
  self.assertIn(zs[2][0].detach().cpu().tolist()     ,   [self.EXPECTED_OUTPUT_0, self.EXPECTED_OUTPUT_0_PT_2]    )

 @slow
 def 		SCREAMING_SNAKE_CASE__     (				self			:							List[Any]    )     ->		Union[str, Any]:

  """simple docstring"""





  UpperCamelCase_      :		int				=      False
  UpperCamelCase_      :		str				=      JukeboxModel.from_pretrained(self.model_id     ,   min_duration=0    ).eval()

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

  UpperCamelCase_      :		List[str]				=      model.priors[0]
  UpperCamelCase_      :		str				=      0
  UpperCamelCase_      :		List[str]				=      top_prior.get_music_tokens_conds(snake_case     ,   start=snake_case     ,   end=start + top_prior.n_ctx    )
  UpperCamelCase_      :		int				=      top_prior.get_metadata(labels[0].clone()     ,   snake_case     ,   1_0_5_8_3_0_4     ,   0    )

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

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

 @slow
 def 		SCREAMING_SNAKE_CASE__     (				self			:							Dict    )     ->		str:

  """simple docstring"""





  UpperCamelCase_      :		Optional[Any]				=      False

  UpperCamelCase_      :		Optional[int]				=      JukeboxModel.from_pretrained(self.model_id     ,   min_duration=0    ).eval()
  set_seed(0    )
  UpperCamelCase_      :		List[Any]				=      torch.rand((1, 5_1_2_0, 1)    )
  UpperCamelCase_      :		int				=      list(self.prepare_inputs()    )

  UpperCamelCase_      :		List[str]				=      [model.vqvae.encode(snake_case     ,   start_level=2     ,   bs_chunks=waveform.shape[0]    )[0], None, None]
  UpperCamelCase_      :		Tuple				=      model._sample(
      snake_case     ,   snake_case     ,   sample_levels=[0]     ,   save_results=snake_case     ,   sample_length=4_0 * model.priors[0].raw_to_tokens    )
  torch.testing.assert_allclose(zs[0][0][:4_0]     ,   torch.tensor(self.EXPECTED_PRIMED_0    )    )

  UpperCamelCase_      :		List[str]				=      torch.cat((zs[0], torch.zeros(1     ,   2_0_4_8 - zs[0].shape[-1]    ))     ,   dim=-1    ).long()
  UpperCamelCase_      :		Tuple				=      [upper_a, model.vqvae.encode(snake_case     ,   start_level=1     ,   bs_chunks=waveform.shape[0]    )[0], None]
  UpperCamelCase_      :		List[Any]				=      model._sample(
      snake_case     ,   snake_case     ,   sample_levels=[1]     ,   save_results=snake_case     ,   sample_length=4_0 * model.priors[1].raw_to_tokens    )
  torch.testing.assert_allclose(zs[1][0][:4_0]     ,   torch.tensor(self.EXPECTED_PRIMED_1    )    )

  UpperCamelCase_      :		Dict				=      torch.cat((zs[1], torch.zeros(1     ,   2_0_4_8 - zs[1].shape[-1]    ))     ,   dim=-1    ).long()
  UpperCamelCase_      :		List[str]				=      [upper_a, upper_a, model.vqvae.encode(snake_case     ,   start_level=0     ,   bs_chunks=waveform.shape[0]    )[0]]
  UpperCamelCase_      :		Tuple				=      model._sample(
      snake_case     ,   snake_case     ,   sample_levels=[2]     ,   save_results=snake_case     ,   sample_length=4_0 * model.priors[2].raw_to_tokens    )
  torch.testing.assert_allclose(zs[2][0][:4_0].cpu()     ,   torch.tensor(self.EXPECTED_PRIMED_2    )    )


 @slow
 def 		SCREAMING_SNAKE_CASE__     (				self			:							int    )     ->		List[str]:

  """simple docstring"""





  UpperCamelCase_      :		Optional[Any]				=      JukeboxModel.from_pretrained(self.model_id     ,   min_duration=0    ).eval()
  set_seed(0    )
  UpperCamelCase_      :		Optional[Any]				=      torch.rand((1, 5_1_2_0, 1)    )
  with torch.no_grad():
   UpperCamelCase_      :		Union[str, Any]				=      model.vqvae.encode(snake_case     ,   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_      :		Dict				=      model.vqvae.decode(snake_case     ,   start_level=2     ,   bs_chunks=x.shape[0]    )
  torch.testing.assert_allclose(x[0, :4_0, 0]     ,   torch.tensor(self.EXPECTED_VQVAE_DECODE    )     ,   atol=1e-4     ,   rtol=1e-4    )





@require_torch
class 	_lowercase		(      unittest.TestCase ):
 lowercase         =     (JukeboxModel,) if is_torch_available() else ()
 lowercase         =     'openai/jukebox-5b-lyrics'
 lowercase         =     {
     '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
 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]

