




from typing import Optional, Union

from ...file_utils import TensorType
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, TruncationStrategy





class        lowerCamelCase__(   __lowerCamelCase):
      UpperCAmelCase__ :      int       						=  'MarkupLMFeatureExtractor'
      UpperCAmelCase__ :      Union[str, Any]       						=  ('MarkupLMTokenizer', 'MarkupLMTokenizerFast')
      UpperCAmelCase__ :      List[str]       						=  True
      def __call__(							self:					str       ,			UpperCamelCase_:					int=None       ,			UpperCamelCase_:					Optional[int]=None       ,			UpperCamelCase_:					List[Any]=None       ,			UpperCamelCase_:					List[Any]=None       ,			UpperCamelCase_:					Union[str, Any]=None       ,			UpperCamelCase_:					bool = True       ,			UpperCamelCase_:					Union[bool, str, PaddingStrategy] = False       ,			UpperCamelCase_:					Union[bool, str, TruncationStrategy] = None       ,			UpperCamelCase_:					Optional[int] = None       ,			UpperCamelCase_:					int = 0       ,			UpperCamelCase_:					Optional[int] = None       ,			UpperCamelCase_:					Optional[bool] = None       ,			UpperCamelCase_:					Optional[bool] = None       ,			UpperCamelCase_:					bool = False       ,			UpperCamelCase_:					bool = False       ,			UpperCamelCase_:					bool = False       ,			UpperCamelCase_:					bool = False       ,			UpperCamelCase_:					bool = True       ,			UpperCamelCase_:					Optional[Union[str, TensorType]] = None       ,			**UpperCamelCase_:					Tuple       ,			):
             # first, create nodes and xpaths
             if self.parse_html:
                    if html_strings is None:
                           raise ValueError("""Make sure to pass HTML strings in case `parse_html` is set to `True`"""  )

                    if nodes is not None or xpaths is not None or node_labels is not None:
                           raise ValueError(
                               """Please don't pass nodes, xpaths nor node labels in case `parse_html` is set to `True`"""  )

                    __lowerCamelCase  =		self.feature_extractor(UpperCamelCase_  )
                    __lowerCamelCase  =		features["""nodes"""]
                    __lowerCamelCase  =		features["""xpaths"""]
             else:
                    if html_strings is not None:
                           raise ValueError("""You have passed HTML strings but `parse_html` is set to `False`."""  )
                    if nodes is None or xpaths is None:
                           raise ValueError("""Make sure to pass nodes and xpaths in case `parse_html` is set to `False`"""  )

        # # second, apply the tokenizer
             if questions is not None and self.parse_html:
                    if isinstance(UpperCamelCase_       ,			UpperCamelCase_  ):
                           __lowerCamelCase  =		[questions]  # add batch dimension (as the feature extractor always adds a batch dimension)

             __lowerCamelCase  =		self.tokenizer(
                 text=questions if questions is not None else nodes       ,			text_pair=nodes if questions is not None else None       ,			xpaths=UpperCamelCase_       ,			node_labels=UpperCamelCase_       ,			add_special_tokens=UpperCamelCase_       ,			padding=UpperCamelCase_       ,			truncation=UpperCamelCase_       ,			max_length=UpperCamelCase_       ,			stride=UpperCamelCase_       ,			pad_to_multiple_of=UpperCamelCase_       ,			return_token_type_ids=UpperCamelCase_       ,			return_attention_mask=UpperCamelCase_       ,			return_overflowing_tokens=UpperCamelCase_       ,			return_special_tokens_mask=UpperCamelCase_       ,			return_offsets_mapping=UpperCamelCase_       ,			return_length=UpperCamelCase_       ,			verbose=UpperCamelCase_       ,			return_tensors=UpperCamelCase_       ,			**UpperCamelCase_       ,			)

             return encoded_inputs
      def      lowerCAmelCase__		(							self:					str       ,			*UpperCamelCase_:					Union[str, Any]       ,			**UpperCamelCase_:					Optional[Any]  ):
             return self.tokenizer.batch_decode(*UpperCamelCase_       ,			**UpperCamelCase_  )
      def      lowerCAmelCase__		(							self:					Optional[Any]       ,			*UpperCamelCase_:					Tuple       ,			**UpperCamelCase_:					int  ):
             return self.tokenizer.decode(*UpperCamelCase_       ,			**UpperCamelCase_  )




      @property
      def      lowerCAmelCase__		(							self:					Union[str, Any]  ):
             __lowerCamelCase  =		self.tokenizer.model_input_names
             return tokenizer_input_names







