Buckets:
| from __future__ import annotations | |
| import argparse | |
| import os | |
| from pathlib import Path | |
| for _name in ( | |
| "OMP_NUM_THREADS", | |
| "OPENBLAS_NUM_THREADS", | |
| "MKL_NUM_THREADS", | |
| "VECLIB_MAXIMUM_THREADS", | |
| "NUMEXPR_NUM_THREADS", | |
| "BLIS_NUM_THREADS", | |
| ): | |
| os.environ[_name] = "1" | |
| os.environ["LOSS_AWARE_TIMING_CLI_BOOTSTRAP"] = "before_scientific_imports_v1" | |
| from loss_aware_dro_repro.timing_harness import run_timing_escalation # noqa: E402 | |
| def main() -> None: | |
| parser = argparse.ArgumentParser( | |
| description="Run the parent-bound, local-only fixed-1000 timing escalation." | |
| ) | |
| parser.add_argument("--config", type=Path, required=True) | |
| parser.add_argument("--output", type=Path, required=True) | |
| arguments = parser.parse_args() | |
| run_timing_escalation(arguments.config, arguments.output) | |
| if __name__ == "__main__": | |
| main() | |
Xet Storage Details
- Size:
- 900 Bytes
- Xet hash:
- 55dd590643d96c2b6ad10e18e02660c50b14564196b103e184996060eb620a23
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.