






from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_openai import OpenAIGPTTokenizer


snake_case_   :	Any							      =logging.get_logger(__name__)

snake_case_   :	List[str]							      ={'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case_   :	Dict							      ={
    '''vocab_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/vocab.json'''},
    '''merges_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/merges.txt'''},
    '''tokenizer_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/tokenizer.json'''},
}

snake_case_   :	Union[str, Any]							      ={
    '''openai-gpt''': 512,
}





class        a__      (	lowerCAmelCase__		):
		UpperCAmelCase_							:       int 					= VOCAB_FILES_NAMES
		UpperCAmelCase_							:       Union[str, Any] 					= PRETRAINED_VOCAB_FILES_MAP
		UpperCAmelCase_							:       Tuple 					= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		UpperCAmelCase_							:       Tuple 					= ['input_ids', 'attention_mask']
		UpperCAmelCase_							:       Optional[Any] 					= OpenAIGPTTokenizer






		def __init__(      self							, lowercase__=None							, lowercase__=None							, lowercase__=None							, lowercase__="<unk>"							, **lowercase__						)				->				Optional[Any]:
				super().__init__(lowercase__							, lowercase__							, tokenizer_file=lowercase__							, unk_token=lowercase__							, **lowercase__						)






		@property
		def 					_lowerCamelCase					(      self						)				->				Any:
				return True






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				Tuple[str]:
				__A    =							self._tokenizer.model.save(lowercase__							, name=lowercase__						)
				return tuple(lowercase__						)





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):


       """simple docstring"""




       A__   		=     (JukeboxModel,) if is_torch_available() else ()
       A__   		=     "openai/jukebox-1b-lyrics"
       A__   		=     {
           "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
       A__   		=     [
           18_64, 15_36, 12_13, 18_70, 13_57, 15_36, 5_19, 8_80, 13_23, 7_89, 10_82, 5_34,
           10_00, 14_45, 11_05, 11_30, 9_67, 5_15, 14_34, 16_20, 5_34, 14_95, 2_83, 14_45,
           3_33, 13_07, 5_39, 16_31, 15_28, 3_75, 14_34, 6_73, 6_27, 7_10, 7_78, 18_83,
           14_05, 12_76, 14_55, 12_28
       ]