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        lowerCamelCase__(   unittest.TestCase):
      UpperCAmelCase__ :      Optional[Any]       						=  (JukeboxModel,) if is_torch_available() else ()
      UpperCAmelCase__ :      Union[str, Any]       						=  'openai/jukebox-1b-lyrics'
      UpperCAmelCase__ :      Optional[int]       						=  {
          '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__ :      Dict       						=  [
          1864, 1536, 1213, 1870, 1357, 1536, 519, 880, 1323, 789, 1082, 534,
          1000, 1445, 1105, 1130, 967, 515, 1434, 1620, 534, 1495, 283, 1445,
          333, 1307, 539, 1631, 1528, 375, 1434, 673, 627, 710, 778, 1883,
          1405, 1276, 1455, 1228
      ]

      UpperCAmelCase__ :      List[Any]       						=  [
          1489, 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
      ]

      UpperCAmelCase__ :      str       						=  [
          1125, 1751, 697, 1776, 1141, 1476, 391, 697, 1125, 684, 867, 416,
          844, 1372, 1274, 717, 1274, 844, 1299, 1419, 697, 1370, 317, 1125,
          191, 1440, 1370, 1440, 1370, 282, 1621, 1370, 368, 349, 867, 1872,
          1262, 869, 1728, 747
      ]
      UpperCAmelCase__ :      str       						=  [
          416, 416, 1125, 1125, 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
      ]

      UpperCAmelCase__ :      str       						=  [
          1755, 842, 307, 1843, 1022, 1395, 234, 1554, 806, 739, 1022, 442,
          616, 556, 268, 1499, 933, 457, 1440, 1837, 755, 985, 308, 902,
          293, 1443, 1671, 1141, 1533, 555, 1562, 1061, 287, 417, 1022, 2008,
          1186, 1015, 1777, 268
      ]
      UpperCAmelCase__ :      Tuple       						=  [
          854, 842, 1353, 114, 1353, 842, 185, 842, 185, 114, 591, 842,
          185, 417, 185, 842, 307, 842, 591, 842, 185, 842, 307, 842,
          591, 842, 1353, 842, 185, 842, 591, 842, 591, 114, 591, 842,
          185, 842, 591, 89
      ]

      UpperCAmelCase__ :      List[Any]       						=  [105_8304, 0, 78_6432, 7169, 507, 76, 27, 40, 30, 76]

      UpperCAmelCase__ :      Union[str, Any]       						=  [
          390, 1160, 1002, 1907, 1788, 1788, 1788, 1907, 1002, 1002, 1854, 1002,
          1002, 1002, 1002, 1002, 1002, 1160, 1160, 1606, 596, 596, 1160, 1002,
          1516, 596, 1002, 1002, 1002, 1907, 1788, 1788, 1788, 1854, 1788, 1907,
          1907, 1788, 596, 1626
      ]
      UpperCAmelCase__ :      List[str]       						=  [
          1236, 1668, 1484, 1920, 1848, 1409, 139, 864, 1828, 1272, 1599, 824,
          1672, 139, 555, 1484, 824, 1920, 555, 596, 1579, 1599, 1231, 1599,
          1637, 1407, 212, 824, 1599, 116, 1433, 824, 258, 1599, 1433, 1895,
          1063, 1433, 1433, 1599
      ]
      UpperCAmelCase__ :      str       						=  [
          1684, 1873, 1119, 1189, 395, 611, 1901, 972, 890, 1337, 1392, 1927,
          96, 972, 672, 780, 1119, 890, 158, 771, 1073, 1927, 353, 1331,
          1269, 1459, 1333, 1645, 812, 1577, 1337, 606, 353, 981, 1466, 619,
          197, 391, 302, 1930
      ]
      UpperCAmelCase__ :      Union[str, Any]       						=  [
          390, 1160, 1002, 1907, 1788, 1788, 1788, 1907, 1002, 1002, 1854, 1002,
          1002, 1002, 1002, 1002, 1002, 1160, 1160, 1606, 596, 596, 1160, 1002,
          1516, 596, 1002, 1002, 1002, 1907, 1788, 1788, 1788, 1854, 1788, 1907,
          1907, 1788, 596, 1626
      ]
      UpperCAmelCase__ :      Optional[int]       						=  [
          -0.04_92, -0.05_24, -0.05_65, -0.06_40, -0.06_86, -0.06_84, -0.06_77, -0.06_64,
          -0.06_05, -0.04_90, -0.03_30, -0.01_68, -0.00_83, -0.00_75, -0.00_51, 0.00_25,
          0.01_36, 0.02_61, 0.03_86, 0.04_97, 0.05_80, 0.05_99, 0.05_83, 0.06_14,
          0.07_40, 0.08_89, 0.10_23, 0.11_62, 0.12_11, 0.12_12, 0.12_51, 0.13_36,
          0.15_02, 0.16_86, 0.18_83, 0.21_48, 0.23_63, 0.24_58, 0.25_07, 0.25_31
      ]
      UpperCAmelCase__ :      Union[str, Any]       						=  [
          0.02_56, -0.05_44, 0.16_00, -0.00_32, 0.10_66, 0.08_25, -0.00_13, 0.34_40,
          0.02_10, 0.04_12, -0.17_77, -0.08_92, -0.01_64, 0.02_85, -0.06_13, -0.06_17,
          -0.01_37, -0.02_01, -0.01_75, 0.02_15, -0.06_27, 0.05_20, -0.07_30, 0.09_70,
          -0.01_00, 0.04_42, -0.05_86, 0.02_07, -0.00_15, -0.00_82
      ]
      UpperCAmelCase__ :      str       						=  [
          0.04_15, 0.08_77, 0.00_22, -0.00_55, 0.07_51, 0.03_34, 0.03_24, -0.00_68,
          0.00_11, 0.00_17, -0.06_76, 0.06_55, -0.01_43, 0.03_99, 0.03_03, 0.07_43,
          -0.01_68, -0.03_94, -0.11_13, 0.01_24, 0.04_42, 0.02_67, -0.00_03, -0.15_36,
          -0.01_16, -0.18_37, -0.01_80, -0.10_26, -0.07_77, -0.04_56
      ]
      UpperCAmelCase__ :      int       						=  [
          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  ):
             __lowerCamelCase  =		JukeboxTokenizer.from_pretrained(self.model_id  )
             __lowerCamelCase  =		tokenizer(**self.metas  )["""input_ids"""]
             return tokens
      @slow
      def      lowerCAmelCase__		(							self:					Union[str, Any]  ):
             __lowerCamelCase  =		JukeboxModel.from_pretrained(self.model_id       ,			min_duration=0  ).eval()
             __lowerCamelCase  =		self.prepare_inputs()

