




'''simple docstring'''



import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
     from PIL import Image

     from transformers import AutoProcessor, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast





@require_vision
class     lowerCAmelCase   ( unittest.TestCase):


       def       lowerCAmelCase      (   self  )      ->  Union[str, Any]:



            '''simple docstring'''




            __snake_case    					=  tempfile.mkdtemp()

            __snake_case    					=  CLIPImageProcessor()
            __snake_case    					=  BertTokenizer.from_pretrained(
                '''hf-internal-testing/tiny-random-BertModel'''    ,  model_input_names=['''input_ids''', '''attention_mask''']  )

            __snake_case    					=  GitProcessor(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )

            processor.save_pretrained(self.tmpdirname  )


       def       lowerCAmelCase      (   self    ,  **__SCREAMING_SNAKE_CASE  )      ->  Any:



            '''simple docstring'''




            return AutoProcessor.from_pretrained(self.tmpdirname    ,  **__SCREAMING_SNAKE_CASE  ).tokenizer


       def       lowerCAmelCase      (   self    ,  **__SCREAMING_SNAKE_CASE  )      ->  Tuple:



            '''simple docstring'''




            return AutoProcessor.from_pretrained(self.tmpdirname    ,  **__SCREAMING_SNAKE_CASE  ).image_processor


       def       lowerCAmelCase      (   self  )      ->  str:



            '''simple docstring'''




            shutil.rmtree(self.tmpdirname  )


       def       lowerCAmelCase      (   self  )      ->  int:



            '''simple docstring'''




            __snake_case    					=  [np.random.randint(255    ,  size=(3, 30, 400)    ,  dtype=np.uinta  )]

            __snake_case    					=  [Image.fromarray(np.moveaxis(__SCREAMING_SNAKE_CASE    ,  0    ,  -1  )  ) for x in image_inputs]

            return image_inputs


       def       lowerCAmelCase      (   self  )      ->  Tuple:



            '''simple docstring'''




            __snake_case    					=  GitProcessor(tokenizer=self.get_tokenizer()    ,  image_processor=self.get_image_processor()  )
            processor.save_pretrained(self.tmpdirname  )

            __snake_case    					=  self.get_tokenizer(bos_token='''(BOS)'''    ,  eos_token='''(EOS)'''  )
            __snake_case    					=  self.get_image_processor(do_normalize=__SCREAMING_SNAKE_CASE    ,  padding_value=1.0  )

            __snake_case    					=  GitProcessor.from_pretrained(
                self.tmpdirname    ,  bos_token='''(BOS)'''    ,  eos_token='''(EOS)'''    ,  do_normalize=__SCREAMING_SNAKE_CASE    ,  padding_value=1.0  )

            self.assertEqual(processor.tokenizer.get_vocab()    ,  tokenizer_add_kwargs.get_vocab()  )
            self.assertIsInstance(processor.tokenizer    ,  __SCREAMING_SNAKE_CASE  )

            self.assertEqual(processor.image_processor.to_json_string()    ,  image_processor_add_kwargs.to_json_string()  )
            self.assertIsInstance(processor.image_processor    ,  __SCREAMING_SNAKE_CASE  )


       def       lowerCAmelCase      (   self  )      ->  int:



            '''simple docstring'''




            __snake_case    					=  self.get_image_processor()
            __snake_case    					=  self.get_tokenizer()

            __snake_case    					=  GitProcessor(tokenizer=__SCREAMING_SNAKE_CASE    ,  image_processor=__SCREAMING_SNAKE_CASE  )

            __snake_case    					=  self.prepare_image_inputs()

            __snake_case    					=  image_processor(__SCREAMING_SNAKE_CASE    ,  return_tensors='''np'''  )
            __snake_case    					=  processor(images=__SCREAMING_SNAKE_CASE    ,  return_tensors='''np'''  )

            for key in input_feat_extract.keys():
                 self.assertAlmostEqual(input_feat_extract[key].sum()    ,  input_processor[key].sum()    ,  delta=1E-2  )


       def       lowerCAmelCase      (   self  )      ->  int:



            '''simple docstring'''




            __snake_case    					=  self.get_image_processor()
            __snake_case    					=  self.get_tokenizer()

            __snake_case    					=  GitProcessor(tokenizer=__SCREAMING_SNAKE_CASE    ,  image_processor=__SCREAMING_SNAKE_CASE  )

            __snake_case    					=  '''lower newer'''

            __snake_case    					=  processor(text=__SCREAMING_SNAKE_CASE  )

            __snake_case    					=  tokenizer(__SCREAMING_SNAKE_CASE    ,  return_token_type_ids=__SCREAMING_SNAKE_CASE  )

            for key in encoded_tok.keys():
                 self.assertListEqual(encoded_tok[key]    ,  encoded_processor[key]  )


       def       lowerCAmelCase      (   self  )      ->  Union[str, Any]:



