





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

					UpperCamelCase								=							[
					    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
					]

					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]

					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]

					UpperCamelCase								=							[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]

					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    -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
					]
					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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      lowerCamelCase	( self      :int		):
												A		=  JukeboxTokenizer.from_pretrained(self.model_id		)
												A		=  tokenizer(**self.metas		)["input_ids"]
												return tokens


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

												set_seed(0		)
												A		=  [torch.zeros(1					,	0					,	dtype=torch.long		).cpu() for _ in range(3		)]
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[0]					,	sample_length=40 * model.priors[0].raw_to_tokens					,	save_results=__UpperCamelCase		)
												self.assertIn(zs[0][0].detach().cpu().tolist()					,	[self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]		)

												set_seed(0		)
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[1]					,	sample_length=40 * model.priors[1].raw_to_tokens					,	save_results=__UpperCamelCase		)
												self.assertIn(zs[1][0].detach().cpu().tolist()					,	[self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]		)

												set_seed(0		)
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[2]					,	sample_length=40 * model.priors[2].raw_to_tokens					,	save_results=__UpperCamelCase		)
												self.assertIn(zs[2][0].detach().cpu().tolist()					,	[self.EXPECTED_OUTPUT_0, self.EXPECTED_OUTPUT_0_PT_2]		)


					@slow
					def      lowerCamelCase	( self      :str		):
												A		=  False
												A		=  JukeboxModel.from_pretrained(self.model_id					,	min_duration=0		).eval()

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

												A		=  model.priors[0]
												A		=  0
												A		=  top_prior.get_music_tokens_conds(__UpperCamelCase					,	start=__UpperCamelCase					,	end=start + top_prior.n_ctx		)
												A		=  top_prior.get_metadata(labels[0].clone()					,	__UpperCamelCase					,	1_05_83_04					,	0		)

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

												A,     A,     A		=  top_prior.get_cond(__UpperCamelCase					,	__UpperCamelCase		)
												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      :List[str]		):
												A		=  False

												A		=  JukeboxModel.from_pretrained(self.model_id					,	min_duration=0		).eval()
												set_seed(0		)
												A		=  torch.rand((1, 51_20, 1)		)
												A		=  list(self.prepare_inputs()		)

												A		=  [model.vqvae.encode(__UpperCamelCase					,	start_level=2					,	bs_chunks=waveform.shape[0]		)[0], None, None]
												A		=  model._sample(
												    __UpperCamelCase					,	__UpperCamelCase					,	sample_levels=[0]					,	save_results=__UpperCamelCase					,	sample_length=40 * model.priors[0].raw_to_tokens		)
												torch.testing.assert_allclose(zs[0][0][:40]					,	torch.tensor(self.EXPECTED_PRIMED_0		)		)

												A		=  torch.cat((zs[0], torch.zeros(1					,	20_48 - zs[0].shape[-1]		))					,	dim=-1		).long()
												A		=  [upper_a, model.vqvae.encode(__UpperCamelCase					,	start_level=1					,	bs_chunks=waveform.shape[0]		)[0], None]
												A		=  model._sample(
												    __UpperCamelCase					,	__UpperCamelCase					,	sample_levels=[1]					,	save_results=__UpperCamelCase					,	sample_length=40 * model.priors[1].raw_to_tokens		)
												torch.testing.assert_allclose(zs[1][0][:40]					,	torch.tensor(self.EXPECTED_PRIMED_1		)		)

												A		=  torch.cat((zs[1], torch.zeros(1					,	20_48 - zs[1].shape[-1]		))					,	dim=-1		).long()
												A		=  [upper_a, upper_a, model.vqvae.encode(__UpperCamelCase					,	start_level=0					,	bs_chunks=waveform.shape[0]		)[0]]
												A		=  model._sample(
												    __UpperCamelCase					,	__UpperCamelCase					,	sample_levels=[2]					,	save_results=__UpperCamelCase					,	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      :Dict		):
												A		=  JukeboxModel.from_pretrained(self.model_id					,	min_duration=0		).eval()
												set_seed(0		)
												A		=  torch.rand((1, 51_20, 1)		)
												with torch.no_grad():
																			A		=  model.vqvae.encode(__UpperCamelCase					,	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():
																			A		=  model.vqvae.decode(__UpperCamelCase					,	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  _UpperCAmelCase       (     unittest.TestCase			):
					UpperCamelCase								=							(JukeboxModel,) if is_torch_available() else ()
					UpperCamelCase								=							'''openai/jukebox-5b-lyrics'''
					UpperCamelCase								=							{
					    '''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
					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]

