
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
		from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


__SCREAMING_SNAKE_CASE     :				int             =       logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE     :				Union[str, Any]             =       {
    'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/config.json',
    'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/config.json',
    'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json',
    'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json',
    'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json',
    'microsoft/deberta-xlarge-mnli': 'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json',
}


class 						__magic_name__				(  snake_case      ):
		_lowerCAmelCase						=		"deberta"





		def __init__(							self      :		Dict  ,					lowerCamelCase__      :		Dict=5_0_2_6_5  ,					lowerCamelCase__      :		List[Any]=7_6_8  ,					lowerCamelCase__      :		Optional[int]=1_2  ,					lowerCamelCase__      :		List[str]=1_2  ,					lowerCamelCase__      :		Optional[Any]=3_0_7_2  ,					lowerCamelCase__      :		Optional[Any]="gelu"  ,					lowerCamelCase__      :		str=0.1  ,					lowerCamelCase__      :		List[str]=0.1  ,					lowerCamelCase__      :		Dict=5_1_2  ,					lowerCamelCase__      :		List[str]=0  ,					lowerCamelCase__      :		int=0.0_2  ,					lowerCamelCase__      :		Dict=1E-7  ,					lowerCamelCase__      :		Dict=False  ,					lowerCamelCase__      :		List[str]=-1  ,					lowerCamelCase__      :		Optional[int]=0  ,					lowerCamelCase__      :		int=True  ,					lowerCamelCase__      :		List[str]=None  ,					lowerCamelCase__      :		List[Any]=0  ,					lowerCamelCase__      :		int="gelu"  ,					**lowerCamelCase__      :		str  ,					):
							super().__init__(**lowerCamelCase__			)

							lowerCAmelCase						:   Any							=       hidden_size
							lowerCAmelCase						:   Optional[int]							=       num_hidden_layers
							lowerCAmelCase						:   List[Any]							=       num_attention_heads
							lowerCAmelCase						:   Optional[int]							=       intermediate_size
							lowerCAmelCase						:   Optional[int]							=       hidden_act
							lowerCAmelCase						:   Union[str, Any]							=       hidden_dropout_prob
							lowerCAmelCase						:   Optional[int]							=       attention_probs_dropout_prob
							lowerCAmelCase						:   List[str]							=       max_position_embeddings
							lowerCAmelCase						:   Any							=       type_vocab_size
							lowerCAmelCase						:   str							=       initializer_range
							lowerCAmelCase						:   Dict							=       relative_attention
							lowerCAmelCase						:   List[str]							=       max_relative_positions
							lowerCAmelCase						:   Dict							=       pad_token_id
							lowerCAmelCase						:   int							=       position_biased_input

							# Backwards compatibility
							if type(lowerCamelCase__			) == str:
												lowerCAmelCase						:   int							=       [x.strip() for x in pos_att_type.lower().split('''|'''			)]

							lowerCAmelCase						:   Union[str, Any]							=       pos_att_type
							lowerCAmelCase						:   str							=       vocab_size
							lowerCAmelCase						:   List[str]							=       layer_norm_eps

							lowerCAmelCase						:   Tuple							=       kwargs.get('''pooler_hidden_size'''  ,					lowerCamelCase__			)
							lowerCAmelCase						:   Optional[int]							=       pooler_dropout
							lowerCAmelCase						:   Union[str, Any]							=       pooler_hidden_act



class 						__magic_name__				(  snake_case      ):





		@property
		def  _A							(							self      :		int			):
							if self.task == "multiple-choice":
												lowerCAmelCase						:   Optional[int]							=       {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
												lowerCAmelCase						:   Optional[int]							=       {0: '''batch''', 1: '''sequence'''}
							if self._config.type_vocab_size > 0:
												return OrderedDict(
												    [('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis), ('''token_type_ids''', dynamic_axis)]			)
							else:
												return OrderedDict([('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis)]			)





		@property
		def  _A							(							self      :		Tuple			):
							return 1_2





		def  _A							(							self      :		List[Any]  ,					lowerCamelCase__      :		Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]  ,					lowerCamelCase__      :		int = -1  ,					lowerCamelCase__      :		int = -1  ,					lowerCamelCase__      :		int = -1  ,					lowerCamelCase__      :		bool = False  ,					lowerCamelCase__      :		Optional["TensorType"] = None  ,					lowerCamelCase__      :		int = 3  ,					lowerCamelCase__      :		int = 4_0  ,					lowerCamelCase__      :		int = 4_0  ,					lowerCamelCase__      :		"PreTrainedTokenizerBase" = None  ,					):
							lowerCAmelCase						:   Union[str, Any]							=       super().generate_dummy_inputs(preprocessor=lowerCamelCase__  ,					framework=lowerCamelCase__			)
							if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
												del dummy_inputs["token_type_ids"]
							return dummy_inputs


