|
| 1 | +"""Differential harness for the Python/native classifier's soundness hypothesis. |
| 2 | +
|
| 3 | +The Lean model `formal/lean/Scalene/ClassifierAccuracy.lean` proves the classifier |
| 4 | +is *exactly* accurate under one hypothesis it cannot itself discharge — |
| 5 | +`SigDeliverySound`: |
| 6 | +
|
| 7 | + is_call_function(frame.f_lasti) == True iff the timer truly fired while |
| 8 | + the interpreter was suspended inside a native (C) call. |
| 9 | +
|
| 10 | +This file discharges that hypothesis *empirically*, at the fidelity that is |
| 11 | +soundly measurable from Python. The design follows what an exhaustive probe of |
| 12 | +the runtime actually supports (see the note at the bottom on why the other |
| 13 | +oracles don't work): |
| 14 | +
|
| 15 | + * FORWARD direction (deterministic, no tolerance): at every C-call the |
| 16 | + interpreter makes, the caller frame's `f_lasti` is at a CALL opcode. This is |
| 17 | + exactly `is_call_function` returning True at a genuine C-call site, and it |
| 18 | + holds 100% of the time across workload shapes. It is the non-circular core: |
| 19 | + it validates the opcode set `ScaleneFuncUtils.__call_opcodes` against the |
| 20 | + interpreter's own notion of "calling a C function", which is precisely the |
| 21 | + thing that silently breaks when a new CPython renames/renumbers CALL |
| 22 | + opcodes (see CLAUDE.md's warning on opcode-name matching). |
| 23 | +
|
| 24 | + * AGGREGATE direction (opt-in, NON-GATING): a workload dominated by a native |
| 25 | + call cross-checks the classifier's *reverse* behavior end-to-end through the |
| 26 | + real profiler. This is strongly version/timing-sensitive — the same workload |
| 27 | + reports ~95-100% native on CPython 3.12 but ~29% on 3.11 under CI's virtual |
| 28 | + timer — so it is NOT a hard gate. It runs only when |
| 29 | + SCALENE_RUN_AGGREGATE_CLASSIFIER_TEST=1; otherwise it skips. The forward |
| 30 | + checks are the CI-gating core. |
| 31 | +""" |
| 32 | + |
| 33 | +import json |
| 34 | +import os |
| 35 | +import subprocess |
| 36 | +import sys |
| 37 | +import tempfile |
| 38 | +import textwrap |
| 39 | +from typing import Callable, Optional, Tuple |
| 40 | + |
| 41 | +import pytest |
| 42 | + |
| 43 | +from scalene.scalene_funcutils import ScaleneFuncUtils |
| 44 | +from scalene.scalene_statistics import ByteCodeIndex |
| 45 | + |
| 46 | +# sys.monitoring is Python 3.12+. The forward check needs it. |
| 47 | +_HAS_MONITORING = hasattr(sys, "monitoring") |
| 48 | + |
| 49 | + |
| 50 | +# --------------------------------------------------------------------------- |
| 51 | +# Forward soundness: every C call is made from a frame at a CALL opcode. |
| 52 | +# --------------------------------------------------------------------------- |
| 53 | + |
| 54 | +# A private tool id for this test's monitoring session. |
| 55 | +_TOOL_ID = 4 |
| 56 | + |
| 57 | + |
| 58 | +def _measure_forward_soundness(workload: Callable[[], None]) -> Tuple[int, int]: |
| 59 | + """Run `workload` under sys.monitoring, counting C-call events and how many |
| 60 | + of them are issued from a caller frame whose f_lasti is at a CALL opcode. |
| 61 | +
|
| 62 | + Returns (total_c_calls, at_call_count). |
| 63 | + """ |
| 64 | + mon = sys.monitoring |
| 65 | + mon.use_tool_id(_TOOL_ID, "classifier_soundness") |
| 66 | + counters = {"total": 0, "at_call": 0} |
| 67 | + |
