

'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp


def       a__    (  )			-> Dict:


	"""simple docstring"""





	UpperCAmelCase_			:	Dict      =   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       a__    (  )			-> Tuple:


	"""simple docstring"""





	UpperCAmelCase_			:	int      =   parse_args()

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

	# Patch sys.argv
	UpperCAmelCase_			:	List[str]      =   [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 transformers import PretrainedConfig
class  _snake_case						(__SCREAMING_SNAKE_CASE):
			__A   :     Optional[Any]          ="custom"






			def __init__(   self       ,_snake_case=1       ,**_snake_case			):
				UpperCAmelCase_			:	Optional[int]      =   attribute
				super().__init__(**_snake_case			)




class  _snake_case						(__SCREAMING_SNAKE_CASE):
			__A   :     Dict          ="custom"






			def __init__(   self       ,_snake_case=1       ,**_snake_case			):
				UpperCAmelCase_			:	Optional[int]      =   attribute




