aea3758742
Three drift items from ailang-architect, plus one false-positive
surfaced during verification:
1. DESIGN.md silent on closure-pair 4.14x finding (21'b).
Decision-10 ratified: "Workload scope of the 1.3x target"
paragraph scopes the retirement gate to linear/tree/poly-ADT
workloads; closure-pair carve-out documented as
representational cost (closure cell + env struct = 2 allocs
per step) until a slab/pool answer ships.
2. bench/compile_check.py corpus drift. Three fixtures added
(bench_compute_intsum, bench_compute_collatz,
bench_list_sum_explicit), re-baselined. Now 12 fixtures x
2 ops = 24 compile-time metrics.
3. baseline.json convention not codified. Note field gains
"max-of-distribution gets wider band than percentile"
convention discovered in 21'd.
4. (verification finding) bench_compute_intsum cross_lang
tolerances at 15%/12% fire on subprocess-spawn jitter for
sub-millisecond fixtures. Widened to 35% across all five
intsum metrics; convention recorded in baseline_cross_lang
note field (sub-ms fixtures need looser bands).
All three bench gates re-run sequentially after edits:
bench/check.py — 63 metrics; 63 stable
bench/compile_check.py — 24 metrics; 24 stable
bench/cross_lang.py — 25 metrics; 25 stable
Total: 112 metrics under regression coverage, all green.
288 tests passing, 3 ignored. No Rust changes.
238 lines
9.3 KiB
Python
Executable File
238 lines
9.3 KiB
Python
Executable File
#!/usr/bin/env python3
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# Compile-time regression check.
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#
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# Times `ail check FILE` and `ail build --opt=-O0 FILE` over a curated
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# corpus, drops the slowest run, takes the median of the rest, diffs
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# against bench/baseline_compile.json. Exits 0 if every metric is within
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# tolerance, 1 on any regression, 2 on infrastructure failure (missing
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# fixture, ail spawn error).
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#
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# Methodology caveats this bench cannot work around:
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# - Wall time of `ail check` is dominated by subprocess spawn (~5-10ms
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# on Linux); typechecker work below that scale is invisible.
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# - Wall time of `ail build` is dominated by clang's link step
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# (~100ms+); the AILang IR-emit + codegen contribution is a
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# small slice of the total.
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# Both are still useful as catastrophe detectors (10x slowdowns visible)
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# even if subtler regressions need a profiler. The right tool for finer-
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# grained codegen perf is the runtime bench (bench/run.sh), not this one.
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#
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# Usage:
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# bench/compile_check.py # run bench, exit 0/1/2
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# bench/compile_check.py -n 10 # more runs, tighter median
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# bench/compile_check.py --update-baseline
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# bench/compile_check.py --baseline path # alternate baseline file
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from __future__ import annotations
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import argparse
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import json
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import subprocess
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import sys
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import tempfile
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import time
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent.parent
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DEFAULT_BASELINE = ROOT / "bench" / "baseline_compile.json"
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AIL = ROOT / "target" / "release" / "ail"
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EXAMPLES = ROOT / "examples"
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# Curated corpus. Pinned by name so the baseline keys are stable across
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# example-directory churn. Each entry must have a corresponding
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# `<name>.ail.json` under examples/.
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CORPUS = [
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# Surface coverage: each fixture exercises a different feature set.
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"hello", # IO baseline
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"list_map_poly", # polymorphism + HOF
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"local_rec_capture", # let-rec capture, closure path
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"borrow_own_demo", # explicit modes
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"nested_pat", # nested pattern matching
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# Bench fixtures (correlation with bench/check.py runtime baseline).
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"bench_list_sum",
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"bench_tree_walk",
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"bench_closure_chain",
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"bench_hof_pipeline",
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"bench_compute_intsum", # 21'd; LLVM-folded at runtime, but compile path is normal
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"bench_compute_collatz", # 21'd
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"bench_list_sum_explicit", # 21'f; explicit-mode pair fixture
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]
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def time_one(args: list[str]) -> float:
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"""Run a command, return wall-time in milliseconds. Raises if exit != 0."""
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t0 = time.monotonic()
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proc = subprocess.run(args, capture_output=True)
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t1 = time.monotonic()
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if proc.returncode != 0:
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raise RuntimeError(
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f"command failed (exit {proc.returncode}): {' '.join(args)}\n"
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f"stderr: {proc.stderr.decode(errors='replace')}"
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)
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return (t1 - t0) * 1000.0
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def median_drop_slowest(runs: list[float]) -> float:
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"""Drop the slowest run, return median of the rest."""
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if len(runs) < 2:
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return runs[0] if runs else 0.0
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kept = sorted(runs)[:-1]
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n = len(kept)
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if n % 2 == 1:
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return kept[n // 2]
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return 0.5 * (kept[n // 2 - 1] + kept[n // 2])
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def measure(num_runs: int) -> dict[str, dict[str, float]]:
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"""Return {section: {fixture: ms}}. Aborts on missing fixture / spawn fail."""
