






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        a__      (	unittest.TestCase		):
		UpperCAmelCase_							:       Union[str, Any] 					= (JukeboxModel,) if is_torch_available() else ()
		UpperCAmelCase_							:       str 					= 'openai/jukebox-1b-lyrics'
		UpperCAmelCase_							:       Union[str, Any] 					= {
		    '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
		UpperCAmelCase_							:       Any 					= [
		    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
		]

		UpperCAmelCase_							:       List[str] 					= [
		    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
		]

		UpperCAmelCase_							:       int 					= [
		    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
		]
		UpperCAmelCase_							:       Optional[int] 					= [
		    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
		]

		UpperCAmelCase_							:       Optional[Any] 					= [
		    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
		]
		UpperCAmelCase_							:       Tuple 					= [
		    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
		]

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

		UpperCAmelCase_							:       Dict 					= [
		    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
		]
		UpperCAmelCase_							:       Optional[Any] 					= [
		    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
		]
		UpperCAmelCase_							:       List[str] 					= [
		    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
		]
		UpperCAmelCase_							:       Optional[Any] 					= [
		    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
		]
		UpperCAmelCase_							:       Any 					= [
		    -0.0_4_9_2, -0.0_5_2_4, -0.0_5_6_5, -0.0_6_4_0, -0.0_6_8_6, -0.0_6_8_4, -0.0_6_7_7, -0.0_6_6_4,
		    -0.0_6_0_5, -0.0_4_9_0, -0.0_3_3_0, -0.0_1_6_8, -0.0_0_8_3, -0.0_0_7_5, -0.0_0_5_1, 0.0_0_2_5,
		    0.0_1_3_6, 0.0_2_6_1, 0.0_3_8_6, 0.0_4_9_7, 0.0_5_8_0, 0.0_5_9_9, 0.0_5_8_3, 0.0_6_1_4,
		    0.0_7_4_0, 0.0_8_8_9, 0.1_0_2_3, 0.1_1_6_2, 0.1_2_1_1, 0.1_2_1_2, 0.1_2_5_1, 0.1_3_3_6,
		    0.1_5_0_2, 0.1_6_8_6, 0.1_8_8_3, 0.2_1_4_8, 0.2_3_6_3, 0.2_4_5_8, 0.2_5_0_7, 0.2_5_3_1
		]
		UpperCAmelCase_							:       Any 					= [
		    0.0_2_5_6, -0.0_5_4_4, 0.1_6_0_0, -0.0_0_3_2, 0.1_0_6_6, 0.0_8_2_5, -0.0_0_1_3, 0.3_4_4_0,
		    0.0_2_1_0, 0.0_4_1_2, -0.1_7_7_7, -0.0_8_9_2, -0.0_1_6_4, 0.0_2_8_5, -0.0_6_1_3, -0.0_6_1_7,
		    -0.0_1_3_7, -0.0_2_0_1, -0.0_1_7_5, 0.0_2_1_5, -0.0_6_2_7, 0.0_5_2_0, -0.0_7_3_0, 0.0_9_7_0,
		    -0.0_1_0_0, 0.0_4_4_2, -0.0_5_8_6, 0.0_2_0_7, -0.0_0_1_5, -0.0_0_8_2
		]
		UpperCAmelCase_							:       Union[str, Any] 					= [
		    0.0_4_1_5, 0.0_8_7_7, 0.0_0_2_2, -0.0_0_5_5, 0.0_7_5_1, 0.0_3_3_4, 0.0_3_2_4, -0.0_0_6_8,
		    0.0_0_1_1, 0.0_0_1_7, -0.0_6_7_6, 0.0_6_5_5, -0.0_1_4_3, 0.0_3_9_9, 0.0_3_0_3, 0.0_7_4_3,
		    -0.0_1_6_8, -0.0_3_9_4, -0.1_1_1_3, 0.0_1_2_4, 0.0_4_4_2, 0.0_2_6_7, -0.0_0_0_3, -0.1_5_3_6,
		    -0.0_1_1_6, -0.1_8_3_7, -0.0_1_8_0, -0.1_0_2_6, -0.0_7_7_7, -0.0_4_5_6
		]
		UpperCAmelCase_							:       List[Any] 					= [
		    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						)				->				Dict:
				__A    =							JukeboxTokenizer.from_pretrained(self.model_id						)
				__A    =							tokenizer(**self.metas						)["input_ids"]
				return tokens






