






'''simple docstring'''
import unittest
from unittest import skip

from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow
from transformers.trainer_utils import set_seed


if is_torch_available():
						import torch

						from transformers import JukeboxModel, JukeboxPrior, JukeboxTokenizer


@require_torch
class    _snake_case   (				unittest.TestCase					):

					"""simple docstring"""





					_UpperCamelCase		 =      (JukeboxModel,) if is_torch_available() else ()
					_UpperCamelCase		 =      "openai/jukebox-1b-lyrics"
					_UpperCamelCase		 =      {
					    "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    ",
					}
					# fmt: off
					_UpperCamelCase		 =      [
					    1864, 1536, 1213, 1870, 1357, 1536, 519, 880, 1323, 789, 1082, 534,
					    1000, 1445, 1105, 1130, 967, 515, 1434, 1620, 534, 1495, 283, 1445,
					    333, 1307, 539, 1631, 1528, 375, 1434, 673, 627, 710, 778, 1883,
					    1405, 1276, 1455, 1228
					]

					_UpperCamelCase		 =      [
					    1489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653
					]

					_UpperCamelCase		 =      [
					    1125, 1751, 697, 1776, 1141, 1476, 391, 697, 1125, 684, 867, 416,
					    844, 1372, 1274, 717, 1274, 844, 1299, 1419, 697, 1370, 317, 1125,
					    191, 1440, 1370, 1440, 1370, 282, 1621, 1370, 368, 349, 867, 1872,
					    1262, 869, 1728, 747
					]
					_UpperCamelCase		 =      [
					    416, 416, 1125, 1125, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416
					]

					_UpperCamelCase		 =      [
					    1755, 842, 307, 1843, 1022, 1395, 234, 1554, 806, 739, 1022, 442,
					    616, 556, 268, 1499, 933, 457, 1440, 1837, 755, 985, 308, 902,
					    293, 1443, 1671, 1141, 1533, 555, 1562, 1061, 287, 417, 1022, 2008,
					    1186, 1015, 1777, 268
					]
					_UpperCamelCase		 =      [
					    854, 842, 1353, 114, 1353, 842, 185, 842, 185, 114, 591, 842,
					    185, 417, 185, 842, 307, 842, 591, 842, 185, 842, 307, 842,
					    591, 842, 1353, 842, 185, 842, 591, 842, 591, 114, 591, 842,
					    185, 842, 591, 89
					]

					_UpperCamelCase		 =      [105_8304, 0, 78_6432, 7169, 507, 76, 27, 40, 30, 76]

