
'''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				):
     snake_case   :    Optional[Any]							      =      (JukeboxModel,) if is_torch_available() else ()
     snake_case   :    Optional[Any]							      =      """openai/jukebox-1b-lyrics"""
     snake_case   :    int							      =      {
         """artist""": """Zac Brown Band""",
         """genres""": """Country""",
         """lyrics""": """I met a traveller from an antique land,
    Who said \"Two vast and trunkless legs of stone
    Stand in the desert. . . . Near them, on the sand,
    Half sunk a shattered visage lies, whose frown,
    And wrinkled lip, and sneer of cold command,
    Tell that its sculptor well those passions read
    Which yet survive, stamped on these lifeless things,
    The hand that mocked them, and the heart that fed;
    And on the pedestal, these words appear:
    My name is Ozymandias, King of Kings;
    Look on my Works, ye Mighty, and despair!
    Nothing beside remains. Round the decay
    Of that colossal Wreck, boundless and bare
    The lone and level sands stretch far away
    """,
     }
     # fmt: off
     snake_case   :    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
     ]

     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
     ]

     snake_case   :    Optional[int]							      =      [
         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   :    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
     ]

     snake_case   :    Any							      =      [
         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   :    Union[str, 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
     ]

     snake_case   :    List[str]							      =      [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   :    Dict							      =      [
         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[Any]							      =      [
         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   :    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
     ]
     snake_case   :    Optional[int]							      =      [
         -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
     ]
     snake_case   :    List[str]							      =      [
         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
     ]
     snake_case   :    Any							      =      [
         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
     ]
     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	):
          _UpperCAmelCase					:  Optional[Any]         =    JukeboxTokenizer.from_pretrained(self.model_id	)
          _UpperCAmelCase					:  List[str]         =    tokenizer(**self.metas	)["""input_ids"""]
          return tokens



     @slow
     def     snake_case_ (self	):
          _UpperCAmelCase					:  Union[str, Any]         =    JukeboxModel.from_pretrained(self.model_id						,	min_duration=0	).eval()
          _UpperCAmelCase					:  int         =    self.prepare_inputs()

          set_seed(0	)
          _UpperCAmelCase					:  Optional[Any]         =    [torch.zeros(1						,	0						,	dtype=torch.long	).cpu() for _ in range(3	)]
          _UpperCAmelCase					:  int         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[0]						,	sample_length=4_0 * 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					:  List[str]         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[1]						,	sample_length=4_0 * 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					:  List[str]         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[2]						,	sample_length=4_0 * 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	):
          _UpperCAmelCase					:  Tuple         =    False
          _UpperCAmelCase					:  Union[str, Any]         =    JukeboxModel.from_pretrained(self.model_id						,	min_duration=0	).eval()

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

          _UpperCAmelCase					:  Optional[int]         =    model.priors[0]
          _UpperCAmelCase					:  Optional[Any]         =    0
          _UpperCAmelCase					:  Dict         =    top_prior.get_music_tokens_conds(lowerCAmelCase__						,	start=lowerCAmelCase__						,	end=start + top_prior.n_ctx	)
          _UpperCAmelCase					:  Optional[Any]         =    top_prior.get_metadata(labels[0].clone()						,	lowerCAmelCase__						,	1_0_5_8_3_0_4						,	0	)

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

          _UpperCAmelCase  ,     _UpperCAmelCase  ,     _UpperCAmelCase					:  Dict         =    top_prior.get_cond(lowerCAmelCase__						,	lowerCAmelCase__	)
          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     snake_case_ (self	):
          _UpperCAmelCase					:  Any         =    False

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

          _UpperCAmelCase					:  List[str]         =    [model.vqvae.encode(lowerCAmelCase__						,	start_level=2						,	bs_chunks=waveform.shape[0]	)[0], None, None]
          _UpperCAmelCase					:  Tuple         =    model._sample(
              lowerCAmelCase__						,	lowerCAmelCase__						,	sample_levels=[0]						,	save_results=lowerCAmelCase__						,	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					:  Optional[Any]         =    torch.cat((zs[0], torch.zeros(1						,	2_0_4_8 - zs[0].shape[-1]	))						,	dim=-1	).long()
          _UpperCAmelCase					:  int         =    [upper_a, model.vqvae.encode(lowerCAmelCase__						,	start_level=1						,	bs_chunks=waveform.shape[0]	)[0], None]
          _UpperCAmelCase					:  str         =    model._sample(
              lowerCAmelCase__						,	lowerCAmelCase__						,	sample_levels=[1]						,	save_results=lowerCAmelCase__						,	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					:  List[str]         =    torch.cat((zs[1], torch.zeros(1						,	2_0_4_8 - zs[1].shape[-1]	))						,	dim=-1	).long()
          _UpperCAmelCase					:  Dict         =    [upper_a, upper_a, model.vqvae.encode(lowerCAmelCase__						,	start_level=0						,	bs_chunks=waveform.shape[0]	)[0]]
          _UpperCAmelCase					:  Optional[int]         =    model._sample(
              lowerCAmelCase__						,	lowerCAmelCase__						,	sample_levels=[2]						,	save_results=lowerCAmelCase__						,	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     snake_case_ (self	):
          _UpperCAmelCase					:  List[str]         =    JukeboxModel.from_pretrained(self.model_id						,	min_duration=0	).eval()
          set_seed(0	)
          _UpperCAmelCase					:  str         =    torch.rand((1, 5_1_2_0, 1)	)
          with torch.no_grad():
               _UpperCAmelCase					:  Any         =    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					:  Union[str, Any]         =    model.vqvae.decode(lowerCAmelCase__						,	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 	__lowerCAmelCase    (  unittest.TestCase				):
     snake_case   :    Union[str, Any]							      =      (JukeboxModel,) if is_torch_available() else ()
     snake_case   :    Union[str, Any]							      =      """openai/jukebox-5b-lyrics"""
     snake_case   :    Dict							      =      {
         """artist""": """Zac Brown Band""",
         """genres""": """Country""",
         """lyrics""": """I met a traveller from an antique land,
    Who said \"Two vast and trunkless legs of stone
    Stand in the desert. . . . Near them, on the sand,
    Half sunk a shattered visage lies, whose frown,
    And wrinkled lip, and sneer of cold command,
    Tell that its sculptor well those passions read
    Which yet survive, stamped on these lifeless things,
    The hand that mocked them, and the heart that fed;
    And on the pedestal, these words appear:
    My name is Ozymandias, King of Kings;
    Look on my Works, ye Mighty, and despair!
    Nothing beside remains. Round the decay
    Of that colossal Wreck, boundless and bare
    The lone and level sands stretch far away
    """,
     }

