





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

import torch_xla.distributed.xla_multiprocessing as xmp


def 							SCREAMING_SNAKE_CASE__  (      ):
	snake_case_						:     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=__a				,	default=1				,	help='Number of TPU cores to use (1 or 8).'				)

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

	return parser.parse_args()


def 							SCREAMING_SNAKE_CASE__  (      ):
	snake_case_						:     Dict     =		parse_args()

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

	# Patch sys.argv
	snake_case_						:     Union[str, Any]     =		[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()








from __future__ import annotations

import math


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				):
	snake_case_						:     Optional[int]     =		u
	for i in range(1				,	__a				):
		snake_case_						:     Optional[Any]     =		temp * (u - i)
	return temp


def 							SCREAMING_SNAKE_CASE__  (      ):
	snake_case_						:     Dict     =		int(input('enter the numbers of values: '				)				)
	snake_case_						:     list[list[float]]     =		[]
	for _ in range(__a				):
		y.append([]				)
	for i in range(__a				):
		for j in range(__a				):
			y[i].append(__a				)
			snake_case_						:     str     =		0

	print('enter the values of parameters in a list: '				)
	snake_case_						:     int     =		list(map(__a				,	input().split()				)				)

	print('enter the values of corresponding parameters: '				)
	for i in range(__a				):
		snake_case_						:     Union[str, Any]     =		float(input()				)

	snake_case_						:     int     =		int(input('enter the value to interpolate: '				)				)
	snake_case_						:     List[Any]     =		(value - x[0]) / (x[1] - x[0])

	# for calculating forward difference table

	for i in range(1				,	__a				):
		for j in range(n - i				):
			snake_case_						:     int     =		y[j + 1][i - 1] - y[j][i - 1]

	snake_case_						:     str     =		y[0][0]
	for i in range(1				,	__a				):
		summ += (ucal(__a				,	__a				) * y[0][i]) / math.factorial(__a				)

	print(f"""the value at {value} is {summ}"""				)


if __name__ == "__main__":
						main()