            '''simple docstring'''




            __snake_case    					=  self.get_image_processor()
            __snake_case    					=  self.get_tokenizer()

            __snake_case    					=  GitProcessor(tokenizer=__SCREAMING_SNAKE_CASE    ,  image_processor=__SCREAMING_SNAKE_CASE  )

            __snake_case    					=  '''lower newer'''
            __snake_case    					=  self.prepare_image_inputs()

            __snake_case    					=  processor(text=__SCREAMING_SNAKE_CASE    ,  images=__SCREAMING_SNAKE_CASE  )

            self.assertListEqual(list(inputs.keys()  )    ,  ['''input_ids''', '''attention_mask''', '''pixel_values''']  )

            # test if it raises when no input is passed
            with pytest.raises(__SCREAMING_SNAKE_CASE  ):
                 processor()


       def       lowerCAmelCase      (   self  )      ->  List[str]:



            '''simple docstring'''




            __snake_case    					=  self.get_image_processor()
            __snake_case    					=  self.get_tokenizer()

            __snake_case    					=  GitProcessor(tokenizer=__SCREAMING_SNAKE_CASE    ,  image_processor=__SCREAMING_SNAKE_CASE  )

            __snake_case    					=  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

            __snake_case    					=  processor.batch_decode(__SCREAMING_SNAKE_CASE  )
            __snake_case    					=  tokenizer.batch_decode(__SCREAMING_SNAKE_CASE  )

            self.assertListEqual(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )




       def       lowerCAmelCase      (   self  )      ->  Union[str, Any]:



            '''simple docstring'''




            __snake_case    					=  self.get_image_processor()
            __snake_case    					=  self.get_tokenizer()

            __snake_case    					=  GitProcessor(tokenizer=__SCREAMING_SNAKE_CASE    ,  image_processor=__SCREAMING_SNAKE_CASE  )

            __snake_case    					=  '''lower newer'''
            __snake_case    					=  self.prepare_image_inputs()

            __snake_case    					=  processor(text=__SCREAMING_SNAKE_CASE    ,  images=__SCREAMING_SNAKE_CASE  )

            # For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
            self.assertListEqual(list(inputs.keys()  )    ,  ['''input_ids''', '''attention_mask''', '''pixel_values''']  )












'''simple docstring'''



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):
       __lowercase  :      int        =			(JukeboxModel,) if is_torch_available() else ()
       __lowercase  :      Tuple        =			'''openai/jukebox-1b-lyrics'''
       __lowercase  :      Any        =			{
           '''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
       __lowercase  :      int        =			[
           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
       ]

       __lowercase  :      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
       ]

       __lowercase  :      Union[str, Any]        =			[
           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
       ]
       __lowercase  :      Tuple        =			[
           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
       ]

       __lowercase  :      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
       ]
       __lowercase  :      Optional[int]        =			[
           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
       ]

       __lowercase  :      Dict        =			[105_8304, 0, 78_6432, 7169, 507, 76, 27, 40, 30, 76]

       __lowercase  :      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
       ]
       __lowercase  :      Tuple        =			[
           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
       ]
       __lowercase  :      Union[str, Any]        =			[
           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
       ]
       __lowercase  :      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
       ]
       __lowercase  :      List[Any]        =			[
           -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
       ]
       __lowercase  :      Optional[int]        =			[
           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
       ]
       __lowercase  :      List[Any]        =			[
           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
       ]
       __lowercase  :      Optional[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  )      ->  Union[str, Any]:



            '''simple docstring'''




            __snake_case    					=  JukeboxTokenizer.from_pretrained(self.model_id  )
            __snake_case    					=  tokenizer(**self.metas  )['''input_ids''']
            return tokens


       @slow
       def       lowerCAmelCase      (   self  )      ->  List[str]:



            '''simple docstring'''




            __snake_case    					=  JukeboxModel.from_pretrained(self.model_id    ,  min_duration=0  ).eval()
            __snake_case    					=  self.prepare_inputs()

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

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

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


       @slow
       def       lowerCAmelCase      (   self  )      ->  List[Any]:



            '''simple docstring'''




            __snake_case    					=  False
            __snake_case    					=  JukeboxModel.from_pretrained(self.model_id    ,  min_duration=0  ).eval()