     # fmt: off
     snake_case   :    Optional[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,
         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   :    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
     ]

     snake_case   :    Tuple							      =      [
         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   :    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
     ]

     snake_case   :    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   :    str							      =      [
         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   :    Optional[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   :    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, 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   :    Dict							      =      [
         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   :    List[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						,	lowerCAmelCase__	):
          _UpperCAmelCase					:  str         =    JukeboxTokenizer.from_pretrained(lowerCAmelCase__	)
          _UpperCAmelCase					:  Tuple         =    tokenizer(**self.metas	)["""input_ids"""]
          return tokens



     @slow
     def     snake_case_ (self	):
          _UpperCAmelCase					:  Dict         =    JukeboxModel.from_pretrained(self.model_id						,	min_duration=0	).eval()
          _UpperCAmelCase					:  Optional[Any]         =    self.prepare_inputs(self.model_id	)

          set_seed(0	)
          _UpperCAmelCase					:  Union[str, Any]         =    [torch.zeros(1						,	0						,	dtype=torch.long	).cpu() for _ in range(3	)]
          _UpperCAmelCase					:  List[Any]         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[0]						,	sample_length=6_0 * 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					:  List[str]         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[1]						,	sample_length=6_0 * 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					:  Optional[Any]         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[2]						,	sample_length=6_0 * 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	):
          _UpperCAmelCase					:  Tuple         =    JukeboxModel.from_pretrained(self.model_id						,	min_duration=0	).eval()
          _UpperCAmelCase					:  Dict         =    [i.cuda() for i in self.prepare_inputs(self.model_id	)]

          set_seed(0	)
          model.priors[0].cuda()
          _UpperCAmelCase					:  Any         =    [torch.zeros(1						,	0						,	dtype=torch.long	).cuda() for _ in range(3	)]
          _UpperCAmelCase					:  List[str]         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[0]						,	sample_length=6_0 * 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					:  Optional[Any]         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[1]						,	sample_length=6_0 * 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					:  Optional[Any]         =    model._sample(lowerCAmelCase__						,	lowerCAmelCase__						,	[2]						,	sample_length=6_0 * 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	):
          _UpperCAmelCase					:  Dict         =    """ArthurZ/jukebox_prior_0"""
          _UpperCAmelCase					:  int         =    JukeboxPrior.from_pretrained(lowerCAmelCase__						,	min_duration=0	).eval().half().to("""cuda"""	)

          _UpperCAmelCase					:  int         =    self.prepare_inputs(lowerCAmelCase__	)[0].cuda()
          _UpperCAmelCase					:  str         =    model.get_metadata(lowerCAmelCase__						,	0						,	7_6_8_0						,	0	)
          set_seed(0	)
          _UpperCAmelCase					:  Any         =    model.sample(1						,	metadata=lowerCAmelCase__						,	sample_tokens=6_0	)
          self.assertIn(outputs[0].cpu().tolist()						,	[self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]	)










"""simple docstring"""



def      SCREAMING_SNAKE_CASE__    (   snake_case    :      str							)->						str:






     '''simple docstring'''



     UpperCAmelCase__		:  Tuple				=				word.upper()
     UpperCAmelCase__		:  Union[str, Any]				=				0
     UpperCAmelCase__		:  Optional[Any]				=				{}
     UpperCAmelCase__		:  List[Any]				=				[]

     for letter in word:
          if letter not in letter_nums:
               UpperCAmelCase__		:  Tuple				=				str(snake_case							)
               next_num += 1
          word_pattern.append(letter_nums[letter]							)
     return ".".join(snake_case							)


if __name__ == "__main__":
 import pprint
 import time

 _lowerCAmelCase     :     Optional[Any]            =	time.time()
 with open("""dictionary.txt""") as in_file:
  _lowerCAmelCase     :     Optional[int]            =	in_file.read().splitlines()

 _lowerCAmelCase     :     dict            =	{}
 for word in word_list:
  _lowerCAmelCase     :     int            =	get_word_pattern(word)
  if pattern in all_patterns:
   all_patterns[pattern].append(word)
  else:
   _lowerCAmelCase     :     Any            =	[word]

 with open("""word_patterns.txt""", """w""") as out_file:
  out_file.write(pprint.pformat(all_patterns))

 _lowerCAmelCase     :     Union[str, Any]            =	round(time.time() - start_time, 2)
 print(F"""Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.""")
 # Done!  9,581 word patterns found in 0.58 seconds.