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 						__magic_name__				(  unittest.TestCase      ):
		_lowerCAmelCase						=		(JukeboxModel,) if is_torch_available() else ()
		_lowerCAmelCase						=		"openai/jukebox-1b-lyrics"
		_lowerCAmelCase						=		{
		    "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
		_lowerCAmelCase						=		[
		    1_864, 1_536, 1_213, 1_870, 1_357, 1_536, 519, 880, 1_323, 789, 1_082, 534,
		    1_000, 1_445, 1_105, 1_130, 967, 515, 1_434, 1_620, 534, 1_495, 283, 1_445,
		    333, 1_307, 539, 1_631, 1_528, 375, 1_434, 673, 627, 710, 778, 1_883,
		    1_405, 1_276, 1_455, 1_228
		]

		_lowerCAmelCase						=		[
		    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653
		]

		_lowerCAmelCase						=		[
		    1_125, 1_751, 697, 1_776, 1_141, 1_476, 391, 697, 1_125, 684, 867, 416,
		    844, 1_372, 1_274, 717, 1_274, 844, 1_299, 1_419, 697, 1_370, 317, 1_125,
		    191, 1_440, 1_370, 1_440, 1_370, 282, 1_621, 1_370, 368, 349, 867, 1_872,
		    1_262, 869, 1_728, 747
		]
		_lowerCAmelCase						=		[
		    416, 416, 1_125, 1_125, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416
		]

		_lowerCAmelCase						=		[
		    1_755, 842, 307, 1_843, 1_022, 1_395, 234, 1_554, 806, 739, 1_022, 442,
		    616, 556, 268, 1_499, 933, 457, 1_440, 1_837, 755, 985, 308, 902,
		    293, 1_443, 1_671, 1_141, 1_533, 555, 1_562, 1_061, 287, 417, 1_022, 2_008,
		    1_186, 1_015, 1_777, 268
		]
		_lowerCAmelCase						=		[
		    854, 842, 1_353, 114, 1_353, 842, 185, 842, 185, 114, 591, 842,
		    185, 417, 185, 842, 307, 842, 591, 842, 185, 842, 307, 842,
		    591, 842, 1_353, 842, 185, 842, 591, 842, 591, 114, 591, 842,
		    185, 842, 591, 89
		]

		_lowerCAmelCase						=		[1_058_304, 0, 786_432, 7_169, 507, 76, 27, 40, 30, 76]

		_lowerCAmelCase						=		[
		    390, 1_160, 1_002, 1_907, 1_788, 1_788, 1_788, 1_907, 1_002, 1_002, 1_854, 1_002,
		    1_002, 1_002, 1_002, 1_002, 1_002, 1_160, 1_160, 1_606, 596, 596, 1_160, 1_002,
		    1_516, 596, 1_002, 1_002, 1_002, 1_907, 1_788, 1_788, 1_788, 1_854, 1_788, 1_907,
		    1_907, 1_788, 596, 1_626
		]
		_lowerCAmelCase						=		[
		    1_236, 1_668, 1_484, 1_920, 1_848, 1_409, 139, 864, 1_828, 1_272, 1_599, 824,
		    1_672, 139, 555, 1_484, 824, 1_920, 555, 596, 1_579, 1_599, 1_231, 1_599,
		    1_637, 1_407, 212, 824, 1_599, 116, 1_433, 824, 258, 1_599, 1_433, 1_895,
		    1_063, 1_433, 1_433, 1_599
		]
		_lowerCAmelCase						=		[
		    1_684, 1_873, 1_119, 1_189, 395, 611, 1_901, 972, 890, 1_337, 1_392, 1_927,
		    96, 972, 672, 780, 1_119, 890, 158, 771, 1_073, 1_927, 353, 1_331,
		    1_269, 1_459, 1_333, 1_645, 812, 1_577, 1_337, 606, 353, 981, 1_466, 619,
		    197, 391, 302, 1_930
		]
		_lowerCAmelCase						=		[
		    390, 1_160, 1_002, 1_907, 1_788, 1_788, 1_788, 1_907, 1_002, 1_002, 1_854, 1_002,
		    1_002, 1_002, 1_002, 1_002, 1_002, 1_160, 1_160, 1_606, 596, 596, 1_160, 1_002,
		    1_516, 596, 1_002, 1_002, 1_002, 1_907, 1_788, 1_788, 1_788, 1_854, 1_788, 1_907,
		    1_907, 1_788, 596, 1_626
		]
		_lowerCAmelCase						=		[
		    -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
		]
		_lowerCAmelCase						=		[
		    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
		]
		_lowerCAmelCase						=		[
		    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
		]
		_lowerCAmelCase						=		[
		    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  _A							(							self      :		Dict			):
							lowerCAmelCase						:   int							=       JukeboxTokenizer.from_pretrained(self.model_id			)
							lowerCAmelCase						:   Union[str, Any]							=       tokenizer(**self.metas			)['''input_ids''']
							return tokens





