
__SCREAMING_SNAKE_CASE     :				int             =       float('inf')


class 						__magic_name__				:





		def __init__(							self      :		int  ,					lowerCamelCase__      :		Dict			):
							lowerCAmelCase						:   Tuple							=       [0] * n
							lowerCAmelCase						:   Tuple							=       [0] * n
							lowerCAmelCase						:   Dict							=       [0] * n
							lowerCAmelCase						:   List[str]							=       [[] for _ in range(lowerCamelCase__			)]





		def  _A							(							self      :		Tuple  ,					lowerCamelCase__      :		List[Any]  ,					lowerCamelCase__      :		Any  ,					lowerCamelCase__      :		Tuple  ,					lowerCamelCase__      :		Optional[Any]=0			):
							self.adj[a].append([b, len(self.adj[b]			), c, 0]			)
							self.adj[b].append([a, len(self.adj[a]			) - 1, rcap, 0]			)





		def  _A							(							self      :		Tuple  ,					lowerCamelCase__      :		Dict  ,					lowerCamelCase__      :		List[Any]  ,					lowerCamelCase__      :		List[str]			):
							if vertex == sink or not flow:
												return flow

							for i in range(self.ptr[vertex]  ,					len(self.adj[vertex]			)			):
												lowerCAmelCase						:   Optional[Any]							=       self.adj[vertex][i]
												if self.lvl[e[0]] == self.lvl[vertex] + 1:
																	lowerCAmelCase						:   int							=       self.depth_first_search(e[0]  ,					lowerCamelCase__  ,					min(lowerCamelCase__  ,					e[2] - e[3]			)			)
																	if p:
																						self.adj[vertex][i][3] += p
																						self.adj[e[0]][e[1]][3] -= p
																						return p
												lowerCAmelCase						:   List[Any]							=       self.ptr[vertex] + 1
							return 0





		def  _A							(							self      :		Optional[Any]  ,					lowerCamelCase__      :		List[Any]  ,					lowerCamelCase__      :		List[str]			):
							lowerCAmelCase		,							lowerCAmelCase						:   Dict							=       0, source
							for l in range(3_1			):  # noqa: E741  l = 30 maybe faster for random data
												while True:
																	lowerCAmelCase		,							lowerCAmelCase						:   Optional[int]							=       [0] * len(self.q			), [0] * len(self.q			)
																	lowerCAmelCase		,							lowerCAmelCase		,							lowerCAmelCase						:   Union[str, Any]							=       0, 1, 1
																	while qi < qe and not self.lvl[sink]:
																						lowerCAmelCase						:   Tuple							=       self.q[qi]
																						qi += 1
																						for e in self.adj[v]:
																											if not self.lvl[e[0]] and (e[2] - e[3]) >> (3_0 - l):
																																lowerCAmelCase						:   Dict							=       e[0]
																																qe += 1
																																lowerCAmelCase						:   str							=       self.lvl[v] + 1

																	lowerCAmelCase						:   Union[str, Any]							=       self.depth_first_search(lowerCamelCase__  ,					lowerCamelCase__  ,					lowerCamelCase__			)
																	while p:
																						flow += p
																						lowerCAmelCase						:   Dict							=       self.depth_first_search(lowerCamelCase__  ,					lowerCamelCase__  ,					lowerCamelCase__			)

																	if not self.lvl[sink]:
																						break

							return flow
__SCREAMING_SNAKE_CASE     :				Optional[int]             =       Dinic(10)
__SCREAMING_SNAKE_CASE     :				str             =       0
__SCREAMING_SNAKE_CASE     :				Union[str, Any]             =       9
for vertex in range(1, 5):
		graph.add_edge(source, vertex, 1)
for vertex in range(5, 9):
		graph.add_edge(vertex, sink, 1)
for vertex in range(1, 5):
		graph.add_edge(vertex, vertex + 4, 1)

# Now we can know that is the maximum flow(source -> sink)
print(graph.max_flow(source, sink))


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]			)