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

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

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

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

       A__   		=     [
           3_90, 11_60, 10_02, 19_07, 17_88, 17_88, 17_88, 19_07, 10_02, 10_02, 18_54, 10_02,
           10_02, 10_02, 10_02, 10_02, 10_02, 11_60, 11_60, 16_06, 5_96, 5_96, 11_60, 10_02,
           15_16, 5_96, 10_02, 10_02, 10_02, 19_07, 17_88, 17_88, 17_88, 18_54, 17_88, 19_07,
           19_07, 17_88, 5_96, 16_26
       ]
       A__   		=     [
           12_36, 16_68, 14_84, 19_20, 18_48, 14_09, 1_39, 8_64, 18_28, 12_72, 15_99, 8_24,
           16_72, 1_39, 5_55, 14_84, 8_24, 19_20, 5_55, 5_96, 15_79, 15_99, 12_31, 15_99,
           16_37, 14_07, 2_12, 8_24, 15_99, 1_16, 14_33, 8_24, 2_58, 15_99, 14_33, 18_95,
           10_63, 14_33, 14_33, 15_99
       ]
       A__   		=     [
           16_84, 18_73, 11_19, 11_89, 3_95, 6_11, 19_01, 9_72, 8_90, 13_37, 13_92, 19_27,
           96, 9_72, 6_72, 7_80, 11_19, 8_90, 1_58, 7_71, 10_73, 19_27, 3_53, 13_31,
           12_69, 14_59, 13_33, 16_45, 8_12, 15_77, 13_37, 6_06, 3_53, 9_81, 14_66, 6_19,
           1_97, 3_91, 3_02, 19_30
       ]
       A__   		=     [
           3_90, 11_60, 10_02, 19_07, 17_88, 17_88, 17_88, 19_07, 10_02, 10_02, 18_54, 10_02,
           10_02, 10_02, 10_02, 10_02, 10_02, 11_60, 11_60, 16_06, 5_96, 5_96, 11_60, 10_02,
           15_16, 5_96, 10_02, 10_02, 10_02, 19_07, 17_88, 17_88, 17_88, 18_54, 17_88, 19_07,
           19_07, 17_88, 5_96, 16_26
       ]
       A__   		=     [
           -0.0_492, -0.0_524, -0.0_565, -0.0_640, -0.0_686, -0.0_684, -0.0_677, -0.0_664,
           -0.0_605, -0.0_490, -0.0_330, -0.0_168, -0.0_083, -0.0_075, -0.0_051, 0.0_025,
           0.0_136, 0.0_261, 0.0_386, 0.0_497, 0.0_580, 0.0_599, 0.0_583, 0.0_614,
           0.0_740, 0.0_889, 0.1_023, 0.1_162, 0.1_211, 0.1_212, 0.1_251, 0.1_336,
           0.1_502, 0.1_686, 0.1_883, 0.2_148, 0.2_363, 0.2_458, 0.2_507, 0.2_531
       ]
       A__   		=     [
           0.0_256, -0.0_544, 0.1_600, -0.0_032, 0.1_066, 0.0_825, -0.0_013, 0.3_440,
           0.0_210, 0.0_412, -0.1_777, -0.0_892, -0.0_164, 0.0_285, -0.0_613, -0.0_617,
           -0.0_137, -0.0_201, -0.0_175, 0.0_215, -0.0_627, 0.0_520, -0.0_730, 0.0_970,
           -0.0_100, 0.0_442, -0.0_586, 0.0_207, -0.0_015, -0.0_082
       ]
       A__   		=     [
           0.0_415, 0.0_877, 0.0_022, -0.0_055, 0.0_751, 0.0_334, 0.0_324, -0.0_068,
           0.0_011, 0.0_017, -0.0_676, 0.0_655, -0.0_143, 0.0_399, 0.0_303, 0.0_743,
           -0.0_168, -0.0_394, -0.1_113, 0.0_124, 0.0_442, 0.0_267, -0.0_003, -0.1_536,
           -0.0_116, -0.1_837, -0.0_180, -0.1_026, -0.0_777, -0.0_456
       ]
       A__   		=     [
           76, 27, 40, 30, 76, 46, 44, 47, 40, 37, 38, 31, 45, 45, 76, 38, 31, 33,
           45, 76, 41, 32, 76, 45, 46, 41, 40, 31, 78, 76
       ]





       def 		lowerCAmelCase	(  self				:     Optional[int]			):


             '''simple docstring'''



             lowerCamelCase__						:							Tuple       =    JukeboxTokenizer.from_pretrained(self.model_id			)
             lowerCamelCase__						:							Dict       =    tokenizer(**self.metas			)["input_ids"]
             return tokens





       @slow
       def 		lowerCAmelCase	(  self				:     Optional[Any]			):


             '''simple docstring'''



             lowerCamelCase__						:							Optional[int]       =    JukeboxModel.from_pretrained(self.model_id   , min_duration=0			).eval()
             lowerCamelCase__						:							Optional[Any]       =    self.prepare_inputs()

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


             '''simple docstring'''



             lowerCamelCase__						:							str       =    False
             lowerCamelCase__						:							Any       =    JukeboxModel.from_pretrained(self.model_id   , min_duration=0			).eval()

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

             lowerCamelCase__						:							Optional[int]       =    model.priors[0]
             lowerCamelCase__						:							List[str]       =    0
             lowerCamelCase__						:							List[str]       =    top_prior.get_music_tokens_conds(__lowerCamelCase   , start=__lowerCamelCase   , end=start + top_prior.n_ctx			)
             lowerCamelCase__						:							List[Any]       =    top_prior.get_metadata(labels[0].clone()   , __lowerCamelCase   , 1058304   , 0			)

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

             lowerCamelCase__       ,  lowerCamelCase__       ,  lowerCamelCase__						:							str       =    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 		lowerCAmelCase	(  self				:     Optional[Any]			):


             '''simple docstring'''



             lowerCamelCase__						:							Dict       =    False

             lowerCamelCase__						:							List[Any]       =    JukeboxModel.from_pretrained(self.model_id   , min_duration=0			).eval()
             set_seed(0			)
             lowerCamelCase__						:							int       =    torch.rand((1, 5120, 1)			)
             lowerCamelCase__						:							int       =    list(self.prepare_inputs()			)

             lowerCamelCase__						:							List[str]       =    [model.vqvae.encode(__lowerCamelCase   , start_level=2   , bs_chunks=waveform.shape[0]			)[0], None, None]
             lowerCamelCase__						:							str       =    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			)			)