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

							set_seed(0			)
							lowerCAmelCase						:   Optional[int]							=       [torch.zeros(1  ,					0  ,					dtype=torch.long			).cpu() for _ in range(3			)]
							lowerCAmelCase						:   Optional[Any]							=       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			)
							lowerCAmelCase						:   Tuple							=       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			)
							lowerCAmelCase						:   Tuple							=       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  _A							(							self      :		str			):
							lowerCAmelCase						:   str							=       False
							lowerCAmelCase						:   Any							=       JukeboxModel.from_pretrained(self.model_id  ,					min_duration=0			).eval()

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

							lowerCAmelCase						:   Optional[Any]							=       model.priors[0]
							lowerCAmelCase						:   Tuple							=       0
							lowerCAmelCase						:   Tuple							=       top_prior.get_music_tokens_conds(lowerCamelCase__  ,					start=lowerCamelCase__  ,					end=start + top_prior.n_ctx			)
							lowerCAmelCase						:   List[str]							=       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			)

							lowerCAmelCase		,							lowerCAmelCase		,							lowerCAmelCase						:   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  _A							(							self      :		List[str]			):
							lowerCAmelCase						:   Tuple							=       False

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

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

							lowerCAmelCase						:   List[Any]							=       torch.cat((zs[0], torch.zeros(1  ,					2_0_4_8 - zs[0].shape[-1]			))  ,					dim=-1			).long()
							lowerCAmelCase						:   List[str]							=       [upper_a, model.vqvae.encode(lowerCamelCase__  ,					start_level=1  ,					bs_chunks=waveform.shape[0]			)[0], None]
							lowerCAmelCase						:   List[Any]							=       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			)			)

							lowerCAmelCase						:   Any							=       torch.cat((zs[1], torch.zeros(1  ,					2_0_4_8 - zs[1].shape[-1]			))  ,					dim=-1			).long()
							lowerCAmelCase						:   str							=       [upper_a, upper_a, model.vqvae.encode(lowerCamelCase__  ,					start_level=0  ,					bs_chunks=waveform.shape[0]			)[0]]
							lowerCAmelCase						:   List[Any]							=       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  _A							(							self      :		Any			):
							lowerCAmelCase						:   Any							=       JukeboxModel.from_pretrained(self.model_id  ,					min_duration=0			).eval()
							set_seed(0			)
							lowerCAmelCase						:   Tuple							=       torch.rand((1, 5_1_2_0, 1)			)
							with torch.no_grad():
												lowerCAmelCase						:   Tuple							=       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						:   int							=       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 						__magic_name__				(  unittest.TestCase      ):
		_lowerCAmelCase						=		(JukeboxModel,) if is_torch_available() else ()
		_lowerCAmelCase						=		"openai/jukebox-5b-lyrics"
		_lowerCAmelCase						=		{
		    "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
		_lowerCAmelCase						=		[
		    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    1_489, 1_489, 1_489, 1_489, 1_150, 1_853, 1_509, 1_150, 1_357, 1_509, 6, 1_272
		]
		_lowerCAmelCase						=		[
		    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653
		]

		_lowerCAmelCase						=		[
		    1_125, 416, 1_125, 1_125, 1_125, 1_125, 1_125, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416
		]
		_lowerCAmelCase						=		[
		    416, 416, 1_125, 1_125, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416
		]

