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https://github.com/huggingface/transformers.git
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ebf80e2e70
* wip * wip * a last wip * Better logging when using TPUs * Correct argument name * Tests * fix * Metrics in evaluation * Update src/transformers/training_args.py * [tpu] Use launcher script instead * [tpu] lots of tweaks * Fix formatting Co-authored-by: Julien Chaumond <chaumond@gmail.com>
75 lines
1.9 KiB
Python
75 lines
1.9 KiB
Python
"""
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A simple launcher script for TPU training
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Inspired by https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py
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::
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>>> python xla_spawn.py --num_cores=NUM_CORES_YOU_HAVE
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YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other
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arguments of your training script)
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"""
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import importlib
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import os
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import sys
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from argparse import REMAINDER, ArgumentParser
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import torch_xla.distributed.xla_multiprocessing as xmp
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def trim_suffix(s: str, suffix: str):
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return s if not s.endswith(suffix) or len(suffix) == 0 else s[: -len(suffix)]
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def parse_args():
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"""
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Helper function parsing the command line options
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@retval ArgumentParser
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"""
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parser = ArgumentParser(
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description=(
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"PyTorch TPU distributed training launch "
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"helper utility that will spawn up "
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"multiple distributed processes"
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)
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)
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# Optional arguments for the launch helper
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parser.add_argument("--num_cores", type=int, default=1, help="Number of TPU cores to use (1 or 8).")
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# positional
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parser.add_argument(
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"training_script",
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type=str,
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help=(
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"The full module name to the single TPU training "
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"program/script to be launched in parallel, "
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"followed by all the arguments for the "
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"training script"
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),
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)
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# rest from the training program
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parser.add_argument("training_script_args", nargs=REMAINDER)
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return parser.parse_args()
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def main():
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args = parse_args()
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# Import training_script as a module.
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mod_name = trim_suffix(os.path.basename(args.training_script), ".py")
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mod = importlib.import_module(mod_name)
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# Patch sys.argv
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sys.argv = [args.training_script] + args.training_script_args + ["--tpu_num_cores", str(args.num_cores)]
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xmp.spawn(mod._mp_fn, args=(), nprocs=args.num_cores)
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if __name__ == "__main__":
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main()
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