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

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

             __lowerCamelCase  =		model.priors[0]
             __lowerCamelCase  =		0
             __lowerCamelCase  =		top_prior.get_music_tokens_conds(UpperCamelCase_       ,			start=UpperCamelCase_       ,			end=start + top_prior.n_ctx  )
             __lowerCamelCase  =		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  )

             __lowerCamelCase,  __lowerCamelCase,  __lowerCamelCase  =		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[Any]  ):
             __lowerCamelCase  =		False

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

             __lowerCamelCase  =		[model.vqvae.encode(UpperCamelCase_       ,			start_level=2       ,			bs_chunks=waveform.shape[0]  )[0], None, None]
             __lowerCamelCase  =		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  )  )

             __lowerCamelCase  =		torch.cat((zs[0], torch.zeros(1       ,			20_48 - zs[0].shape[-1]  ))       ,			dim=-1  ).long()
             __lowerCamelCase  =		[upper_a, model.vqvae.encode(UpperCamelCase_       ,			start_level=1       ,			bs_chunks=waveform.shape[0]  )[0], None]
             __lowerCamelCase  =		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  )  )

             __lowerCamelCase  =		torch.cat((zs[1], torch.zeros(1       ,			20_48 - zs[1].shape[-1]  ))       ,			dim=-1  ).long()
             __lowerCamelCase  =		[upper_a, upper_a, model.vqvae.encode(UpperCamelCase_       ,			start_level=0       ,			bs_chunks=waveform.shape[0]  )[0]]
             __lowerCamelCase  =		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:					List[Any]  ):
             __lowerCamelCase  =		JukeboxModel.from_pretrained(self.model_id       ,			min_duration=0  ).eval()
             set_seed(0  )
             __lowerCamelCase  =		torch.rand((1, 51_20, 1)  )
             with torch.no_grad():
                    __lowerCamelCase  =		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():
                    __lowerCamelCase  =		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        lowerCamelCase__(   unittest.TestCase):
      UpperCAmelCase__ :      List[Any]       						=  (JukeboxModel,) if is_torch_available() else ()
      UpperCAmelCase__ :      Optional[int]       						=  'openai/jukebox-5b-lyrics'
      UpperCAmelCase__ :      Optional[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__ :      Optional[int]       						=  [
          1489, 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,
          1489, 1489, 1489, 1489, 1150, 1853, 1509, 1150, 1357, 1509, 6, 1272
      ]
      UpperCAmelCase__ :      Union[str, Any]       						=  [
          1489, 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
      ]

