94 lines
3.5 KiB
Python
94 lines
3.5 KiB
Python
#!/usr/bin/env python3
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"""Freeze the training-task prefix models before prospective GPU work."""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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from analyze_prefixes import (
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DEFAULT_REGULARIZATION,
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POLICY_THRESHOLDS,
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build_examples,
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fit_frozen_model,
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sha256_file,
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)
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def main() -> None:
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parser = argparse.ArgumentParser()
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parser.add_argument("--phase6-metrics", type=Path, required=True)
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parser.add_argument("--prefix-metrics", type=Path, required=True)
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parser.add_argument("--raw-root", type=Path, required=True)
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parser.add_argument("--output", type=Path, required=True)
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args = parser.parse_args()
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cutoff_s = 5.0
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threshold = 0.95
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if threshold not in POLICY_THRESHOLDS:
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raise AssertionError("frozen threshold is outside audited policy thresholds")
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phase6 = json.loads(args.phase6_metrics.read_text(encoding="utf-8"))
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examples = build_examples(phase6, args.raw_root, cutoff_s)
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payload = {
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"schema": "fidelity-prefix-model-v1",
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"status": "FROZEN_BEFORE_PROSPECTIVE_RUN",
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"cutoff_s": cutoff_s,
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"accept_probability": threshold,
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"reject_probability": 1.0 - threshold,
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"regularization": DEFAULT_REGULARIZATION,
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"label": "same-placement 2-of-3 adjudicated anchor feasibility",
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"training_split_role": "historical training only; never headline test",
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"training_examples": [
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{
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"cell": example.cell,
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"anchor": example.anchor,
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"label_feasible": bool(example.feasible),
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"primary_feasible": bool(example.primary_feasible),
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"completion_time_source": example.completion_time_source,
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}
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for example in examples
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],
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"models": {
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"outcome_only": fit_frozen_model(
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examples,
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instrumentation_aware=False,
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regularization=DEFAULT_REGULARIZATION,
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),
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"instrumentation_aware": fit_frozen_model(
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examples,
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instrumentation_aware=True,
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regularization=DEFAULT_REGULARIZATION,
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),
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},
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"provenance": {
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"phase6_metrics": str(args.phase6_metrics.resolve()),
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"phase6_metrics_sha256": sha256_file(args.phase6_metrics),
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"prefix_metrics": str(args.prefix_metrics.resolve()),
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"prefix_metrics_sha256": sha256_file(args.prefix_metrics),
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"raw_root": str(args.raw_root.resolve()),
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},
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"sanity": {
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"n": len(examples),
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"positive": sum(example.feasible for example in examples),
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"negative": sum(not example.feasible for example in examples),
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"cells": len({example.cell for example in examples}),
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"invariants": {
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"n_37": len(examples) == 37,
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"cells_12": len({example.cell for example in examples}) == 12,
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"both_labels": len({example.feasible for example in examples}) == 2,
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"cutoff_5s": cutoff_s == 5.0,
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"threshold_0.95": threshold == 0.95,
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},
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},
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}
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if not all(payload["sanity"]["invariants"].values()):
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raise RuntimeError(f"model freeze invariants failed: {payload['sanity']}")
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args.output.parent.mkdir(parents=True, exist_ok=True)
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args.output.write_text(json.dumps(payload, indent=2, sort_keys=True) + "\n")
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print(json.dumps({"status": payload["status"], "output": str(args.output)}))
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if __name__ == "__main__":
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main()
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