



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

import torch_xla.distributed.xla_multiprocessing as xmp


def       UpperCamelCase(  ):
		lowerCAmelCase_      :					Optional[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=__UpperCamelCase					,default=1					,help='''Number of TPU cores to use (1 or 8).'''			)

		# positional
		parser.add_argument(
		    '''training_script'''					,type=__UpperCamelCase					,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=__UpperCamelCase			)

		return parser.parse_args()


def       UpperCamelCase(  ):
		lowerCAmelCase_      :					List[Any]     =			parse_args()

		# Import training_script as a module.
		lowerCAmelCase_      :					List[Any]     =			Path(args.training_script			)
		sys.path.append(str(script_fpath.parent.resolve()			)			)
		lowerCAmelCase_      :					List[str]     =			script_fpath.stem
		lowerCAmelCase_      :					Optional[int]     =			importlib.import_module(__UpperCamelCase			)

		# Patch sys.argv
		lowerCAmelCase_      :					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()










def       UpperCamelCase(  __UpperCamelCase							:		list			):
		for i, _ in enumerate(__UpperCamelCase			):
				if (i % 2 == 1) == (nums[i - 1] > nums[i]):
						lowerCAmelCase_ ,  lowerCAmelCase_      :					Union[str, Any]     =			nums[i], nums[i - 1]

		return nums


if __name__ == "__main__":
						print('''Enter the array elements:''')
						A__  :  str       = list(map(int, input().split()))
						print('''The unsorted array is:''')
						print(array)
						print('''Array after Wiggle sort:''')
						print(wiggle_sort(array))