					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]

					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]

					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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
					]

					UpperCamelCase								=							[
					    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
					]
					UpperCamelCase								=							[
					    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      lowerCamelCase	( self      :Optional[Any]					,	__UpperCamelCase      :Union[str, Any]		):
												A		=  JukeboxTokenizer.from_pretrained(__UpperCamelCase		)
												A		=  tokenizer(**self.metas		)["input_ids"]
												return tokens


					@slow
					def      lowerCamelCase	( self      :List[str]		):
												A		=  JukeboxModel.from_pretrained(self.model_id					,	min_duration=0		).eval()
												A		=  self.prepare_inputs(self.model_id		)

												set_seed(0		)
												A		=  [torch.zeros(1					,	0					,	dtype=torch.long		).cpu() for _ in range(3		)]
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[0]					,	sample_length=60 * model.priors[0].raw_to_tokens					,	save_results=__UpperCamelCase		)
												self.assertIn(zs[0][0].detach().cpu().tolist()					,	[self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]		)

												set_seed(0		)
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[1]					,	sample_length=60 * model.priors[1].raw_to_tokens					,	save_results=__UpperCamelCase		)
												self.assertIn(zs[1][0].detach().cpu().tolist()					,	[self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]		)

												set_seed(0		)
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[2]					,	sample_length=60 * model.priors[2].raw_to_tokens					,	save_results=__UpperCamelCase		)
												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      :int		):
												A		=  JukeboxModel.from_pretrained(self.model_id					,	min_duration=0		).eval()
												A		=  [i.cuda() for i in self.prepare_inputs(self.model_id		)]

												set_seed(0		)
												model.priors[0].cuda()
												A		=  [torch.zeros(1					,	0					,	dtype=torch.long		).cuda() for _ in range(3		)]
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[0]					,	sample_length=60 * model.priors[0].raw_to_tokens					,	save_results=__UpperCamelCase		)
												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()
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[1]					,	sample_length=60 * model.priors[1].raw_to_tokens					,	save_results=__UpperCamelCase		)
												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()
												A		=  model._sample(__UpperCamelCase					,	__UpperCamelCase					,	[2]					,	sample_length=60 * model.priors[2].raw_to_tokens					,	save_results=__UpperCamelCase		)
												torch.testing.assert_allclose(zs[2][0].cpu()					,	torch.tensor(self.EXPECTED_GPU_OUTPUTS_0		)		)


					@slow
					def      lowerCamelCase	( self      :Union[str, Any]		):
												A		=  "ArthurZ/jukebox_prior_0"
												A		=  JukeboxPrior.from_pretrained(__UpperCamelCase					,	min_duration=0		).eval().half().to("cuda"		)

												A		=  self.prepare_inputs(__UpperCamelCase		)[0].cuda()
												A		=  model.get_metadata(__UpperCamelCase					,	0					,	76_80					,	0		)
												set_seed(0		)
												A		=  model.sample(1					,	metadata=__UpperCamelCase					,	sample_tokens=60		)
												self.assertIn(outputs[0].cpu().tolist()					,	[self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]		)









"""simple docstring"""
import argparse
import os
import sys
import urllib.request
import zipfile


