


"""simple docstring"""


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class 						_UpperCamelCase						(     unittest.TestCase	):
							'''simple docstring'''







							__UpperCAmelCase		:					Union[str, Any]          =JukeboxTokenizer
							__UpperCAmelCase		:					Optional[Any]          ={
							    """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     snake_case       (  self			):
										import torch

										__lowerCAmelCase       					=    JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics"			)
										__lowerCAmelCase       					=    tokenizer(**self.metas			)["input_ids"]
										# fmt: off
										__lowerCAmelCase       					=    [
										    torch.tensor([[
										        0, 0, 0, 71_69, 5_07, 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, 10_69, 11]]			),
										    torch.tensor([[0, 0, 0, 10_69, 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			):
										import torch

										__lowerCAmelCase       					=    JukeboxTokenizer.from_pretrained("openai/jukebox-5b-lyrics"			)
										__lowerCAmelCase       					=    tokenizer(**self.metas			)["input_ids"]
										# fmt: off
										__lowerCAmelCase       					=    [
										    torch.tensor([[
										        0, 0, 0, 10_69, 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, 10_69, 11, -1, -1, -1, -1]]			),
										    torch.tensor([[0, 0, 0, 10_69, 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]			)			)








"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A  :     Union[str, Any]    					=    {
    "configuration_x_clip": [
        "XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "XCLIPConfig",
        "XCLIPTextConfig",
        "XCLIPVisionConfig",
    ],
    "processing_x_clip": ["XCLIPProcessor"],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A  :     Optional[int]    					=    [
	    "XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "XCLIPModel",
	    "XCLIPPreTrainedModel",
	    "XCLIPTextModel",
	    "XCLIPVisionModel",
	]

if TYPE_CHECKING:
	from .configuration_x_clip import (
	    XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    XCLIPConfig,
	    XCLIPTextConfig,
	    XCLIPVisionConfig,
	)
	from .processing_x_clip import XCLIPProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_x_clip import (
		    XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    XCLIPModel,
		    XCLIPPreTrainedModel,
		    XCLIPTextModel,
		    XCLIPVisionModel,
		)

else:
	import sys

	A  :     Union[str, Any]    					=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




