
import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch

class   lowerCAmelCase__	(      unittest.TestCase     ):
		a__			:		List[str]     =						JukeboxTokenizer
		a__			:		Optional[int]     =						{
		    '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 					__A			(						self						:				Optional[int]    )	->				Tuple:
						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 					__A			(						self						:				List[Any]    )	->				Any:
						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'''
import argparse
import os

import torch

from transformers import (
    XLNetConfig,
    XLNetForQuestionAnswering,
    XLNetForSequenceClassification,
    XLNetLMHeadModel,
    load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


lowercase__											={
    'cola': 2,
    'mnli': 3,
    'mrpc': 2,
    'sst-2': 2,
    'sts-b': 1,
    'qqp': 2,
    'qnli': 2,
    'rte': 2,
    'wnli': 2,
}


logging.set_verbosity_info()






def      UpperCamelCase_				(      A__  ,      A__  ,      A__  ,      A__=None						):
	# Initialise PyTorch model
	a_      				=						XLNetConfig.from_json_file(A__						)

	a_      				=						finetuning_task.lower() if finetuning_task is not None else """"""
	if finetuning_task in GLUE_TASKS_NUM_LABELS:
		print(F'''Building PyTorch XLNetForSequenceClassification model from configuration: {config}'''						)
		a_      				=						finetuning_task
		a_      				=						GLUE_TASKS_NUM_LABELS[finetuning_task]
		a_      				=						XLNetForSequenceClassification(A__						)
	elif "squad" in finetuning_task:
		a_      				=						finetuning_task
		a_      				=						XLNetForQuestionAnswering(A__						)
	else:
		a_      				=						XLNetLMHeadModel(A__						)

	# Load weights from tf checkpoint
	load_tf_weights_in_xlnet(A__  ,      A__  ,      A__						)

	# Save pytorch-model
	a_      				=						os.path.join(A__  ,      A__						)
	a_      				=						os.path.join(A__  ,      A__						)
	print(F'''Save PyTorch model to {os.path.abspath(A__						)}'''						)
	torch.save(model.state_dict()  ,      A__						)
	print(F'''Save configuration file to {os.path.abspath(A__						)}'''						)
	with open(A__  ,      """w"""  ,      encoding="""utf-8"""						) as f:
		f.write(config.to_json_string()						)


if __name__ == "__main__":
		lowercase__											=argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    '--tf_checkpoint_path', default=None, type=str, required=True, help='Path to the TensorFlow checkpoint path.'
		)
		parser.add_argument(
		    '--xlnet_config_file',
		    default=None,
		    type=str,
		    required=True,
		    help=(
		        'The config json file corresponding to the pre-trained XLNet model. \n'
		        'This specifies the model architecture.'
		    ),
		)
		parser.add_argument(
		    '--pytorch_dump_folder_path',
		    default=None,
		    type=str,
		    required=True,
		    help='Path to the folder to store the PyTorch model or dataset/vocab.',
		)
		parser.add_argument(
		    '--finetuning_task',
		    default=None,
		    type=str,
		    help='Name of a task on which the XLNet TensorFlow model was fine-tuned',
		)
		lowercase__											=parser.parse_args()
		print(args)

		convert_xlnet_checkpoint_to_pytorch(
		    args.tf_checkpoint_path, args.xlnet_config_file, args.pytorch_dump_folder_path, args.finetuning_task
		)