		@slow
		def 					_lowerCamelCase					(      self						)				->				int:
				__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(lowercase__							, lowercase__							, [0]							, sample_length=40 * model.priors[0].raw_to_tokens							, save_results=lowercase__						)
				self.assertIn(zs[0][0].detach().cpu().tolist()							, [self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]						)

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

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






		@slow
		def 					_lowerCamelCase					(      self						)				->				Tuple:
				__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(lowercase__							, start=lowercase__							, end=start + top_prior.n_ctx						)
				__A    =							top_prior.get_metadata(labels[0].clone()							, lowercase__							, 1058304							, 0						)

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

				__A ,   __A ,   __A    =							top_prior.get_cond(lowercase__							, lowercase__						)
				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						)				->				Union[str, Any]:
				__A    =							False

				__A    =							JukeboxModel.from_pretrained(self.model_id							, min_duration=0						).eval()
				set_seed(0						)
				__A    =							torch.rand((1, 5120, 1)						)
				__A    =							list(self.prepare_inputs()						)

				__A    =							[model.vqvae.encode(lowercase__							, start_level=2							, bs_chunks=waveform.shape[0]						)[0], None, None]
				__A    =							model._sample(
				    lowercase__							, lowercase__							, sample_levels=[0]							, save_results=lowercase__							, 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							, 2048 - zs[0].shape[-1]						))							, dim=-1						).long()
				__A    =							[upper_a, model.vqvae.encode(lowercase__							, start_level=1							, bs_chunks=waveform.shape[0]						)[0], None]
				__A    =							model._sample(
				    lowercase__							, lowercase__							, sample_levels=[1]							, save_results=lowercase__							, 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							, 2048 - zs[1].shape[-1]						))							, dim=-1						).long()
				__A    =							[upper_a, upper_a, model.vqvae.encode(lowercase__							, start_level=0							, bs_chunks=waveform.shape[0]						)[0]]
				__A    =							model._sample(
				    lowercase__							, lowercase__							, sample_levels=[2]							, save_results=lowercase__							, 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						)				->				Any:
				__A    =							JukeboxModel.from_pretrained(self.model_id							, min_duration=0						).eval()
				set_seed(0						)
				__A    =							torch.rand((1, 5120, 1)						)
				with torch.no_grad():
						__A    =							model.vqvae.encode(lowercase__							, 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(lowercase__							, 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        a__      (	unittest.TestCase		):
		UpperCAmelCase_							:       List[Any] 					= (JukeboxModel,) if is_torch_available() else ()
		UpperCAmelCase_							:       List[Any] 					= 'openai/jukebox-5b-lyrics'
		UpperCAmelCase_							:       List[Any] 					= {
		    '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
		UpperCAmelCase_							:       List[Any] 					= [
		    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
		]
		UpperCAmelCase_							:       List[Any] 					= [
		    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
		]

		UpperCAmelCase_							:       Dict 					= [
		    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
		]
		UpperCAmelCase_							:       int 					= [
		    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
		]

		UpperCAmelCase_							:       List[str] 					= [
		    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
		]
		UpperCAmelCase_							:       int 					= [
		    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
		]

		UpperCAmelCase_							:       Optional[int] 					= [
		    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
		]
		UpperCAmelCase_							:       Optional[Any] 					= [
		    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
		]

		UpperCAmelCase_							:       str 					= [
		    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
		]
		UpperCAmelCase_							:       Any 					= [
		    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							, lowercase__						)				->				str:
				__A    =							JukeboxTokenizer.from_pretrained(lowercase__						)
				__A    =							tokenizer(**self.metas						)["input_ids"]
				return tokens






		@slow
		def 					_lowerCamelCase					(      self						)				->				int:
				__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(lowercase__							, lowercase__							, [0]							, sample_length=60 * model.priors[0].raw_to_tokens							, save_results=lowercase__						)
				self.assertIn(zs[0][0].detach().cpu().tolist()							, [self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]						)

