#!/usr/bin/env python3 from __future__ import annotations import json import tempfile from pathlib import Path import numpy as np from analyze_prefixes import PrefixExample from analyze_strong_pilot import ( fit_model, load_pilot_simulator, predict_model, ) def example(index: int) -> PrefixExample: label = int(index >= 4) return PrefixExample( cell=f"cell-{index // 2}", anchor=float(index), cutoff_s=5.0, tp=1, full_elapsed_s=10.0, feasible=label, primary_feasible=label, outcome=tuple(float(index + offset) for offset in range(13)), instrumentation=tuple(float(index * offset + 1) for offset in range(17)), completion_time_source="exact_monotonic", ) def main() -> None: examples = [example(index) for index in range(8)] simulator = [(float(index), index / 10.0, float(index >= 4)) for index in range(8)] for instrumentation_aware in (False, True): model = fit_model( examples, simulator, instrumentation_aware=instrumentation_aware, regularization=1.0, ) probability = predict_model(model, examples, simulator) assert probability.shape == (8,) assert np.all((probability >= 0.0) & (probability <= 1.0)) payload = { "status": "PASS", "results": [ { "cell": f"cell-{index // 2}", "role": "low1" if index % 2 == 0 else "high1", "scorer": { "throughput_requests_per_second_per_gpu": 1.0 + index, "slo": { "pass_rate": index / 12.0, "feasible": index % 2 == 0, }, }, } for index in range(12) ], } with tempfile.TemporaryDirectory() as temporary: path = Path(temporary) / "metrics.json" path.write_text(json.dumps(payload), encoding="utf-8") features, red_flags = load_pilot_simulator(path) assert len(features) == 12 assert red_flags == [] print("fidelity strong pilot: PASS") if __name__ == "__main__": main()