_snake_case					:		Any							=			['CoLA', 'SST', 'MRPC', 'QQP', 'STS', 'MNLI', 'SNLI', 'QNLI', 'RTE', 'WNLI', 'diagnostic']
_snake_case					:		List[str]							=			{
    'CoLA': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FCoLA.zip?alt=media&token=46d5e637-3411-4188-bc44-5809b5bfb5f4',
    'SST': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8',
    'MRPC': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2Fmrpc_dev_ids.tsv?alt=media&token=ec5c0836-31d5-48f4-b431-7480817f1adc',
    'QQP': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FQQP.zip?alt=media&token=700c6acf-160d-4d89-81d1-de4191d02cb5',
    'STS': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSTS-B.zip?alt=media&token=bddb94a7-8706-4e0d-a694-1109e12273b5',
    'MNLI': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FMNLI.zip?alt=media&token=50329ea1-e339-40e2-809c-10c40afff3ce',
    'SNLI': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSNLI.zip?alt=media&token=4afcfbb2-ff0c-4b2d-a09a-dbf07926f4df',
    'QNLI': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FQNLIv2.zip?alt=media&token=6fdcf570-0fc5-4631-8456-9505272d1601',
    'RTE': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FRTE.zip?alt=media&token=5efa7e85-a0bb-4f19-8ea2-9e1840f077fb',
    'WNLI': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FWNLI.zip?alt=media&token=068ad0a0-ded7-4bd7-99a5-5e00222e0faf',
    'diagnostic': 'https://storage.googleapis.com/mtl-sentence-representations.appspot.com/tsvsWithoutLabels%2FAX.tsv?GoogleAccessId=firebase-adminsdk-0khhl@mtl-sentence-representations.iam.gserviceaccount.com&Expires=2498860800&Signature=DuQ2CSPt2Yfre0C%2BiISrVYrIFaZH1Lc7hBVZDD4ZyR7fZYOMNOUGpi8QxBmTNOrNPjR3z1cggo7WXFfrgECP6FBJSsURv8Ybrue8Ypt%2FTPxbuJ0Xc2FhDi%2BarnecCBFO77RSbfuz%2Bs95hRrYhTnByqu3U%2FYZPaj3tZt5QdfpH2IUROY8LiBXoXS46LE%2FgOQc%2FKN%2BA9SoscRDYsnxHfG0IjXGwHN%2Bf88q6hOmAxeNPx6moDulUF6XMUAaXCSFU%2BnRO2RDL9CapWxj%2BDl7syNyHhB7987hZ80B%2FwFkQ3MEs8auvt5XW1%2Bd4aCU7ytgM69r8JDCwibfhZxpaa4gd50QXQ%3D%3D',
}

_snake_case					:		List[str]							=			'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt'
_snake_case					:		List[str]							=			'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt'






def  A__    (      UpperCamelCase ,  UpperCamelCase	):
							print(F"Downloading and extracting {task}..."	)
							A		=  F"{task}.zip"
							urllib.request.urlretrieve(TASKaPATH[task] ,  UpperCamelCase	)
							with zipfile.ZipFile(UpperCamelCase	) as zip_ref:
														zip_ref.extractall(UpperCamelCase	)
							os.remove(UpperCamelCase	)
							print("\tCompleted!"	)






def  A__    (      UpperCamelCase ,  UpperCamelCase	):
							print("Processing MRPC..."	)
							A		=  os.path.join(UpperCamelCase ,  "MRPC"	)
							if not os.path.isdir(UpperCamelCase	):
														os.mkdir(UpperCamelCase	)
							if path_to_data:
														A		=  os.path.join(UpperCamelCase ,  "msr_paraphrase_train.txt"	)
														A		=  os.path.join(UpperCamelCase ,  "msr_paraphrase_test.txt"	)
							else:
														print("Local MRPC data not specified, downloading data from %s" % MRPC_TRAIN	)
														A		=  os.path.join(UpperCamelCase ,  "msr_paraphrase_train.txt"	)
														A		=  os.path.join(UpperCamelCase ,  "msr_paraphrase_test.txt"	)
														urllib.request.urlretrieve(UpperCamelCase ,  UpperCamelCase	)
														urllib.request.urlretrieve(UpperCamelCase ,  UpperCamelCase	)
							if not os.path.isfile(UpperCamelCase	):
														raise ValueError(F"Train data not found at {mrpc_train_file}"	)
							if not os.path.isfile(UpperCamelCase	):
														raise ValueError(F"Test data not found at {mrpc_test_file}"	)
							urllib.request.urlretrieve(TASKaPATH["MRPC"] ,  os.path.join(UpperCamelCase ,  "dev_ids.tsv"	)	)

