import json
import logging
import os
import subprocess
from argparse import ArgumentParser


UpperCamelCase      			=     logging.getLogger(__name__)



def    lowerCamelCase_   (  )							->	Optional[int]:
		__A							:   str	  =				ArgumentParser()
		__A  ,       __A							:   int	  =				parser.parse_known_args()
		for arg in unknown:
				if arg.startswith(("-", "--")    ):
						parser.add_argument(arg.split("="    )[0]    )

		return parser.parse_args()



def    lowerCamelCase_   (  )							->	List[Any]:
		__A							:   int	  =				parse_args()
		__A							:   Tuple	  =				8_888
		__A							:   Dict	  =				int(os.environ["SM_NUM_GPUS"]    )
		__A							:   Union[str, Any]	  =				json.loads(os.environ["SM_HOSTS"]    )
		__A							:   Optional[Any]	  =				len(_lowercase    )
		__A							:   List[Any]	  =				os.environ["SM_CURRENT_HOST"]
		__A							:   List[Any]	  =				hosts.index(_lowercase    )
		__A							:   List[Any]	  =				"INFO"

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


if __name__ == "__main__":
					main()






from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
					from .image_encoder import PaintByExampleImageEncoder
					from .pipeline_paint_by_example import PaintByExamplePipeline