             lowerCamelCase__						:							Tuple       =    torch.cat((zs[0], torch.zeros(1   , 2048 - zs[0].shape[-1]			))   , dim=-1			).long()
             lowerCamelCase__						:							Dict       =    [upper_a, model.vqvae.encode(__lowerCamelCase   , start_level=1   , bs_chunks=waveform.shape[0]			)[0], None]
             lowerCamelCase__						:							str       =    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			)			)

             lowerCamelCase__						:							List[Any]       =    torch.cat((zs[1], torch.zeros(1   , 2048 - zs[1].shape[-1]			))   , dim=-1			).long()
             lowerCamelCase__						:							Union[str, Any]       =    [upper_a, upper_a, model.vqvae.encode(__lowerCamelCase   , start_level=0   , bs_chunks=waveform.shape[0]			)[0]]
             lowerCamelCase__						:							str       =    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 		lowerCAmelCase	(  self				:     Optional[Any]			):


             '''simple docstring'''



             lowerCamelCase__						:							int       =    JukeboxModel.from_pretrained(self.model_id   , min_duration=0			).eval()
             set_seed(0			)
             lowerCamelCase__						:							Dict       =    torch.rand((1, 5120, 1)			)
             with torch.no_grad():
                   lowerCamelCase__						:							Optional[int]       =    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():
                   lowerCamelCase__						:							Tuple       =    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      _lowercase					(				unittest.TestCase):


       """simple docstring"""




       A__   		=     (JukeboxModel,) if is_torch_available() else ()
       A__   		=     "openai/jukebox-5b-lyrics"
       A__   		=     {
           "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
       A__   		=     [
           14_89, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           14_89, 14_89, 14_89, 14_89, 11_50, 18_53, 15_09, 11_50, 13_57, 15_09, 6, 12_72
       ]
       A__   		=     [
           14_89, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53,
           6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53, 6_53
       ]

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

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

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

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





       def 		lowerCAmelCase	(  self				:     Tuple   , __lowerCamelCase				:     List[Any]			):


             '''simple docstring'''



             lowerCamelCase__						:							str       =    JukeboxTokenizer.from_pretrained(__lowerCamelCase			)
             lowerCamelCase__						:							List[Any]       =    tokenizer(**self.metas			)["input_ids"]
             return tokens





       @slow
       def 		lowerCAmelCase	(  self				:     Tuple			):


             '''simple docstring'''



             lowerCamelCase__						:							List[str]       =    JukeboxModel.from_pretrained(self.model_id   , min_duration=0			).eval()
             lowerCamelCase__						:							Dict       =    self.prepare_inputs(self.model_id			)

             set_seed(0			)
             lowerCamelCase__						:							int       =    [torch.zeros(1   , 0   , dtype=torch.long			).cpu() for _ in range(3			)]
             lowerCamelCase__						:							Union[str, Any]       =    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			)
             lowerCamelCase__						:							List[Any]       =    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			)
             lowerCamelCase__						:							Tuple       =    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 		lowerCAmelCase	(  self				:     Union[str, Any]			):


             '''simple docstring'''



             lowerCamelCase__						:							Optional[Any]       =    JukeboxModel.from_pretrained(self.model_id   , min_duration=0			).eval()
             lowerCamelCase__						:							Optional[int]       =    [i.cuda() for i in self.prepare_inputs(self.model_id			)]

             set_seed(0			)
             model.priors[0].cuda()
             lowerCamelCase__						:							Tuple       =    [torch.zeros(1   , 0   , dtype=torch.long			).cuda() for _ in range(3			)]
             lowerCamelCase__						:							List[Any]       =    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()
             lowerCamelCase__						:							Dict       =    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()
             lowerCamelCase__						:							Tuple       =    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 		lowerCAmelCase	(  self				:     int			):


             '''simple docstring'''



             lowerCamelCase__						:							Tuple       =    "ArthurZ/jukebox_prior_0"
             lowerCamelCase__						:							Optional[Any]       =    JukeboxPrior.from_pretrained(__lowerCamelCase   , min_duration=0			).eval().half().to("cuda"			)

             lowerCamelCase__						:							Dict       =    self.prepare_inputs(__lowerCamelCase			)[0].cuda()
             lowerCamelCase__						:							Union[str, Any]       =    model.get_metadata(__lowerCamelCase   , 0   , 7680   , 0			)
             set_seed(0			)
             lowerCamelCase__						:							Optional[int]       =    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]			)