					_UpperCamelCase		 =      [
					    390, 1160, 1002, 1907, 1788, 1788, 1788, 1907, 1002, 1002, 1854, 1002,
					    1002, 1002, 1002, 1002, 1002, 1160, 1160, 1606, 596, 596, 1160, 1002,
					    1516, 596, 1002, 1002, 1002, 1907, 1788, 1788, 1788, 1854, 1788, 1907,
					    1907, 1788, 596, 1626
					]
					_UpperCamelCase		 =      [
					    1236, 1668, 1484, 1920, 1848, 1409, 139, 864, 1828, 1272, 1599, 824,
					    1672, 139, 555, 1484, 824, 1920, 555, 596, 1579, 1599, 1231, 1599,
					    1637, 1407, 212, 824, 1599, 116, 1433, 824, 258, 1599, 1433, 1895,
					    1063, 1433, 1433, 1599
					]
					_UpperCamelCase		 =      [
					    1684, 1873, 1119, 1189, 395, 611, 1901, 972, 890, 1337, 1392, 1927,
					    96, 972, 672, 780, 1119, 890, 158, 771, 1073, 1927, 353, 1331,
					    1269, 1459, 1333, 1645, 812, 1577, 1337, 606, 353, 981, 1466, 619,
					    197, 391, 302, 1930
					]
					_UpperCamelCase		 =      [
					    390, 1160, 1002, 1907, 1788, 1788, 1788, 1907, 1002, 1002, 1854, 1002,
					    1002, 1002, 1002, 1002, 1002, 1160, 1160, 1606, 596, 596, 1160, 1002,
					    1516, 596, 1002, 1002, 1002, 1907, 1788, 1788, 1788, 1854, 1788, 1907,
					    1907, 1788, 596, 1626
					]
					_UpperCamelCase		 =      [
					    -0.0_492, -0.0_524, -0.0_565, -0.0_640, -0.0_686, -0.0_684, -0.0_677, -0.0_664,
					    -0.0_605, -0.0_490, -0.0_330, -0.0_168, -0.0_083, -0.0_075, -0.0_051, 0.0_025,
					    0.0_136, 0.0_261, 0.0_386, 0.0_497, 0.0_580, 0.0_599, 0.0_583, 0.0_614,
					    0.0_740, 0.0_889, 0.1_023, 0.1_162, 0.1_211, 0.1_212, 0.1_251, 0.1_336,
					    0.1_502, 0.1_686, 0.1_883, 0.2_148, 0.2_363, 0.2_458, 0.2_507, 0.2_531
					]
					_UpperCamelCase		 =      [
					    0.0_256, -0.0_544, 0.1_600, -0.0_032, 0.1_066, 0.0_825, -0.0_013, 0.3_440,
					    0.0_210, 0.0_412, -0.1_777, -0.0_892, -0.0_164, 0.0_285, -0.0_613, -0.0_617,
					    -0.0_137, -0.0_201, -0.0_175, 0.0_215, -0.0_627, 0.0_520, -0.0_730, 0.0_970,
					    -0.0_100, 0.0_442, -0.0_586, 0.0_207, -0.0_015, -0.0_082
					]
					_UpperCamelCase		 =      [
					    0.0_415, 0.0_877, 0.0_022, -0.0_055, 0.0_751, 0.0_334, 0.0_324, -0.0_068,
					    0.0_011, 0.0_017, -0.0_676, 0.0_655, -0.0_143, 0.0_399, 0.0_303, 0.0_743,
					    -0.0_168, -0.0_394, -0.1_113, 0.0_124, 0.0_442, 0.0_267, -0.0_003, -0.1_536,
					    -0.0_116, -0.1_837, -0.0_180, -0.1_026, -0.0_777, -0.0_456
					]
					_UpperCamelCase		 =      [
					    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
					]




					def  __SCREAMING_SNAKE_CASE (     self     )      ->	int:
										a_									=   JukeboxTokenizer.from_pretrained(self.model_id     )
										a_									=   tokenizer(**self.metas     )['''input_ids''']
										return tokens




					@slow
					def  __SCREAMING_SNAKE_CASE (     self     )      ->	Optional[Any]:
										a_									=   JukeboxModel.from_pretrained(self.model_id   , min_duration=0     ).eval()
										a_									=   self.prepare_inputs()

										set_seed(0     )
										a_									=   [torch.zeros(1   , 0   , dtype=torch.long     ).cpu() for _ in range(3     )]
										a_									=   model._sample(lowercase_   , lowercase_   , [0]   , sample_length=40 * model.priors[0].raw_to_tokens   , save_results=lowercase_     )
										self.assertIn(zs[0][0].detach().cpu().tolist()   , [self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]     )

										set_seed(0     )
										a_									=   model._sample(lowercase_   , lowercase_   , [1]   , sample_length=40 * model.priors[1].raw_to_tokens   , save_results=lowercase_     )
										self.assertIn(zs[1][0].detach().cpu().tolist()   , [self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]     )

										set_seed(0     )
										a_									=   model._sample(lowercase_   , lowercase_   , [2]   , sample_length=40 * model.priors[2].raw_to_tokens   , save_results=lowercase_     )
										self.assertIn(zs[2][0].detach().cpu().tolist()   , [self.EXPECTED_OUTPUT_0, self.EXPECTED_OUTPUT_0_PT_2]     )




