pytorch

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"""Basic runner for the instruction count microbenchmarks.
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The contents of this file are placeholders, and will be replaced by more
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expressive and robust components (e.g. better runner and result display
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components) in future iterations. However this allows us to excercise the
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underlying benchmark generation infrastructure in the mean time.
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"""
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import argparse
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import sys
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from typing import List
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from applications import ci
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from core.expand import materialize
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from definitions.standard import BENCHMARKS
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from execution.runner import Runner
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from execution.work import WorkOrder
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def main(argv: List[str]) -> None:
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    work_orders = tuple(
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        WorkOrder(label, autolabels, timer_args, timeout=600, retries=2)
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        for label, autolabels, timer_args in materialize(BENCHMARKS)
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    )
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    results = Runner(work_orders).run()
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    for work_order in work_orders:
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        print(
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            work_order.label,
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            work_order.autolabels,
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            work_order.timer_args.num_threads,
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            results[work_order].instructions,
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        )
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if __name__ == "__main__":
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    modes = {
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        "debug": main,
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        "ci": ci.main,
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    }
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    parser = argparse.ArgumentParser()
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    parser.add_argument("--mode", type=str, choices=list(modes.keys()), default="debug")
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    args, remaining_args = parser.parse_known_args(sys.argv)
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    modes[args.mode](remaining_args[1:])
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