		_lowerCAmelCase						=		[
		    1_755, 1_061, 234, 1_755, 1_061, 1_755, 185, 290, 307, 307, 616, 616,
		    616, 616, 616, 616, 307, 290, 417, 1_755, 234, 1_755, 185, 290,
		    290, 290, 307, 616, 616, 616, 616, 616, 290, 234, 234, 1_755,
		    234, 234, 1_755, 234, 185, 185, 307, 616, 616, 616, 616, 290,
		    1_755, 1_755, 1_755, 234, 234, 1_755, 1_572, 290, 307, 616, 34, 616
		]
		_lowerCAmelCase						=		[
		    854, 842, 1_353, 114, 1_353, 842, 185, 842, 185, 114, 591, 842, 185,
		    417, 185, 842, 307, 842, 591, 842, 185, 842, 185, 842, 591, 842,
		    1_353, 842, 185, 842, 591, 842, 591, 114, 591, 842, 185, 842, 591,
		    89, 591, 842, 591, 842, 591, 417, 1_372, 842, 1_372, 842, 34, 842,
		    185, 89, 591, 842, 185, 842, 591, 632
		]

		_lowerCAmelCase						=		[
		    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653
		]
		_lowerCAmelCase						=		[
		    1_489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
		    653, 653, 653, 653, 653, 653, 653, 1_853, 1_177, 1_536, 1_228,
		    710, 475, 1_489, 1_229, 1_224, 231, 1_224, 252, 1_434, 653, 475,
		    1_106, 1_877, 1_599, 1_228, 1_600, 1_683, 1_182, 1_853, 475, 1_864,
		    252, 1_229, 1_434, 2_001
		]

		_lowerCAmelCase						=		[
		    1_125, 1_125, 416, 1_125, 1_125, 416, 1_125, 1_125, 416, 416, 1_125, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
		    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416
		]
		_lowerCAmelCase						=		[
		    491, 1_755, 34, 1_613, 1_755, 417, 992, 1_613, 222, 842, 1_353, 1_613,
		    844, 632, 185, 1_613, 844, 632, 185, 1_613, 185, 842, 677, 1_613,
		    185, 114, 1_353, 1_613, 307, 89, 844, 1_613, 307, 1_332, 234, 1_979,
		    307, 89, 1_353, 616, 34, 842, 185, 842, 34, 842, 185, 842,
		    307, 114, 185, 89, 34, 1_268, 185, 89, 34, 842, 185, 89
		]





		def  _A							(							self      :		List[Any]  ,					lowerCamelCase__      :		int			):
							lowerCAmelCase						:   Any							=       JukeboxTokenizer.from_pretrained(lowerCamelCase__			)
							lowerCAmelCase						:   List[Any]							=       tokenizer(**self.metas			)['''input_ids''']
							return tokens





		@slow
		def  _A							(							self      :		int			):
							lowerCAmelCase						:   Any							=       JukeboxModel.from_pretrained(self.model_id  ,					min_duration=0			).eval()
							lowerCAmelCase						:   Dict							=       self.prepare_inputs(self.model_id			)

							set_seed(0			)
							lowerCAmelCase						:   List[str]							=       [torch.zeros(1  ,					0  ,					dtype=torch.long			).cpu() for _ in range(3			)]
							lowerCAmelCase						:   Tuple							=       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			)
							lowerCAmelCase						:   int							=       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			)
							lowerCAmelCase						:   Dict							=       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  _A							(							self      :		str			):
							lowerCAmelCase						:   int							=       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						:   List[str]							=       [torch.zeros(1  ,					0  ,					dtype=torch.long			).cuda() for _ in range(3			)]
							lowerCAmelCase						:   int							=       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()
							lowerCAmelCase						:   int							=       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()
							lowerCAmelCase						:   int							=       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  _A							(							self      :		Tuple			):
							lowerCAmelCase						:   Dict							=       '''ArthurZ/jukebox_prior_0'''
							lowerCAmelCase						:   Tuple							=       JukeboxPrior.from_pretrained(lowerCamelCase__  ,					min_duration=0			).eval().half().to('''cuda'''			)

							lowerCAmelCase						:   List[str]							=       self.prepare_inputs(lowerCamelCase__			)[0].cuda()
							lowerCAmelCase						:   int							=       model.get_metadata(lowerCamelCase__  ,					0  ,					7_6_8_0  ,					0			)
							set_seed(0			)
							lowerCAmelCase						:   str							=       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]			)
