






"""simple docstring"""
import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class _lowerCAmelCase	(						__UpperCAmelCase      ,     unittest.TestCase					):
						SCREAMING_SNAKE_CASE_:				Optional[Any]   				=							MPNetTokenizer
						SCREAMING_SNAKE_CASE_:				Optional[int]   				=							MPNetTokenizerFast
						SCREAMING_SNAKE_CASE_:				str   				=							True
						SCREAMING_SNAKE_CASE_:				Any   				=							True







						def  A			(						self       )		->       Optional[Any]:
										super().setUp()

										_SCREAMING_SNAKE_CASE      :		Optional[int]							=						[
										    '[UNK]',
										    '[CLS]',
										    '[SEP]',
										    '[PAD]',
										    '[MASK]',
										    'want',
										    '##want',
										    '##ed',
										    'wa',
										    'un',
										    'runn',
										    '##ing',
										    ',',
										    'low',
										    'lowest',
										]
										_SCREAMING_SNAKE_CASE      :		List[Any]							=						os.path.join(self.tmpdirname      ,							VOCAB_FILES_NAMES['vocab_file']       )
										with open(self.vocab_file      ,							'w'      ,							encoding='utf-8'       ) as vocab_writer:
														vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]       )       )







						def  A			(						self      ,							lowerCAmelCase_       )		->       str:
										_SCREAMING_SNAKE_CASE      :		List[str]							=						'UNwant\u00E9d,running'
										_SCREAMING_SNAKE_CASE      :		Any							=						'unwanted, running'
										return input_text, output_text







						def  A			(						self       )		->       List[str]:
										_SCREAMING_SNAKE_CASE      :		List[str]							=						self.tokenizer_class(self.vocab_file       )

										_SCREAMING_SNAKE_CASE      :		List[Any]							=						tokenizer.tokenize('UNwant\u00E9d,running'       )
										self.assertListEqual(lowerCAmelCase_      ,							['un', '##want', '##ed', ',', 'runn', '##ing']       )
										self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_       )      ,							[9, 6, 7, 1_2, 1_0, 1_1]       )







						@slow
						def  A			(						self       )		->       Optional[int]:
										_SCREAMING_SNAKE_CASE      :		Any							=						self.tokenizer_class.from_pretrained('microsoft/mpnet-base'       )

										_SCREAMING_SNAKE_CASE      :		str							=						tokenizer.encode('sequence builders'      ,							add_special_tokens=lowerCAmelCase_       )
										_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						tokenizer.encode('multi-sequence build'      ,							add_special_tokens=lowerCAmelCase_       )

										_SCREAMING_SNAKE_CASE      :		Tuple							=						tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_       )
										_SCREAMING_SNAKE_CASE      :		Dict							=						tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_      ,							lowerCAmelCase_       )

										assert encoded_sentence == [0] + text + [2]
										assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]









"""simple docstring"""
import json
import logging
import os
import subprocess
from argparse import ArgumentParser


lowerCAmelCase__							= logging.getLogger(__name__)





def 							lowercase__		(				):
				_SCREAMING_SNAKE_CASE      :		Tuple							=						ArgumentParser()
				_SCREAMING_SNAKE_CASE		,	_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						parser.parse_known_args()
				for arg in unknown:
								if arg.startswith(('-', '--')					):
												parser.add_argument(arg.split('='					)[0]					)

				return parser.parse_args()





def 							lowercase__		(				):
				_SCREAMING_SNAKE_CASE      :		Tuple							=						parse_args()
				_SCREAMING_SNAKE_CASE      :		List[Any]							=						8_888
				_SCREAMING_SNAKE_CASE      :		Optional[int]							=						int(os.environ['SM_NUM_GPUS']					)
				_SCREAMING_SNAKE_CASE      :		Any							=						json.loads(os.environ['SM_HOSTS']					)
				_SCREAMING_SNAKE_CASE      :		List[str]							=						len(lowerCamelCase					)
				_SCREAMING_SNAKE_CASE      :		Dict							=						os.environ['SM_CURRENT_HOST']
				_SCREAMING_SNAKE_CASE      :		List[str]							=						hosts.index(lowerCamelCase					)
				_SCREAMING_SNAKE_CASE      :		Optional[int]							=						'INFO'

				if num_nodes > 1:
								_SCREAMING_SNAKE_CASE      :		Dict							=						f"""python -m torch.distributed.launch \
                --nnodes={num_nodes}  \
                --node_rank={rank}  \
                --nproc_per_node={num_gpus}  \
                --master_addr={hosts[0]}  \
                --master_port={port} \
                ./run_glue.py \
                {"".join(["nested fstring" for parameter,value in args.__dict__.items()]					)}"""
				else:
								_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						f"""python -m torch.distributed.launch \
            --nproc_per_node={num_gpus}  \
            ./run_glue.py \
            {"".join(["nested fstring" for parameter,value in args.__dict__.items()]					)}"""
				try:
								subprocess.run(lowerCamelCase,	shell=lowerCamelCase					)
				except Exception as e:
								logger.info(lowerCamelCase					)


if __name__ == "__main__":
			main()

