



'''simple docstring'''






import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property



@unittest.skipUnless(os.path.exists(__lowerCAmelCase				)					,					"""Tatoeba directory does not exist."""				)
class 							lowercase       (  unittest.TestCase				):


 """simple docstring"""


 @cached_property
 def _snake_case (							self							)		->   List[Any]:
        _UpperCAmelCase  :						Any			     = tempfile.mkdtemp()
        return TatoebaConverter(save_dir=lowerCAmelCase_							)







 @slow
 def _snake_case (							self							)		->   str:
        self.resolver.convert_models(["""heb-eng"""]							)







 @slow
 def _snake_case (							self							)		->   Optional[Any]:
        _UpperCAmelCase     ,_UpperCAmelCase  :						str			     = self.resolver.write_model_card("""opus-mt-he-en"""  ,dry_run=lowerCAmelCase_							)
        assert mmeta["long_pair"] == "heb-eng"




import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch



class 				a							(			unittest.TestCase       ):







 """simple docstring"""






 lowerCamelCase	:Tuple    			=		JukeboxTokenizer
 lowerCamelCase	:str    			=		{
     '''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      UpperCAmelCase							(					self							)  ->					Tuple:
        import torch

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

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