      UpperCAmelCase__ :      Optional[int]       						=  [
          1125, 416, 1125, 1125, 1125, 1125, 1125, 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
      ]
      UpperCAmelCase__ :      List[str]       						=  [
          416, 416, 1125, 1125, 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
      ]

      UpperCAmelCase__ :      Optional[Any]       						=  [
          1755, 1061, 234, 1755, 1061, 1755, 185, 290, 307, 307, 616, 616,
          616, 616, 616, 616, 307, 290, 417, 1755, 234, 1755, 185, 290,
          290, 290, 307, 616, 616, 616, 616, 616, 290, 234, 234, 1755,
          234, 234, 1755, 234, 185, 185, 307, 616, 616, 616, 616, 290,
          1755, 1755, 1755, 234, 234, 1755, 1572, 290, 307, 616, 34, 616
      ]
      UpperCAmelCase__ :      str       						=  [
          854, 842, 1353, 114, 1353, 842, 185, 842, 185, 114, 591, 842, 185,
          417, 185, 842, 307, 842, 591, 842, 185, 842, 185, 842, 591, 842,
          1353, 842, 185, 842, 591, 842, 591, 114, 591, 842, 185, 842, 591,
          89, 591, 842, 591, 842, 591, 417, 1372, 842, 1372, 842, 34, 842,
          185, 89, 591, 842, 185, 842, 591, 632
      ]

      UpperCAmelCase__ :      List[Any]       						=  [
          1489, 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
      ]
      UpperCAmelCase__ :      Dict       						=  [
          1489, 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, 1853, 1177, 1536, 1228,
          710, 475, 1489, 1229, 1224, 231, 1224, 252, 1434, 653, 475,
          1106, 1877, 1599, 1228, 1600, 1683, 1182, 1853, 475, 1864,
          252, 1229, 1434, 2001
      ]

      UpperCAmelCase__ :      Optional[int]       						=  [
          1125, 1125, 416, 1125, 1125, 416, 1125, 1125, 416, 416, 1125, 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
      ]
      UpperCAmelCase__ :      str       						=  [
          491, 1755, 34, 1613, 1755, 417, 992, 1613, 222, 842, 1353, 1613,
          844, 632, 185, 1613, 844, 632, 185, 1613, 185, 842, 677, 1613,
          185, 114, 1353, 1613, 307, 89, 844, 1613, 307, 1332, 234, 1979,
          307, 89, 1353, 616, 34, 842, 185, 842, 34, 842, 185, 842,
          307, 114, 185, 89, 34, 1268, 185, 89, 34, 842, 185, 89
      ]
      def      lowerCAmelCase__		(							self:					Optional[Any]       ,			UpperCamelCase_:					Optional[int]  ):
             __lowerCamelCase  =		JukeboxTokenizer.from_pretrained(UpperCamelCase_  )
             __lowerCamelCase  =		tokenizer(**self.metas  )["""input_ids"""]
             return tokens
      @slow
      def      lowerCAmelCase__		(							self:					Tuple  ):
             __lowerCamelCase  =		JukeboxModel.from_pretrained(self.model_id       ,			min_duration=0  ).eval()
             __lowerCamelCase  =		self.prepare_inputs(self.model_id  )

             set_seed(0  )
             __lowerCamelCase  =		[torch.zeros(1       ,			0       ,			dtype=torch.long  ).cpu() for _ in range(3  )]
             __lowerCamelCase  =		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  )
             __lowerCamelCase  =		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  )
             __lowerCamelCase  =		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:					List[Any]  ):
             __lowerCamelCase  =		JukeboxModel.from_pretrained(self.model_id       ,			min_duration=0  ).eval()
             __lowerCamelCase  =		[i.cuda() for i in self.prepare_inputs(self.model_id  )]

             set_seed(0  )
             model.priors[0].cuda()
             __lowerCamelCase  =		[torch.zeros(1       ,			0       ,			dtype=torch.long  ).cuda() for _ in range(3  )]
             __lowerCamelCase  =		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()
             __lowerCamelCase  =		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()
             __lowerCamelCase  =		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:					Dict  ):
             __lowerCamelCase  =		"""ArthurZ/jukebox_prior_0"""
             __lowerCamelCase  =		JukeboxPrior.from_pretrained(UpperCamelCase_       ,			min_duration=0  ).eval().half().to("""cuda"""  )

             __lowerCamelCase  =		self.prepare_inputs(UpperCamelCase_  )[0].cuda()
             __lowerCamelCase  =		model.get_metadata(UpperCamelCase_       ,			0       ,			76_80       ,			0  )
             set_seed(0  )
             __lowerCamelCase  =		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]  )

