
'''simple docstring'''



import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch




class     UpperCAmelCase_	(						unittest.TestCase					):






						'''simple docstring'''






						_lowercase						: List[Any]										=  JukeboxTokenizer
						_lowercase						: int										=  {
						    '''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
        ''',
						}




						@require_torch
						def    _lowercase      (   self ):

												"""simple docstring"""



												import torch

												_lowerCAmelCase    		=					JukeboxTokenizer.from_pretrained("""openai/jukebox-1b-lyrics""" )
												_lowerCAmelCase    		=					tokenizer(**self.metas )["""input_ids"""]
												# fmt: off
												_lowerCAmelCase    		=					[
												    torch.tensor([[
												        0, 0, 0, 7_169, 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, 1_069, 11]] ),
												    torch.tensor([[0, 0, 0, 1_069, 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    _lowercase      (   self ):

												"""simple docstring"""



												import torch

												_lowerCAmelCase    		=					JukeboxTokenizer.from_pretrained("""openai/jukebox-5b-lyrics""" )
												_lowerCAmelCase    		=					tokenizer(**self.metas )["""input_ids"""]
												# fmt: off
												_lowerCAmelCase    		=					[
												    torch.tensor([[
												        0, 0, 0, 1_069, 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, 1_069, 11, -1, -1, -1, -1]] ),
												    torch.tensor([[0, 0, 0, 1_069, 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] ) )







from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments

def      UpperCAmelCase_    (    )	->				Optional[Any]:
     '''simple docstring'''


     A_          =       HfArgumentParser(_UpperCAmelCase				)
     A_          =       parser.parse_args_into_dataclasses()[0]
     A_          =       TensorFlowBenchmark(args=_UpperCAmelCase				)
     try:
          A_          =       parser.parse_args_into_dataclasses()[0]
     except ValueError as e:
          A_          =       '''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
          A_          =       ''' '''.join(str(_UpperCAmelCase				).split(''' '''				)[:-1]				)
          A_          =       ''''''
          A_          =       eval(str(_UpperCAmelCase				).split(''' '''				)[-1]				)
          A_          =       []
          for arg in depreciated_args:
               # arg[2:] removes '--'
               if arg[2:] in TensorFlowBenchmark.deprecated_args:
                    # arg[5:] removes '--no_'
                    full_error_msg += arg_error_msg.format(arg[5:]				)
               else:
                    wrong_args.append(_UpperCAmelCase				)
          if len(_UpperCAmelCase				) > 0:
               A_          =       full_error_msg + begin_error_msg + str(_UpperCAmelCase				)
          raise ValueError(_UpperCAmelCase				)
     benchmark.run()


if __name__ == "__main__":
      main()