					@slow
					def  __SCREAMING_SNAKE_CASE (     self     )      ->	str:
										a_									=   False
										a_									=   JukeboxModel.from_pretrained(self.model_id   , min_duration=0     ).eval()

										a_									=   self.prepare_inputs()
										set_seed(0     )
										a_									=   [torch.zeros(1   , 0   , dtype=torch.long     ) for _ in range(3     )]

										a_									=   model.priors[0]
										a_									=   0
										a_									=   top_prior.get_music_tokens_conds(lowercase_   , start=lowercase_   , end=start + top_prior.n_ctx     )
										a_									=   top_prior.get_metadata(labels[0].clone()   , lowercase_   , 105_8304   , 0     )

										self.assertIsNone(lowercase_     )
										self.assertListEqual(metadata.numpy()[0][:10].tolist()   , self.EXPECTED_Y_COND     )

										a_									=   top_prior.get_cond(lowercase_   , lowercase_     )
										torch.testing.assert_allclose(
										    audio_conditioning[0][0][:30].detach()   , torch.tensor(self.EXPECTED_AUDIO_COND     )   , atol=1e-4   , rtol=1e-4     )
										torch.testing.assert_allclose(
										    metadata_conditioning[0][0][:30].detach()   , torch.tensor(self.EXPECTED_META_COND     )   , atol=1e-4   , rtol=1e-4     )
										torch.testing.assert_allclose(
										    lyric_tokens[0, :30].detach()   , torch.tensor(self.EXPECTED_LYRIC_COND     )   , atol=1e-4   , rtol=1e-4     )




					@slow
					def  __SCREAMING_SNAKE_CASE (     self     )      ->	Optional[int]:
										a_									=   False

										a_									=   JukeboxModel.from_pretrained(self.model_id   , min_duration=0     ).eval()
										set_seed(0     )
										a_									=   torch.rand((1, 5120, 1)     )
										a_									=   list(self.prepare_inputs()     )

										a_									=   [model.vqvae.encode(lowercase_   , start_level=2   , bs_chunks=waveform.shape[0]     )[0], None, None]
										a_									=   model._sample(
										    lowercase_   , lowercase_   , sample_levels=[0]   , save_results=lowercase_   , sample_length=40 * model.priors[0].raw_to_tokens     )
										torch.testing.assert_allclose(zs[0][0][:40]   , torch.tensor(self.EXPECTED_PRIMED_0     )     )

										a_									=   torch.cat((zs[0], torch.zeros(1   , 2048 - zs[0].shape[-1]     ))   , dim=-1     ).long()
										a_									=   [upper_a, model.vqvae.encode(lowercase_   , start_level=1   , bs_chunks=waveform.shape[0]     )[0], None]
										a_									=   model._sample(
										    lowercase_   , lowercase_   , sample_levels=[1]   , save_results=lowercase_   , sample_length=40 * model.priors[1].raw_to_tokens     )
										torch.testing.assert_allclose(zs[1][0][:40]   , torch.tensor(self.EXPECTED_PRIMED_1     )     )

										a_									=   torch.cat((zs[1], torch.zeros(1   , 2048 - zs[1].shape[-1]     ))   , dim=-1     ).long()
										a_									=   [upper_a, upper_a, model.vqvae.encode(lowercase_   , start_level=0   , bs_chunks=waveform.shape[0]     )[0]]
										a_									=   model._sample(
										    lowercase_   , lowercase_   , sample_levels=[2]   , save_results=lowercase_   , sample_length=40 * model.priors[2].raw_to_tokens     )
										torch.testing.assert_allclose(zs[2][0][:40].cpu()   , torch.tensor(self.EXPECTED_PRIMED_2     )     )




					@slow
					def  __SCREAMING_SNAKE_CASE (     self     )      ->	Union[str, Any]:
										a_									=   JukeboxModel.from_pretrained(self.model_id   , min_duration=0     ).eval()
										set_seed(0     )
										a_									=   torch.rand((1, 5120, 1)     )
										with torch.no_grad():
															a_									=   model.vqvae.encode(lowercase_   , start_level=2   , bs_chunks=x.shape[0]     )
										torch.testing.assert_allclose(zs[0][0]   , torch.tensor(self.EXPECTED_VQVAE_ENCODE     )     )

										with torch.no_grad():
															a_									=   model.vqvae.decode(lowercase_   , start_level=2   , bs_chunks=x.shape[0]     )
										torch.testing.assert_allclose(x[0, :40, 0]   , torch.tensor(self.EXPECTED_VQVAE_DECODE     )   , atol=1e-4   , rtol=1e-4     )



@require_torch
class    _snake_case   (				unittest.TestCase					):