 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]

 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]

 lowercase         =     [
     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
 ]
 lowercase         =     [
     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
 ]

 lowercase         =     [
     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
 ]
 lowercase         =     [
     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 		SCREAMING_SNAKE_CASE__     (				self			:							Dict     ,   snake_case			:							Optional[int]    )     ->		List[str]:

  """simple docstring"""





  UpperCamelCase_      :		str				=      JukeboxTokenizer.from_pretrained(snake_case    )
  UpperCamelCase_      :		Optional[int]				=      tokenizer(**self.metas    )['input_ids']
  return tokens

 @slow
 def 		SCREAMING_SNAKE_CASE__     (				self			:							List[str]    )     ->		List[Any]:

  """simple docstring"""





  UpperCamelCase_      :		int				=      JukeboxModel.from_pretrained(self.model_id     ,   min_duration=0    ).eval()
  UpperCamelCase_      :		str				=      self.prepare_inputs(self.model_id    )

  set_seed(0    )
  UpperCamelCase_      :		Optional[Any]				=      [torch.zeros(1     ,   0     ,   dtype=torch.long    ).cpu() for _ in range(3    )]
  UpperCamelCase_      :		Dict				=      model._sample(snake_case     ,   snake_case     ,   [0]     ,   sample_length=6_0 * model.priors[0].raw_to_tokens     ,   save_results=snake_case    )
  self.assertIn(zs[0][0].detach().cpu().tolist()     ,   [self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]    )

  set_seed(0    )
  UpperCamelCase_      :		str				=      model._sample(snake_case     ,   snake_case     ,   [1]     ,   sample_length=6_0 * model.priors[1].raw_to_tokens     ,   save_results=snake_case    )
  self.assertIn(zs[1][0].detach().cpu().tolist()     ,   [self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]    )

  set_seed(0    )
  UpperCamelCase_      :		Union[str, Any]				=      model._sample(snake_case     ,   snake_case     ,   [2]     ,   sample_length=6_0 * model.priors[2].raw_to_tokens     ,   save_results=snake_case    )
  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 		SCREAMING_SNAKE_CASE__     (				self			:							Union[str, Any]    )     ->		Union[str, Any]:

  """simple docstring"""





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

  set_seed(0    )
  model.priors[0].cuda()
  UpperCamelCase_      :		Optional[Any]				=      [torch.zeros(1     ,   0     ,   dtype=torch.long    ).cuda() for _ in range(3    )]
  UpperCamelCase_      :		Union[str, Any]				=      model._sample(snake_case     ,   snake_case     ,   [0]     ,   sample_length=6_0 * model.priors[0].raw_to_tokens     ,   save_results=snake_case    )
  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_      :		Any				=      model._sample(snake_case     ,   snake_case     ,   [1]     ,   sample_length=6_0 * model.priors[1].raw_to_tokens     ,   save_results=snake_case    )
  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_      :		str				=      model._sample(snake_case     ,   snake_case     ,   [2]     ,   sample_length=6_0 * model.priors[2].raw_to_tokens     ,   save_results=snake_case    )
  torch.testing.assert_allclose(zs[2][0].cpu()     ,   torch.tensor(self.EXPECTED_GPU_OUTPUTS_0    )    )


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

  """simple docstring"""





  UpperCamelCase_      :		int				=      'ArthurZ/jukebox_prior_0'
  UpperCamelCase_      :		Optional[int]				=      JukeboxPrior.from_pretrained(snake_case     ,   min_duration=0    ).eval().half().to('cuda'    )

  UpperCamelCase_      :		Optional[Any]				=      self.prepare_inputs(snake_case    )[0].cuda()
  UpperCamelCase_      :		List[Any]				=      model.get_metadata(snake_case     ,   0     ,   7_6_8_0     ,   0    )
  set_seed(0    )
  UpperCamelCase_      :		Union[str, Any]				=      model.sample(1     ,   metadata=snake_case     ,   sample_tokens=6_0    )
  self.assertIn(outputs[0].cpu().tolist()     ,   [self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]    )




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a_					      = {
    'configuration_marian': ['MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MarianConfig', 'MarianOnnxConfig'],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a_					      = ['MarianTokenizer']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a_					      = [
       'MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST',
       'MarianForCausalLM',
       'MarianModel',
       'MarianMTModel',
       'MarianPreTrainedModel',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a_					      = ['TFMarianModel', 'TFMarianMTModel', 'TFMarianPreTrainedModel']

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a_					      = ['FlaxMarianModel', 'FlaxMarianMTModel', 'FlaxMarianPreTrainedModel']

if TYPE_CHECKING:
   from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_marian import MarianTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_marian import (
          MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
          MarianForCausalLM,
          MarianModel,
          MarianMTModel,
          MarianPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
   import sys

   a_					      = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



