



import importlib.metadata
from typing import Union

from packaging.version import Version, parse

from .constants import STR_OPERATION_TO_FUNC


__UpperCAmelCase			       =	parse(importlib.metadata.version('''torch'''))
def 		UpperCamelCase     (       snake_case__	:   Union[str, Version]	,					snake_case__	:   str	,					snake_case__	:   str     )     ->					Union[str, Any]:
   if operation not in STR_OPERATION_TO_FUNC.keys():
      raise ValueError(F"""`operation` must be one of {list(STR_OPERATION_TO_FUNC.keys()     )}, received {operation}"""     )
   UpperCamelCase   :  Dict						     =     STR_OPERATION_TO_FUNC[operation]
   if isinstance(__lowerCAmelCase	,					__lowerCAmelCase     ):
      UpperCamelCase   :  Any						     =     parse(importlib.metadata.version(__lowerCAmelCase     )     )
   return operation(__lowerCAmelCase	,					parse(__lowerCAmelCase     )     )


def 		UpperCamelCase     (       snake_case__	:   str	,					snake_case__	:   str     )     ->					str:
   return compare_versions(__lowerCAmelCase	,					__lowerCAmelCase	,					__lowerCAmelCase     )








import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch



class     lowerCAmelCase_		(  unittest.TestCase							):
       UpperCAmelCase__    : Union[str, Any]       					=  JukeboxTokenizer
       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        ",
       }
       @require_torch
       def  snake_case_	(      self	)					->		Optional[Any]:
          import torch

          UpperCamelCase   :  Tuple						     =     JukeboxTokenizer.from_pretrained('openai/jukebox-1b-lyrics'	)
          UpperCamelCase   :  List[str]						     =     tokenizer(**self.metas	)['input_ids']
          # fmt: off
          UpperCamelCase   :  Dict						     =     [
              torch.tensor([[
                  0, 0, 0, 7169, 507, 9, 76, 39, 31, 46, 76, 27,
                  76, 46, 44, 27, 48, 31, 38, 38, 31, 44, 76, 32,
                  44, 41, 39, 76, 27, 40, 76, 27, 40, 46, 35, 43,
                  47, 31, 76, 38, 27, 40, 30, 64, 78, 76, 76, 76,
                  76, 76, 76, 76, 76, 23, 34, 41, 76, 45, 27, 35,
                  30, 76, 71, 20, 49, 41, 76, 48, 27, 45, 46, 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, 76, 76, 76, 76, 76, 76, 76,
                  19, 46, 27, 40, 30, 76, 35, 40, 76, 46, 34, 31,
                  76, 30, 31, 45, 31, 44, 46, 63, 76, 63, 76, 63,
                  76, 63, 76, 14, 31, 27, 44, 76, 46, 34, 31, 39,
                  64, 76, 41, 40, 76, 46, 34, 31, 76, 45, 27, 40,
                  30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76, 8,
                  27, 38, 32, 76, 45, 47, 40, 37, 76, 27, 76, 45,
                  34, 27, 46, 46, 31, 44, 31, 30, 76, 48, 35, 45,
                  27, 33, 31, 76, 38, 35, 31, 45, 64, 76, 49, 34,
                  41, 45, 31, 76, 32, 44, 41, 49, 40, 64, 78, 76,
                  76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76, 49,
                  44, 35, 40, 37, 38, 31, 30, 76, 38, 35, 42, 64,
                  76, 27, 40, 30, 76, 45, 40, 31, 31, 44, 76, 41,
                  32, 76, 29, 41, 38, 30, 76, 29, 41, 39, 39, 27,
