


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class 	UpperCAmelCase_					(					unittest.TestCase    ):

   '''simple docstring'''




   __A :      List[Any]     		=		JukeboxTokenizer
   __A :      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 ):






     """simple docstring"""





     import torch

     lowerCamelCase :					Dict    =				JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics" )
     lowerCamelCase :					Tuple    =				tokenizer(**self.metas )["input_ids"]
     # fmt: off
     lowerCamelCase :					Optional[Any]    =				[
         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 ):






     """simple docstring"""





     import torch

     lowerCamelCase :					List[str]    =				JukeboxTokenizer.from_pretrained("openai/jukebox-5b-lyrics" )
     lowerCamelCase :					Optional[Any]    =				tokenizer(**self.metas )["input_ids"]
     # fmt: off
     lowerCamelCase :					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] ) )







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_snake_case             =     {
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     ['''SqueezeBertTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     [
       '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''SqueezeBertForMaskedLM''',
       '''SqueezeBertForMultipleChoice''',
       '''SqueezeBertForQuestionAnswering''',
       '''SqueezeBertForSequenceClassification''',
       '''SqueezeBertForTokenClassification''',
       '''SqueezeBertModel''',
       '''SqueezeBertModule''',
       '''SqueezeBertPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_squeezebert import (
       SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       SqueezeBertConfig,
       SqueezeBertOnnxConfig,
   )
   from .tokenization_squeezebert import SqueezeBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_squeezebert import (
          SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          SqueezeBertForMaskedLM,
          SqueezeBertForMultipleChoice,
          SqueezeBertForQuestionAnswering,
          SqueezeBertForSequenceClassification,
          SqueezeBertForTokenClassification,
          SqueezeBertModel,
          SqueezeBertModule,
          SqueezeBertPreTrainedModel,
      )

else:
   import sys

   _snake_case             =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



