






import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch


class 					_snake_case						(			unittest.TestCase ):
	_A          =   JukeboxTokenizer
	_A          =   {
	    '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    lowerCAmelCase_							(		self       )						->    str:
					import torch

					snake_case__      :Dict         =   JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics"       )
					snake_case__      :int         =   tokenizer(**self.metas       )["input_ids"]
					# fmt: off
					snake_case__      :List[str]         =   [
					    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    lowerCAmelCase_							(		self       )						->    Dict:
					import torch

					snake_case__      :Tuple         =   JukeboxTokenizer.from_pretrained("openai/jukebox-5b-lyrics"       )
					snake_case__      :Tuple         =   tokenizer(**self.metas       )["input_ids"]
					# fmt: off
					snake_case__      :Optional[int]         =   [
					    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_flax_available,
    is_torch_available,
    is_transformers_available,
)


try:
	if not (is_transformers_available() and is_torch_available()):
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
	from .multicontrolnet import MultiControlNetModel
	from .pipeline_controlnet import StableDiffusionControlNetPipeline
	from .pipeline_controlnet_imgaimg import StableDiffusionControlNetImgaImgPipeline
	from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline


if is_transformers_available() and is_flax_available():
	from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline