


'''simple docstring'''


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

import torch_xla.distributed.xla_multiprocessing as xmp






def        __lowerCAmelCase       ():
		_UpperCAmelCase						:				List[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=__lowerCAmelCase					,       default=1					,       help="Number of TPU cores to use (1 or 8)."      )

		# positional
		parser.add_argument(
		    "training_script"					,       type=__lowerCAmelCase					,       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=__lowerCAmelCase      )

		return parser.parse_args()






def        __lowerCAmelCase       ():
		_UpperCAmelCase						:				Dict	    =					parse_args()

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

		# Patch sys.argv
		_UpperCAmelCase						:				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'''


def        __lowerCAmelCase       (__lowerCAmelCase = 50      ):
		_UpperCAmelCase						:				Tuple	    =					[[0] * 3 for _ in range(length + 1      )]

		for row_length in range(length + 1      ):
				for tile_length in range(2					,       5      ):
						for tile_start in range(row_length - tile_length + 1      ):
								different_colour_ways_number[row_length][tile_length - 2] += (
								    different_colour_ways_number[row_length - tile_start - tile_length][
								        tile_length - 2
								    ]
								    + 1
								)

		return sum(different_colour_ways_number[length]      )


if __name__ == "__main__":
						print(F'''{solution() = }''')