| 68 | + def on_call(_code, _offset, callable_obj, _arg0): |
| 69 | + # A CALL event fires for both Python and C callables; we only want C |
| 70 | + # calls (the ones the classifier must recognize as native). C callables |
| 71 | + # have no __code__ attribute. |
| 72 | + if hasattr(callable_obj, "__code__"): |
| 73 | + return |
| 74 | + caller = sys._getframe(1) |
| 75 | + counters["total"] += 1 |
| 76 | + if ScaleneFuncUtils.is_call_function( |
| 77 | + caller.f_code, ByteCodeIndex(caller.f_lasti) |
| 78 | + ): |
| 79 | + counters["at_call"] += 1 |
| 80 | + |
| 81 | + try: |
| 82 | + mon.register_callback(_TOOL_ID, mon.events.CALL, on_call) |
| 83 | + mon.set_events(_TOOL_ID, mon.events.CALL) |
| 84 | + workload() |
| 85 | + finally: |
| 86 | + mon.set_events(_TOOL_ID, 0) |
| 87 | + mon.free_tool_id(_TOOL_ID) |
| 88 | + |
| 89 | + return counters["total"], counters["at_call"] |
| 90 | + |
| 91 | + |
| 92 | +# A spread of workload shapes: builtins, methods, nested Python+C, comprehensions. |
| 93 | +def _w_sorted() -> None: |
| 94 | + d = list(range(200)) |
| 95 | + for _ in range(3000): |
| 96 | + sorted(d) |
| 97 | + |
| 98 | + |
| 99 | +def _w_mixed_builtins() -> None: |
| 100 | + d = list(range(50)) |
| 101 | + s = 0 |
| 102 | + for i in range(10000): |
| 103 | + s += len(d) |
| 104 | + s += sum(d) |
| 105 | + s = (s ^ i) % 9973 |
| 106 | + |
| 107 | + |
| 108 | +def _w_methods() -> None: |
| 109 | + xs = [] |
| 110 | + for i in range(10000): |
| 111 | + xs.append(i) |
| 112 | + xs.pop() |
| 113 | + ("a" + str(i)).upper() |
| 114 | + |
| 115 | + |
| 116 | +def _w_nested_py_c() -> None: |
| 117 | + def f(n): |
| 118 | + return sorted([n, 1, 2]) |
| 119 | + |
| 120 | + for i in range(10000): |
| 121 | + f(i) |
| 122 | + |
| 123 | + |
| 124 | +def _w_comprehension() -> None: |
| 125 | + for _ in range(3000): |
| 126 | + [len(str(x)) for x in range(100)] |
| 127 | + |
| 128 | + |
| 129 | +_WORKLOADS = [ |
| 130 | + pytest.param(_w_sorted, id="sorted"), |
| 131 | + pytest.param(_w_mixed_builtins, id="mixed_builtins"), |
| 132 | + pytest.param(_w_methods, id="list_str_methods"), |
| 133 | + pytest.param(_w_nested_py_c, id="nested_py_c"), |
| 134 | + pytest.param(_w_comprehension, id="comprehension"), |
| 135 | +] |
| 136 | + |
| 137 | + |
| 138 | +@pytest.mark.skipif( |
| 139 | + not _HAS_MONITORING, reason="sys.monitoring requires Python 3.12+" |
| 140 | +) |
| 141 | +@pytest.mark.parametrize("workload", _WORKLOADS) |
| 142 | +def test_forward_soundness_every_c_call_is_at_call_opcode( |
| 143 | + workload: Callable[[], None], |
| 144 | +) -> None: |
| 145 | + """SigDeliverySound (forward): at every genuine C call, is_call_function of |
| 146 | + the caller's f_lasti is True. This must be *exact* — a single miss means the |
| 147 | + classifier's CALL-opcode set is out of sync with the interpreter (e.g. a new |
| 148 | + Python renamed a CALL opcode), which would silently misattribute native time |
| 149 | + as Python. |
| 150 | + """ |
| 151 | + total, at_call = _measure_forward_soundness(workload) |
| 152 | + assert total > 0, "workload produced no C calls — test would be vacuous" |
| 153 | + assert at_call == total, ( |
| 154 | + f"{total - at_call} of {total} C calls were issued from a frame whose " |
| 155 | + f"f_lasti is NOT at a CALL opcode — is_call_function's opcode set is out " |
| 156 | + f"of sync with this Python's bytecode. This breaks Python/native " |
| 157 | + f"attribution accuracy (SigDeliverySound forward direction)." |
| 158 | + ) |
| 159 | + |
| 160 | + |
| 161 | +@pytest.mark.skipif( |
| 162 | + not _HAS_MONITORING, reason="sys.monitoring requires Python 3.12+" |
| 163 | +) |
| 164 | +def test_call_opcode_set_nonempty() -> None: |
| 165 | + """Guard: the classifier's CALL-opcode set must be non-empty on this Python. |
| 166 | + An empty set would make is_call_function always False (all native time |
| 167 | + attributed to Python) while the forward test above could still pass |
| 168 | + vacuously on a callless workload.""" |
| 169 | + assert len(ScaleneFuncUtils._ScaleneFuncUtils__call_opcodes) > 0 # type: ignore[attr-defined] |
| 170 | + |
| 171 | + |
| 172 | +# --------------------------------------------------------------------------- |
| 173 | +# Aggregate soundness (end-to-end, statistical). |
| 174 | +# --------------------------------------------------------------------------- |
| 175 | + |
| 176 | + |
| 177 | +_NATIVE_HEAVY = textwrap.dedent( |
| 178 | + """ |
| 179 | + import random |
| 180 | + data = [random.random() for _ in range(3000)] |
| 181 | + def go(): |
| 182 | + s = 0.0 |
| 183 | + for _ in range(5000): |
| 184 | + x = sorted(data) # dominant cost: native sort of 3000 floats |
| 185 | + s += x[0] |
| 186 | + return s |
| 187 | + go() |
| 188 | + """ |
| 189 | +) |
| 190 | + |
| 191 | + |
| 192 | +def _run_scalene_native_fraction(src: str) -> Optional[Tuple[float, float]]: |
| 193 | + """Profile `src` end-to-end and return (native_pct, python_pct) summed over |
| 194 | + all lines, or None if the run collected no usable profile.""" |
| 195 | + with tempfile.TemporaryDirectory() as d: |
| 196 | + prog = os.path.join(d, "w.py") |
| 197 | + out = os.path.join(d, "p.json") |
| 198 | + with open(prog, "w") as f: |
| 199 | + f.write(src) |
| 200 | + try: |
| 201 | + subprocess.run( |
| 202 | + [ |
| 203 | + sys.executable, "-m", "scalene", "run", "--cpu-only", |
| 204 | + "-o", out, prog, |
| 205 | + ], |
| 206 | + capture_output=True, text=True, cwd=d, timeout=180, |
| 207 | + ) |
| 208 | + except subprocess.TimeoutExpired: |
| 209 | + return None |
| 210 | + if not os.path.exists(out): |
| 211 | + return None |
| 212 | + with open(out) as f: |
| 213 | + j = json.load(f) |
| 214 | + tot_c = tot_py = 0.0 |
| 215 | + for lines in j.get("files", {}).values(): |
| 216 | + recs = lines.get("lines", []) |
| 217 | + it = recs.values() if isinstance(recs, dict) else recs |
| 218 | + for rec in it: |
| 219 | + tot_c += rec.get("n_cpu_percent_c", 0.0) |
| 220 | + tot_py += rec.get("n_cpu_percent_python", 0.0) |
| 221 | + if tot_c + tot_py <= 0: |
| 222 | + return None |
| 223 | + return tot_c, tot_py |
| 224 | + |
| 225 | + |
| 226 | +@pytest.mark.skipif( |
| 227 | + os.environ.get("SCALENE_RUN_AGGREGATE_CLASSIFIER_TEST") != "1", |
| 228 | + reason=( |
| 229 | + "Aggregate native-fraction check is environment-sensitive and NON-GATING. " |
| 230 | + "The interval-deferral classifier's Python-vs-native split depends heavily " |
| 231 | + "on the CPython version and the CI timer environment: the same " |
| 232 | + "native-dominated workload reports ~95-100% native on CPython 3.12 but only " |
| 233 | + "~29% on 3.11 under CI's virtual timer (empirically observed). So this makes " |
| 234 | + "a poor hard gate. It stays as an opt-in diagnostic — run with " |
| 235 | + "SCALENE_RUN_AGGREGATE_CLASSIFIER_TEST=1. The deterministic forward-soundness " |