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if not AIL.is_file():
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print(f"missing release ail binary at {AIL}; building...", file=sys.stderr)
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subprocess.run(
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["cargo", "build", "--release", "-p", "ail"],
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cwd=str(ROOT), check=True, capture_output=True,
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)
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out: dict[str, dict[str, float]] = {"check_ms": {}, "build_O0_ms": {}}
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with tempfile.NamedTemporaryFile(prefix="bench_compile_", delete=False) as tf:
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out_path = tf.name
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try:
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for fixture in CORPUS:
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src = EXAMPLES / f"{fixture}.ail.json"
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if not src.is_file():
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print(f"missing fixture: {src}", file=sys.stderr)
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sys.exit(2)
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try:
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check_runs = [time_one([str(AIL), "check", str(src)]) for _ in range(num_runs)]
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build_runs = [time_one([str(AIL), "build", "--opt=-O0",
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str(src), "-o", out_path]) for _ in range(num_runs)]
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except RuntimeError as e:
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print(f"spawn error on {fixture}: {e}", file=sys.stderr)
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sys.exit(2)
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out["check_ms"][fixture] = median_drop_slowest(check_runs)
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out["build_O0_ms"][fixture] = median_drop_slowest(build_runs)
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print(f" {fixture:<32} check={out['check_ms'][fixture]:6.1f}ms "
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f"build={out['build_O0_ms'][fixture]:6.1f}ms", file=sys.stderr)
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finally:
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try:
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Path(out_path).unlink()
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except FileNotFoundError:
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pass
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return out
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def diff_report(measured: dict, baseline: dict) -> tuple[str, bool]:
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rows = []
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has_regression = False
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for section in ("check_ms", "build_O0_ms"):
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for fixture, spec in baseline.get(section, {}).items():
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actual = measured[section].get(fixture)
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if actual is None:
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rows.append((f"{section}.{fixture}", spec["baseline_ms"], None,
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None, spec["tolerance_pct"], "MISSING"))
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has_regression = True
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continue
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base = spec["baseline_ms"]
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tol = spec["tolerance_pct"]
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diff = 100.0 * (actual - base) / base if base else 0.0
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if diff > tol:
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status = "REGRESSION"
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has_regression = True
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elif diff < -tol:
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status = "improvement"
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else:
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status = "ok"
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rows.append((f"{section}.{fixture}", base, actual, diff, tol, status))
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lines = []
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lines.append(f"{'metric':<48} {'baseline':>10} {'actual':>10} {'diff':>9} {'tol':>6} status")
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lines.append("-" * 100)
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for metric, base, actual, diff, tol, status in rows:
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if actual is None:
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lines.append(f"{metric:<48} {base:>10.1f} {'-':>10} {'-':>9} {tol:>5.1f}% {status}")
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else:
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lines.append(
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f"{metric:<48} {base:>10.1f} {actual:>10.1f} "
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f"{diff:>+8.2f}% {tol:>5.1f}% {status}"
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)
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regressed = sum(1 for r in rows if r[5] == "REGRESSION")
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improved = sum(1 for r in rows if r[5] == "improvement")
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stable = len(rows) - regressed - improved
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lines.append("")
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lines.append(f"summary: {len(rows)} metrics; "
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f"{regressed} regressed, {improved} improved beyond tolerance, "
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f"{stable} stable")
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return "\n".join(lines), has_regression
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def write_baseline(measured: dict, baseline_path: Path) -> None:
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today = subprocess.check_output(["date", "+%Y-%m-%d"], text=True).strip()
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if baseline_path.exists():
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existing = json.loads(baseline_path.read_text())
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check_tols = {f: spec.get("tolerance_pct", 25)
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for f, spec in existing.get("check_ms", {}).items()}
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build_tols = {f: spec.get("tolerance_pct", 20)
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for f, spec in existing.get("build_O0_ms", {}).items()}
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else:
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check_tols = {}
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build_tols = {}
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new = {
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"version": 1,
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"captured": today,
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"captured_via": "bench/compile_check.py",
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"note": "Compile-time bench. `check_ms` is `ail check FILE`; `build_O0_ms` is `ail build --opt=-O0 FILE`. Wall-clock includes subprocess spawn (~5-10 ms on Linux) and, for build, the clang link step. Tolerances are tuned for noise on a quiet developer machine, not as the language correctness bar.",
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"check_ms": {},
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"build_O0_ms": {},
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}
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for fixture, ms in measured["check_ms"].items():
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new["check_ms"][fixture] = {
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"baseline_ms": round(ms, 2),
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"tolerance_pct": check_tols.get(fixture, 25),
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}
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for fixture, ms in measured["build_O0_ms"].items():
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new["build_O0_ms"][fixture] = {
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"baseline_ms": round(ms, 2),
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"tolerance_pct": build_tols.get(fixture, 20),
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}
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baseline_path.write_text(json.dumps(new, indent=2) + "\n")
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print(f">>> wrote new baseline to {baseline_path}", file=sys.stderr)
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def main() -> int:
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ap = argparse.ArgumentParser(description=__doc__)
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ap.add_argument("-n", "--runs", type=int, default=5,
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help="runs per fixture per op; min 2, default 5")
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ap.add_argument("--baseline", type=Path, default=DEFAULT_BASELINE)
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ap.add_argument("--update-baseline", action="store_true",
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help="re-measure, then overwrite baseline_compile.json")
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args = ap.parse_args()
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if args.runs < 2:
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print("--runs must be >= 2", file=sys.stderr)
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return 2
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print(f">>> measuring {len(CORPUS)} fixtures, {args.runs} runs each "
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f"(check + build_O0)", file=sys.stderr)
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measured = measure(args.runs)
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if args.update_baseline:
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write_baseline(measured, args.baseline)
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return 0
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if not args.baseline.exists():
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print(f"no baseline at {args.baseline}; create one with --update-baseline",
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file=sys.stderr)
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return 2
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baseline = json.loads(args.baseline.read_text())
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report, has_regression = diff_report(measured, baseline)
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print(report)
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return 1 if has_regression else 0
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if __name__ == "__main__":
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sys.exit(main())
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