                  40, 30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76,
                  20, 31, 38, 38, 76, 46, 34, 27, 46, 76, 35, 46,
                  45, 76, 45, 29, 47, 38, 42, 46, 41, 44, 76, 49,
                  31, 38, 38, 76, 46, 34, 41, 45, 31, 76, 42, 27,
                  45, 45, 35, 41, 40, 45, 76, 44, 31, 27, 30, 78,
                  76, 76, 76, 76, 76, 76, 76, 76, 23, 34, 35, 29,
                  34, 76, 51, 31, 46, 76, 45, 47, 44, 48, 35, 48,
                  31, 64, 76, 45, 46, 27, 39, 42, 31, 30, 76, 41,
                  40, 76, 46, 34, 31, 45, 31, 76, 38, 35, 32, 31,
                  38, 31, 45, 45, 76, 46, 34, 35, 40, 33, 45, 64,
                  78, 76, 76, 76, 76, 76, 76, 76, 76, 20, 34, 31,
                  76, 34, 27, 40, 30, 76, 46, 34, 27, 46, 76, 39,
                  41, 29, 37, 31, 30, 76, 46, 34, 31, 39, 64, 76,
                  27, 40, 30, 76, 46, 34, 31, 76, 34, 31, 27, 44,
                  46, 76, 46, 34, 27, 46, 76, 32, 31, 30, 66, 78,
                  76, 76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76,
                  41, 40, 76, 46, 34, 31, 76, 42, 31, 30, 31, 45,
                  46, 27, 38, 64, 76, 46, 34, 31, 45, 31, 76, 49,
                  41, 44, 30, 45, 76, 27, 42, 42, 31, 27, 44, 65,
                  78, 76, 76, 76, 76, 76, 76, 76, 76, 13, 51, 76,
                  40, 27, 39, 31, 76, 35, 45, 76, 15, 52, 51, 39,
                  27, 40, 30, 35, 27, 45, 64, 76, 11, 35, 40, 33,
                  76, 41, 32, 76, 11, 35, 40, 33, 45, 66, 78, 76,
                  76, 76, 76, 76, 76, 76, 76, 12, 41, 41, 37, 76,
                  41, 40, 76, 39, 51, 76, 23, 41, 44, 37, 45, 64,
                  76, 51, 31, 76, 13, 35, 33, 34, 46, 51, 64, 76,
                  27, 40, 30, 76, 30, 31, 45, 42, 27, 35, 44, 67,
                  78, 76, 76, 76, 76, 76, 76, 76, 76, 14, 41, 46,
                  34, 35, 40, 33, 76, 28, 31, 45, 35, 30, 31, 76,
                  44, 31, 39, 27, 35, 40, 45, 63, 76, 18, 41, 47,
                  40, 30, 76, 46, 34, 31, 76, 30, 31, 29, 27, 51,
                  78, 76, 76, 76, 76, 76, 76, 76, 76, 15, 32, 76,
                  46, 34, 27, 46, 76, 29, 41, 38, 41, 45, 45, 27,
                  38, 76, 23, 44, 31, 29, 37, 64, 76, 28, 41, 47,
                  40, 30, 38, 31, 45, 45, 76, 27, 40, 30, 76, 28,
                  27, 44, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
                  20, 34, 31, 76, 38, 41, 40, 31, 76, 27, 40, 30,
                  76, 38, 31, 48, 31, 38, 76, 45, 27, 40, 30, 45,
                  76, 45, 46, 44, 31, 46, 29, 34, 76, 32, 27, 44,
                  76, 27, 49, 27, 51, 78, 76, 76, 76, 76, 76, 76,
                  76, 76]]	),
              torch.tensor([[0, 0, 0, 1069, 11]]	),
              torch.tensor([[0, 0, 0, 1069, 11]]	),
          ]
          # fmt: on
          self.assertTrue(torch.allclose(tokens[0],      EXPECTED_OUTPUT[0]	)	)
          self.assertTrue(torch.allclose(tokens[1],      EXPECTED_OUTPUT[1]	)	)
          self.assertTrue(torch.allclose(tokens[2],      EXPECTED_OUTPUT[2]	)	)