					"""simple docstring"""





					_UpperCamelCase		 =      (JukeboxModel,) if is_torch_available() else ()
					_UpperCamelCase		 =      "openai/jukebox-5b-lyrics"
					_UpperCamelCase		 =      {
					    "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    ",
					}

					# fmt: off
					_UpperCamelCase		 =      [
					    1489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    1489, 1489, 1489, 1489, 1150, 1853, 1509, 1150, 1357, 1509, 6, 1272
					]
					_UpperCamelCase		 =      [
					    1489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653
					]

					_UpperCamelCase		 =      [
					    1125, 416, 1125, 1125, 1125, 1125, 1125, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416
					]
					_UpperCamelCase		 =      [
					    416, 416, 1125, 1125, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416
					]

					_UpperCamelCase		 =      [
					    1755, 1061, 234, 1755, 1061, 1755, 185, 290, 307, 307, 616, 616,
					    616, 616, 616, 616, 307, 290, 417, 1755, 234, 1755, 185, 290,
					    290, 290, 307, 616, 616, 616, 616, 616, 290, 234, 234, 1755,
					    234, 234, 1755, 234, 185, 185, 307, 616, 616, 616, 616, 290,
					    1755, 1755, 1755, 234, 234, 1755, 1572, 290, 307, 616, 34, 616
					]
					_UpperCamelCase		 =      [
					    854, 842, 1353, 114, 1353, 842, 185, 842, 185, 114, 591, 842, 185,
					    417, 185, 842, 307, 842, 591, 842, 185, 842, 185, 842, 591, 842,
					    1353, 842, 185, 842, 591, 842, 591, 114, 591, 842, 185, 842, 591,
					    89, 591, 842, 591, 842, 591, 417, 1372, 842, 1372, 842, 34, 842,
					    185, 89, 591, 842, 185, 842, 591, 632
					]

					_UpperCamelCase		 =      [
					    1489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653
					]
					_UpperCamelCase		 =      [
					    1489, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653, 653,
					    653, 653, 653, 653, 653, 653, 653, 1853, 1177, 1536, 1228,
					    710, 475, 1489, 1229, 1224, 231, 1224, 252, 1434, 653, 475,
					    1106, 1877, 1599, 1228, 1600, 1683, 1182, 1853, 475, 1864,
					    252, 1229, 1434, 2001
					]

					_UpperCamelCase		 =      [
					    1125, 1125, 416, 1125, 1125, 416, 1125, 1125, 416, 416, 1125, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416,
					    416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416, 416
					]
					_UpperCamelCase		 =      [
					    491, 1755, 34, 1613, 1755, 417, 992, 1613, 222, 842, 1353, 1613,
					    844, 632, 185, 1613, 844, 632, 185, 1613, 185, 842, 677, 1613,
					    185, 114, 1353, 1613, 307, 89, 844, 1613, 307, 1332, 234, 1979,
					    307, 89, 1353, 616, 34, 842, 185, 842, 34, 842, 185, 842,
					    307, 114, 185, 89, 34, 1268, 185, 89, 34, 842, 185, 89
					]




					def  __SCREAMING_SNAKE_CASE (     self   , UpperCAmelCase__     )      ->	Optional[Any]:
										a_									=   JukeboxTokenizer.from_pretrained(lowercase_     )
										a_									=   tokenizer(**self.metas     )['''input_ids''']
										return tokens




					@slow
					def  __SCREAMING_SNAKE_CASE (     self     )      ->	Tuple:
										a_									=   JukeboxModel.from_pretrained(self.model_id   , min_duration=0     ).eval()
										a_									=   self.prepare_inputs(self.model_id     )

										set_seed(0     )
										a_									=   [torch.zeros(1   , 0   , dtype=torch.long     ).cpu() for _ in range(3     )]
										a_									=   model._sample(lowercase_   , lowercase_   , [0]   , sample_length=60 * model.priors[0].raw_to_tokens   , save_results=lowercase_     )
										self.assertIn(zs[0][0].detach().cpu().tolist()   , [self.EXPECTED_OUTPUT_2, self.EXPECTED_OUTPUT_2_PT_2]     )

