


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch



class    UpperCAmelCase_	(							unittest.TestCase):
       '''simple docstring'''
       __UpperCamelCase      :     Any							=					JukeboxTokenizer
       __UpperCamelCase      :     Union[str, 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        ",
       }






       @require_torch
       def  _lowercase   (     self						):




              """simple docstring"""




              import torch

              UpperCamelCase    :	int   	=		JukeboxTokenizer.from_pretrained('''openai/jukebox-1b-lyrics'''						)
              UpperCamelCase    :	Union[str, Any]   	=		tokenizer(**self.metas						)['''input_ids''']
              # fmt: off
              UpperCamelCase    :	Dict   	=		[
                  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

              UpperCamelCase    :	Optional[int]   	=		JukeboxTokenizer.from_pretrained('''openai/jukebox-5b-lyrics'''						)
              UpperCamelCase    :	Union[str, Any]   	=		tokenizer(**self.metas						)['''input_ids''']
              # fmt: off
              UpperCamelCase    :	List[Any]   	=		[
                  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 ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
  if not (is_transformers_available() and is_torch_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import ShapEPipeline
else:
  from .camera import create_pan_cameras
  from .pipeline_shap_e import ShapEPipeline
  from .pipeline_shap_e_img2img import ShapEImgaImgPipeline
  from .renderer import (
      BoundingBoxVolume,
      ImportanceRaySampler,
      MLPNeRFModelOutput,
      MLPNeRSTFModel,
      ShapEParamsProjModel,
      ShapERenderer,
      StratifiedRaySampler,
      VoidNeRFModel,
  )