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

            __snake_case    					=  model.priors[0]
            __snake_case    					=  0
            __snake_case    					=  top_prior.get_music_tokens_conds(__SCREAMING_SNAKE_CASE    ,  start=__SCREAMING_SNAKE_CASE    ,  end=start + top_prior.n_ctx  )
            __snake_case    					=  top_prior.get_metadata(labels[0].clone()    ,  __SCREAMING_SNAKE_CASE    ,  105_8304    ,  0  )

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

            __snake_case					,    __snake_case					,    __snake_case    					=  top_prior.get_cond(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )
            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]:



            '''simple docstring'''




            __snake_case    					=  False

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

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

            __snake_case    					=  torch.cat((zs[0], torch.zeros(1    ,  2048 - zs[0].shape[-1]  ))    ,  dim=-1  ).long()
            __snake_case    					=  [upper_a, model.vqvae.encode(__SCREAMING_SNAKE_CASE    ,  start_level=1    ,  bs_chunks=waveform.shape[0]  )[0], None]
            __snake_case    					=  model._sample(
                __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  sample_levels=[1]    ,  save_results=__SCREAMING_SNAKE_CASE    ,  sample_length=40 * model.priors[1].raw_to_tokens  )
            torch.testing.assert_allclose(zs[1][0][:40]    ,  torch.tensor(self.EXPECTED_PRIMED_1  )  )

            __snake_case    					=  torch.cat((zs[1], torch.zeros(1    ,  2048 - zs[1].shape[-1]  ))    ,  dim=-1  ).long()
            __snake_case    					=  [upper_a, upper_a, model.vqvae.encode(__SCREAMING_SNAKE_CASE    ,  start_level=0    ,  bs_chunks=waveform.shape[0]  )[0]]
            __snake_case    					=  model._sample(
                __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  sample_levels=[2]    ,  save_results=__SCREAMING_SNAKE_CASE    ,  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  )      ->  str:



            '''simple docstring'''




            __snake_case    					=  JukeboxModel.from_pretrained(self.model_id    ,  min_duration=0  ).eval()
            set_seed(0  )
            __snake_case    					=  torch.rand((1, 5120, 1)  )
            with torch.no_grad():
                 __snake_case    					=  model.vqvae.encode(__SCREAMING_SNAKE_CASE    ,  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():
                 __snake_case    					=  model.vqvae.decode(__SCREAMING_SNAKE_CASE    ,  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):
       __lowercase  :      Tuple        =			(JukeboxModel,) if is_torch_available() else ()
       __lowercase  :      List[str]        =			'''openai/jukebox-5b-lyrics'''
       __lowercase  :      Any        =			{
           '''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
       __lowercase  :      List[str]        =			[
           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
       ]
       __lowercase  :      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,
           653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653
       ]

       __lowercase  :      Dict        =			[
           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
       ]
       __lowercase  :      Union[str, Any]        =			[
           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
       ]

       __lowercase  :      List[str]        =			[
           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
       ]
       __lowercase  :      Any        =			[
           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
       ]

       __lowercase  :      str        =			[
           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
       ]
       __lowercase  :      List[str]        =			[
           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
       ]

       __lowercase  :      List[str]        =			[
           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
       ]
       __lowercase  :      int        =			[
           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    ,  __SCREAMING_SNAKE_CASE  )      ->  str:



            '''simple docstring'''




            __snake_case    					=  JukeboxTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE  )
            __snake_case    					=  tokenizer(**self.metas  )['''input_ids''']
            return tokens


       @slow
       def       lowerCAmelCase      (   self  )      ->  List[str]:



            '''simple docstring'''




            __snake_case    					=  JukeboxModel.from_pretrained(self.model_id    ,  min_duration=0  ).eval()
            __snake_case    					=  self.prepare_inputs(self.model_id  )

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

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

            set_seed(0  )
            __snake_case    					=  model._sample(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  [2]    ,  sample_length=60 * model.priors[2].raw_to_tokens    ,  save_results=__SCREAMING_SNAKE_CASE  )
            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  )      ->  Any:



            '''simple docstring'''




            __snake_case    					=  JukeboxModel.from_pretrained(self.model_id    ,  min_duration=0  ).eval()
            __snake_case    					=  [i.cuda() for i in self.prepare_inputs(self.model_id  )]

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




       @slow
       def       lowerCAmelCase      (   self  )      ->  int:



            '''simple docstring'''




            __snake_case    					=  '''ArthurZ/jukebox_prior_0'''
            __snake_case    					=  JukeboxPrior.from_pretrained(__SCREAMING_SNAKE_CASE    ,  min_duration=0  ).eval().half().to('''cuda'''  )

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