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

				set_seed(0						)
				__A    =							model._sample(lowercase__							, lowercase__							, [2]							, sample_length=60 * model.priors[2].raw_to_tokens							, save_results=lowercase__						)
				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						)				->				List[str]:
				__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(lowercase__							, lowercase__							, [0]							, sample_length=60 * model.priors[0].raw_to_tokens							, save_results=lowercase__						)
				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(lowercase__							, lowercase__							, [1]							, sample_length=60 * model.priors[1].raw_to_tokens							, save_results=lowercase__						)
				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(lowercase__							, lowercase__							, [2]							, sample_length=60 * model.priors[2].raw_to_tokens							, save_results=lowercase__						)
				torch.testing.assert_allclose(zs[2][0].cpu()							, torch.tensor(self.EXPECTED_GPU_OUTPUTS_0						)						)






		@slow
		def 					_lowerCamelCase					(      self						)				->				Any:
				__A    =							"ArthurZ/jukebox_prior_0"
				__A    =							JukeboxPrior.from_pretrained(lowercase__							, min_duration=0						).eval().half().to("cuda"						)

				__A    =							self.prepare_inputs(lowercase__						)[0].cuda()
				__A    =							model.get_metadata(lowercase__							, 0							, 7680							, 0						)
				set_seed(0						)
				__A    =							model.sample(1							, metadata=lowercase__							, sample_tokens=60						)
				self.assertIn(outputs[0].cpu().tolist()							, [self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]						)









import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
					from .tokenization_xlm_roberta import XLMRobertaTokenizer
else:
					snake_case_   :	Optional[int]							      =None


snake_case_   :	List[str]							      =logging.get_logger(__name__)

snake_case_   :	Optional[int]							      ={'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case_   :	Union[str, Any]							      ={
    '''vocab_file''': {
        '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model''',
        '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model''',
        '''xlm-roberta-large-finetuned-conll02-dutch''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll02-spanish''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll03-english''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll03-german''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json''',
        '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json''',
        '''xlm-roberta-large-finetuned-conll02-dutch''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json'''
        ),
        '''xlm-roberta-large-finetuned-conll02-spanish''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json'''
        ),
        '''xlm-roberta-large-finetuned-conll03-english''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json'''
        ),
        '''xlm-roberta-large-finetuned-conll03-german''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json'''
        ),
    },
}

snake_case_   :	int							      ={
    '''xlm-roberta-base''': 512,
    '''xlm-roberta-large''': 512,
    '''xlm-roberta-large-finetuned-conll02-dutch''': 512,
    '''xlm-roberta-large-finetuned-conll02-spanish''': 512,
    '''xlm-roberta-large-finetuned-conll03-english''': 512,
    '''xlm-roberta-large-finetuned-conll03-german''': 512,
}





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






		def __init__(      self							, lowercase__=None							, lowercase__=None							, lowercase__="<s>"							, lowercase__="</s>"							, lowercase__="</s>"							, lowercase__="<s>"							, lowercase__="<unk>"							, lowercase__="<pad>"							, lowercase__="<mask>"							, **lowercase__							, )				->				List[str]:
				# Mask token behave like a normal word, i.e. include the space before it
				__A    =							AddedToken(lowercase__							, lstrip=lowercase__							, rstrip=lowercase__						) if isinstance(lowercase__							, lowercase__						) else mask_token

				super().__init__(
				    lowercase__							, tokenizer_file=lowercase__							, bos_token=lowercase__							, eos_token=lowercase__							, sep_token=lowercase__							, cls_token=lowercase__							, unk_token=lowercase__							, pad_token=lowercase__							, mask_token=lowercase__							, **lowercase__							, )

				__A    =							vocab_file
				__A    =							False if not self.vocab_file else True






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				List[int]:

				if token_ids_a is None:
						return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
				__A    =							[self.cls_token_id]
				__A    =							[self.sep_token_id]
				return cls + token_ids_a + sep + sep + token_ids_a + sep






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				List[int]:
				__A    =							[self.sep_token_id]
				__A    =							[self.cls_token_id]

				if token_ids_a is None:
						return len(cls + token_ids_a + sep						) * [0]
				return len(cls + token_ids_a + sep + sep + token_ids_a + sep						) * [0]






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				Tuple[str]:
				if not self.can_save_slow_tokenizer:
						raise ValueError(
						    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
						    "tokenizer."						)

				if not os.path.isdir(lowercase__						):
						logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""						)
						return
				__A    =							os.path.join(
				    lowercase__							, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

				if os.path.abspath(self.vocab_file						) != os.path.abspath(lowercase__						):
						copyfile(self.vocab_file							, lowercase__						)

				return (out_vocab_file,)

