homemaker-layout/experiments/ab_shapecurve_warmstart.py

71 lines
2.8 KiB
Python
Raw Permalink Normal View History

"""A/B: does shapecurve-DP NM warm-start beat today's cold/proportion-aware
start on wall-clock/evals-to-fail-count, on the real ``driver.search`` loop
(homemaker-py-6xh, DESIGN.md §37.4)?
Scoped to the DP's validated envelope (DESIGN.md §37.2): single storey, no
leaf_sharing/superpose/max_share/multi_use. ``examples/harbor-house-l0`` is
the single-storey de-risk variant of harbor-house built for exactly this
purpose (storey_minimum=1) -- the full multi-storey ``examples/harbor-house``
is out of scope until the multi-storey DP follow-up lands.
Metric: mean (n_hard, n_soft, fitness) of ``driver.search``'s best individual
at a FIXED budget, across several seeds -- same format as §37.1's tiered-
comparator A/B table, not an evals-to-zero race (harbor-house-l0's small
programme does not reliably reach 0 hard fails within a script-scale budget
across all seeds, so a fixed-budget comparison is the fair, reproducible one).
Usage: python experiments/ab_shapecurve_warmstart.py [budget] [n_seeds]
"""
from __future__ import annotations
import sys
import time
from pathlib import Path
from homemaker_layout import dom, driver
PROGRAMME_DIR = Path(__file__).parent.parent / "examples" / "harbor-house-l0"
def run_arm(seed_root: dom.Node, budget: int, seed: int, warmstart: bool):
t0 = time.perf_counter()
r = driver.search(
seed_root, PROGRAMME_DIR, budget=budget, pop_size=8, child_budget=80,
seed_budget=200, seed=seed, leaf_sharing=False,
shapecurve_warmstart=warmstart,
)
elapsed = time.perf_counter() - t0
return r, elapsed
def main() -> None:
budget = int(sys.argv[1]) if len(sys.argv) > 1 else 4000
n_seeds = int(sys.argv[2]) if len(sys.argv) > 2 else 8
seed_root = dom.load(str(PROGRAMME_DIR / "init.dom"))
rows = []
for seed in range(n_seeds):
off, t_off = run_arm(seed_root, budget, seed, warmstart=False)
on, t_on = run_arm(seed_root, budget, seed, warmstart=True)
rows.append((seed, off.best.n_hard, off.best.n_soft, off.best.fitness, t_off,
on.best.n_hard, on.best.n_soft, on.best.fitness, t_on))
print(f"seed {seed}: off hard={off.best.n_hard} soft={off.best.n_soft} "
f"fit={off.best.fitness:.4g} {t_off:.1f}s | "
f"on hard={on.best.n_hard} soft={on.best.n_soft} "
f"fit={on.best.fitness:.4g} {t_on:.1f}s", flush=True)
n = len(rows)
mean = lambda idx: sum(r[idx] for r in rows) / n
print()
print(f"budget={budget} n_seeds={n_seeds} programme={PROGRAMME_DIR}")
print(f"OFF: mean hard={mean(1):.3f} soft={mean(2):.3f} fitness={mean(3):.6g} "
f"wall={mean(4):.1f}s")
print(f"ON : mean hard={mean(5):.3f} soft={mean(6):.3f} fitness={mean(7):.6g} "
f"wall={mean(8):.1f}s")
if __name__ == "__main__":
main()