							A		=  []
							with open(os.path.join(UpperCamelCase ,  "dev_ids.tsv"	) ,  encoding="utf8"	) as ids_fh:
														for row in ids_fh:
																					dev_ids.append(row.strip().split("\t"	)	)

							with open(UpperCamelCase ,  encoding="utf8"	) as data_fh, open(
							    os.path.join(UpperCamelCase ,  "train.tsv"	) ,  "w" ,  encoding="utf8"	) as train_fh, open(os.path.join(UpperCamelCase ,  "dev.tsv"	) ,  "w" ,  encoding="utf8"	) as dev_fh:
														A		=  data_fh.readline()
														train_fh.write(UpperCamelCase	)
														dev_fh.write(UpperCamelCase	)
														for row in data_fh:
																					A,     A,     A,     A,     A		=  row.strip().split("\t"	)
																					if [ida, ida] in dev_ids:
																												dev_fh.write("%s\t%s\t%s\t%s\t%s\n" % (label, ida, ida, sa, sa)	)
																					else:
																												train_fh.write("%s\t%s\t%s\t%s\t%s\n" % (label, ida, ida, sa, sa)	)

							with open(UpperCamelCase ,  encoding="utf8"	) as data_fh, open(
							    os.path.join(UpperCamelCase ,  "test.tsv"	) ,  "w" ,  encoding="utf8"	) as test_fh:
														A		=  data_fh.readline()
														test_fh.write("index\t#1 ID\t#2 ID\t#1 String\t#2 String\n"	)
														for idx, row in enumerate(UpperCamelCase	):
																					A,     A,     A,     A,     A		=  row.strip().split("\t"	)
																					test_fh.write("%d\t%s\t%s\t%s\t%s\n" % (idx, ida, ida, sa, sa)	)
							print("\tCompleted!"	)






def  A__    (      UpperCamelCase	):
							print("Downloading and extracting diagnostic..."	)
							if not os.path.isdir(os.path.join(UpperCamelCase ,  "diagnostic"	)	):
														os.mkdir(os.path.join(UpperCamelCase ,  "diagnostic"	)	)
							A		=  os.path.join(UpperCamelCase ,  "diagnostic" ,  "diagnostic.tsv"	)
							urllib.request.urlretrieve(TASKaPATH["diagnostic"] ,  UpperCamelCase	)
							print("\tCompleted!"	)
							return






def  A__    (      UpperCamelCase	):
							A		=  task_names.split(","	)
							if "all" in task_names:
														A		=  TASKS
							else:
														A		=  []
														for task_name in task_names:
																					if task_name not in TASKS:
																												raise ValueError(F"Task {task_name} not found!"	)
																					tasks.append(UpperCamelCase	)
							return tasks






def  A__    (      UpperCamelCase	):
							A		=  argparse.ArgumentParser()
							parser.add_argument("--data_dir" ,  help="directory to save data to" ,  type=UpperCamelCase ,  default="glue_data"	)
							parser.add_argument(
							    "--tasks" ,  help="tasks to download data for as a comma separated string" ,  type=UpperCamelCase ,  default="all"	)
							parser.add_argument(
							    "--path_to_mrpc" ,  help="path to directory containing extracted MRPC data, msr_paraphrase_train.txt and msr_paraphrase_text.txt" ,  type=UpperCamelCase ,  default="" ,  )
							A		=  parser.parse_args(UpperCamelCase	)

							if not os.path.isdir(args.data_dir	):
														os.mkdir(args.data_dir	)
							A		=  get_tasks(args.tasks	)

							for task in tasks:
														if task == "MRPC":
																					format_mrpc(args.data_dir ,  args.path_to_mrpc	)
														elif task == "diagnostic":
																					download_diagnostic(args.data_dir	)
														else:
																					download_and_extract(UpperCamelCase ,  args.data_dir	)


if __name__ == "__main__":
		sys.exit(main(sys.argv[1:]))


