"""simple docstring"""







import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp



def     lowercase__( ):
     lowercase_			:       Union[str, Any]									=			ArgumentParser(
         description=(
             'PyTorch TPU distributed training launch '
             'helper utility that will spawn up '
             'multiple distributed processes'
         )   )

     # Optional arguments for the launch helper
     parser.add_argument('--num_cores'  ,    type=__SCREAMING_SNAKE_CASE  ,    default=1  ,    help='Number of TPU cores to use (1 or 8).'   )

     # positional
     parser.add_argument(
         'training_script'  ,    type=__SCREAMING_SNAKE_CASE  ,    help=(
             'The full path to the single TPU training '
             'program/script to be launched in parallel, '
             'followed by all the arguments for the '
             'training script'
         )  ,    )

     # rest from the training program
     parser.add_argument('training_script_args'  ,    nargs=__SCREAMING_SNAKE_CASE   )

     return parser.parse_args()



def     lowercase__( ):
     lowercase_			:       Optional[int]									=			parse_args()

     # Import training_script as a module.
     lowercase_			:       Union[str, Any]									=			Path(args.training_script   )
     sys.path.append(str(script_fpath.parent.resolve()   )   )
     lowercase_			:       Dict									=			script_fpath.stem
     lowercase_			:       List[str]									=			importlib.import_module(__SCREAMING_SNAKE_CASE   )

     # Patch sys.argv
     lowercase_			:       Optional[int]									=			[args.training_script] + args.training_script_args + ['--tpu_num_cores', str(args.num_cores   )]
     xmp.spawn(mod._mp_fn  ,    args=()  ,    nprocs=args.num_cores   )


if __name__ == "__main__":
       main()


"""simple docstring"""







from diffusers.utils.testing_utils import require_onnxruntime







@require_onnxruntime
class  UpperCamelCase	:
   pass