       @require_torch
       def  snake_case_	(      self	)					->		Optional[Any]:
          import torch

          UpperCamelCase   :  str						     =     JukeboxTokenizer.from_pretrained('openai/jukebox-5b-lyrics'	)
          UpperCamelCase   :  Dict						     =     tokenizer(**self.metas	)['input_ids']
          # fmt: off
          UpperCamelCase   :  Optional[int]						     =     [
              torch.tensor([[
                  0, 0, 0, 1069, 11, -1, -1, -1, -1, 9, 77, 39,
                  31, 46, 77, 27, 77, 46, 44, 27, 48, 31, 38, 38,
                  31, 44, 77, 32, 44, 41, 39, 77, 27, 40, 77, 27,
                  40, 46, 35, 43, 47, 31, 77, 38, 27, 40, 30, 64,
                  79, 77, 77, 77, 77, 77, 77, 77, 77, 23, 34, 41,
                  77, 45, 27, 35, 30, 77, 72, 20, 49, 41, 77, 48,
                  27, 45, 46, 77, 27, 40, 30, 77, 46, 44, 47, 40,
                  37, 38, 31, 45, 45, 77, 38, 31, 33, 45, 77, 41,
                  32, 77, 45, 46, 41, 40, 31, 79, 77, 77, 77, 77,
                  77, 77, 77, 77, 19, 46, 27, 40, 30, 77, 35, 40,
                  77, 46, 34, 31, 77, 30, 31, 45, 31, 44, 46, 63,
                  77, 63, 77, 63, 77, 63, 77, 14, 31, 27, 44, 77,
                  46, 34, 31, 39, 64, 77, 41, 40, 77, 46, 34, 31,
                  77, 45, 27, 40, 30, 64, 79, 77, 77, 77, 77, 77,
                  77, 77, 77, 8, 27, 38, 32, 77, 45, 47, 40, 37,
                  77, 27, 77, 45, 34, 27, 46, 46, 31, 44, 31, 30,
                  77, 48, 35, 45, 27, 33, 31, 77, 38, 35, 31, 45,
                  64, 77, 49, 34, 41, 45, 31, 77, 32, 44, 41, 49,
                  40, 64, 79, 77, 77, 77, 77, 77, 77, 77, 77, 1,
                  40, 30, 77, 49, 44, 35, 40, 37, 38, 31, 30, 77,
                  38, 35, 42, 64, 77, 27, 40, 30, 77, 45, 40, 31,
                  31, 44, 77, 41, 32, 77, 29, 41, 38, 30, 77, 29,
                  41, 39, 39, 27, 40, 30, 64, 79, 77, 77, 77, 77,
                  77, 77, 77, 77, 20, 31, 38, 38, 77, 46, 34, 27,
                  46, 77, 35, 46, 45, 77, 45, 29, 47, 38, 42, 46,
                  41, 44, 77, 49, 31, 38, 38, 77, 46, 34, 41, 45,
                  31, 77, 42, 27, 45, 45, 35, 41, 40, 45, 77, 44,
                  31, 27, 30, 79, 77, 77, 77, 77, 77, 77, 77, 77,
                  23, 34, 35, 29, 34, 77, 51, 31, 46, 77, 45, 47,
                  44, 48, 35, 48, 31, 64, 77, 45, 46, 27, 39, 42,
                  31, 30, 77, 41, 40, 77, 46, 34, 31, 45, 31, 77,
                  38, 35, 32, 31, 38, 31, 45, 45, 77, 46, 34, 35,
                  40, 33, 45, 64, 79, 77, 77, 77, 77, 77, 77, 77,
                  77, 20, 34, 31, 77, 34, 27, 40, 30, 77, 46, 34,
                  27, 46, 77, 39, 41, 29, 37, 31, 30, 77, 46, 34,
                  31, 39, 64, 77, 27, 40, 30, 77, 46, 34, 31, 77,
                  34, 31, 27, 44, 46, 77, 46, 34, 27, 46, 77, 32,
                  31, 30, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77,
                  1, 40, 30, 77, 41, 40, 77, 46, 34, 31, 77, 42,
                  31, 30, 31, 45, 46, 27, 38, 64, 77, 46, 34, 31,
                  45, 31, 77, 49, 41, 44, 30, 45, 77, 27, 42, 42,
                  31, 27, 44, 65, 79, 77, 77, 77, 77, 77, 77, 77,
                  77, 13, 51, 77, 40, 27, 39, 31, 77, 35, 45, 77,
                  15, 52, 51, 39, 27, 40, 30, 35, 27, 45, 64, 77,
                  11, 35, 40, 33, 77, 41, 32, 77, 11, 35, 40, 33,
                  45, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77, 12,
                  41, 41, 37, 77, 41, 40, 77, 39, 51, 77, 23, 41,
                  44, 37, 45, 64, 77, 51, 31, 77, 13, 35, 33, 34,
                  46, 51, 64, 77, 27, 40, 30, 77, 30, 31, 45, 42,
                  27, 35, 44, 67, 79, 77, 77, 77, 77, 77, 77, 77,
                  77, 14, 41, 46, 34, 35, 40, 33, 77, 28, 31, 45,
                  35, 30, 31, 77, 44, 31, 39, 27, 35, 40, 45, 63,
                  77, 18, 41, 47, 40, 30, 77, 46, 34, 31, 77, 30,
                  31, 29, 27, 51, 79, 77, 77, 77, 77, 77, 77, 77,
                  77, 15, 32, 77, 46, 34, 27, 46, 77, 29, 41, 38,
                  41, 45, 45, 27, 38, 77, 23, 44, 31, 29, 37, 64,
                  77, 28, 41, 47, 40, 30, 38, 31, 45, 45, 77, 27,
                  40, 30, 77, 28, 27, 44, 31, 79, 77, 77, 77, 77,
                  77, 77, 77, 77, 20, 34, 31, 77, 38, 41, 40, 31,
                  77, 27, 40, 30, 77, 38, 31, 48, 31, 38, 77, 45,
                  27, 40, 30, 45, 77, 45, 46, 44, 31, 46, 29, 34,
                  77, 32, 27, 44, 77, 27, 49, 27, 51, 79, 77, 77,
                  77, 77, 77, 77, 77, 77]]	),
              torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]	),
              torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]	),
          ]
          # fmt: on
          self.assertTrue(torch.allclose(tokens[0],      EXPECTED_OUTPUT[0]	)	)
          self.assertTrue(torch.allclose(tokens[1],      EXPECTED_OUTPUT[1]	)	)
          self.assertTrue(torch.allclose(tokens[2],      EXPECTED_OUTPUT[2]	)	)