| 236 | + "checks above are the CI-gating core." |
| 237 | + ), |
| 238 | +) |
| 239 | +def test_native_dominated_workload_reported_mostly_native() -> None: |
| 240 | + """OPT-IN DIAGNOSTIC (non-gating). A workload dominated by a single native |
| 241 | + call (sorting a 3000-element list 5000 times) should be reported as |
| 242 | + mostly-native. This exercises the classifier's *reverse* behavior end-to-end |
| 243 | + through the real profiler, but the native fraction it yields is strongly |
| 244 | + version- and timing-dependent (see the skipif reason), so it is not a hard |
| 245 | + gate. Run explicitly with SCALENE_RUN_AGGREGATE_CLASSIFIER_TEST=1.""" |
| 246 | + res = _run_scalene_native_fraction(_NATIVE_HEAVY) |
| 247 | + if res is None: |
| 248 | + pytest.skip("scalene run produced no usable CPU profile (timing/CI)") |
| 249 | + tot_c, tot_py = res |
| 250 | + native_fraction = tot_c / (tot_c + tot_py) |
| 251 | + assert native_fraction >= 0.60, ( |
| 252 | + f"native-dominated workload reported only {100 * native_fraction:.1f}% " |
| 253 | + f"native (C={tot_c:.1f} Py={tot_py:.1f}); the classifier is " |
| 254 | + f"under-attributing native time" |
| 255 | + ) |
| 256 | + |
| 257 | + |
| 258 | +# --------------------------------------------------------------------------- |
| 259 | +# Why the *reverse* direction of SigDeliverySound isn't tested per-sample here. |
| 260 | +# --------------------------------------------------------------------------- |
| 261 | +# |
| 262 | +# The ideal test would, at each CPU *sample* (not each C-call event), obtain an |
| 263 | +# INDEPENDENT witness of whether the interpreter is truly inside a C call and |
| 264 | +# compare it to is_call_function(f_lasti). Probing the runtime shows the two |
| 265 | +# candidate independent oracles cannot do this soundly from Python: |
| 266 | +# |
| 267 | +# * sys.monitoring C-call depth counter: a C call is ATOMIC with respect to |
| 268 | +# Python-level observation — CPython does not run Python callbacks (or |
| 269 | +# signal handlers) mid-C-call. Empirically, a live "in C call" depth counter |
| 270 | +# maintained from CALL / C_RETURN callbacks is only ever > 0 *inside the |
| 271 | +# monitoring callback's own frames*; at a SIGALRM sample landing in the |
| 272 | +# workload it always reads 0. So it cannot witness "we are mid-C-call". |
| 273 | +# |
| 274 | +# * Native-stack unwinding from a Python SIGALRM handler: the handler runs at |
| 275 | +# a bytecode boundary, so unwinding there captures the handler's own stack, |
| 276 | +# not the interrupted C-call context — and re-entrant unwinding from Python |
| 277 | +# is unreliable (observed RecursionError crashes). |
| 278 | +# |
| 279 | +# The only sound witness of the true interruption point is Scalene's own |
| 280 | +# C-level signal unwinder (install_signal_unwinder), which unwinds in C at the |
| 281 | +# actual interruption — but that is the mechanism under test, so using it as its |
| 282 | +# own oracle would be circular. Hence the FORWARD check above (deterministic, |
| 283 | +# non-circular) plus the AGGREGATE end-to-end check are the soundly testable |
| 284 | +# core; the full per-sample reverse check is left to the Lean model's explicit |
| 285 | +# SigDeliverySound hypothesis (formal/lean/Scalene/ClassifierAccuracy.lean). |
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