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	# Copyright 2020 The HuggingFace Team. All rights reserved.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	"""
	A simple launcher script for TPU training

	Inspired by https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py

	::
	>>> python xla_spawn.py --num_cores=NUM_CORES_YOU_HAVE
	YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other
	arguments of your training script)

	"""


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

	import torch_xla.distributed.xla_multiprocessing as xmp


	def parse_args():
	"""
	Helper function parsing the command line options
	@retval ArgumentParser
	"""
	parser = 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=int, default=1, help="Number of TPU cores to use. 1 or 8 on v3-8. 1 or 4 on v4-8")

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

	return parser.parse_args()


	def main():
	args = parse_args()

	# Import training_script as a module.
	script_fpath = Path(args.training_script)
	sys.path.append(str(script_fpath.parent.resolve()))
	mod_name = script_fpath.stem
	mod = importlib.import_module(mod_name)

	# Patch sys.argv
	sys.argv = [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()