										set_seed(0     )
										a_									=   model._sample(lowercase_   , lowercase_   , [1]   , sample_length=60 * model.priors[1].raw_to_tokens   , save_results=lowercase_     )
										self.assertIn(zs[1][0].detach().cpu().tolist()   , [self.EXPECTED_OUTPUT_1, self.EXPECTED_OUTPUT_1_PT_2]     )

										set_seed(0     )
										a_									=   model._sample(lowercase_   , lowercase_   , [2]   , sample_length=60 * model.priors[2].raw_to_tokens   , save_results=lowercase_     )
										self.assertIn(zs[2][0].detach().cpu().tolist()   , [self.EXPECTED_OUTPUT_0, self.EXPECTED_OUTPUT_0_PT_2]     )




					@slow
					@skip('Not enough GPU memory on CI runners'     )
					def  __SCREAMING_SNAKE_CASE (     self     )      ->	List[Any]:
										a_									=   JukeboxModel.from_pretrained(self.model_id   , min_duration=0     ).eval()
										a_									=   [i.cuda() for i in self.prepare_inputs(self.model_id     )]

										set_seed(0     )
										model.priors[0].cuda()
										a_									=   [torch.zeros(1   , 0   , dtype=torch.long     ).cuda() for _ in range(3     )]
										a_									=   model._sample(lowercase_   , lowercase_   , [0]   , sample_length=60 * model.priors[0].raw_to_tokens   , save_results=lowercase_     )
										torch.testing.assert_allclose(zs[0][0].cpu()   , torch.tensor(self.EXPECTED_GPU_OUTPUTS_2     )     )
										model.priors[0].cpu()

										set_seed(0     )
										model.priors[1].cuda()
										a_									=   model._sample(lowercase_   , lowercase_   , [1]   , sample_length=60 * model.priors[1].raw_to_tokens   , save_results=lowercase_     )
										torch.testing.assert_allclose(zs[1][0].cpu()   , torch.tensor(self.EXPECTED_GPU_OUTPUTS_1     )     )
										model.priors[1].cpu()

										set_seed(0     )
										model.priors[2].cuda()
										a_									=   model._sample(lowercase_   , lowercase_   , [2]   , sample_length=60 * model.priors[2].raw_to_tokens   , save_results=lowercase_     )
										torch.testing.assert_allclose(zs[2][0].cpu()   , torch.tensor(self.EXPECTED_GPU_OUTPUTS_0     )     )




					@slow
					def  __SCREAMING_SNAKE_CASE (     self     )      ->	List[Any]:
										a_									=   '''ArthurZ/jukebox_prior_0'''
										a_									=   JukeboxPrior.from_pretrained(lowercase_   , min_duration=0     ).eval().half().to('cuda'     )

										a_									=   self.prepare_inputs(lowercase_     )[0].cuda()
										a_									=   model.get_metadata(lowercase_   , 0   , 7680   , 0     )
										set_seed(0     )
										a_									=   model.sample(1   , metadata=lowercase_   , sample_tokens=60     )
										self.assertIn(outputs[0].cpu().tolist()   , [self.EXPECTED_GPU_OUTPUTS_2, self.EXPECTED_GPU_OUTPUTS_2_PT_2]     )









'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__lowerCAmelCase							={"configuration_regnet": ["REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "RegNetConfig"]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase							=[
						    "REGNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "RegNetForImageClassification",
						    "RegNetModel",
						    "RegNetPreTrainedModel",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase							=[
						    "TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "TFRegNetForImageClassification",
						    "TFRegNetModel",
						    "TFRegNetPreTrainedModel",
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase							=[
						    "FlaxRegNetForImageClassification",
						    "FlaxRegNetModel",
						    "FlaxRegNetPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_regnet import (
												    REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RegNetForImageClassification,
												    RegNetModel,
												    RegNetPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_regnet import (
												    TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFRegNetForImageClassification,
												    TFRegNetModel,
												    TFRegNetPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_regnet import (
												    FlaxRegNetForImageClassification,
												    FlaxRegNetModel,
												    FlaxRegNetPreTrainedModel,
												)


else:
						import sys

						__lowerCAmelCase							=_LazyModule(__name__, globals()["__file__"], _import_structure)

