Add conformal falsification bench contract

This commit is contained in:
Shay 2026-06-06 11:52:01 -07:00
parent ea4ed4abb3
commit f9205cc86e
11 changed files with 935 additions and 1 deletions

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@ -114,6 +114,26 @@ _TEST_SUITES: dict[str, tuple[str, ...]] = {
"tests/test_versor_condition_rust_parity.py",
"tests/test_versor_apply_rust_parity.py",
),
"sensorium": (
"tests/test_sensorium_compiler_delta.py",
"tests/test_audio_compiler.py",
"tests/test_audio_crdt_merge.py",
"tests/test_audio_eval_gates.py",
"tests/test_audio_pack_manifest.py",
"tests/test_audio_sensorium_mount.py",
"tests/test_vision_compiler.py",
"tests/test_vision_crdt_merge.py",
"tests/test_vision_eval_gates.py",
"tests/test_vision_sensorium_mount.py",
"tests/test_sensorimotor_contract.py",
"tests/test_sensorimotor_pack_manifest.py",
"tests/test_observation_frame_contract.py",
"tests/test_observation_frame_harness.py",
"tests/test_environment_falsification.py",
"tests/test_environment_falsification_eval_cli.py",
"tests/test_sensorium_eval_cli.py",
"tests/test_efferent_gate.py",
),
"pulse": (
"tests/test_pulse_integration.py",
"tests/test_graph_diffusion.py",
@ -2354,6 +2374,8 @@ def cmd_eval(args: argparse.Namespace) -> int:
"""Run an eval lane by name, or list available lanes."""
if getattr(args, "lane", None) == "sensorium":
return cmd_eval_sensorium(args)
if getattr(args, "lane", None) == "environment-falsification":
return cmd_eval_environment_falsification(args)
if getattr(args, "lane", None) == "math-contemplation":
return cmd_eval_math_contemplation(args)
@ -2494,6 +2516,33 @@ def cmd_eval_sensorium(args: argparse.Namespace) -> int:
return 0 if report["failed"] == 0 and report["gate_closed"] else 1
def cmd_eval_environment_falsification(args: argparse.Namespace) -> int:
"""Run deterministic environmental falsification replay reports."""
from evals.environment_falsification import build_environment_falsification_report
report = build_environment_falsification_report()
if getattr(args, "json", False):
print(json.dumps(report, ensure_ascii=False, indent=2, sort_keys=True))
else:
print(f"lane : {report['lane']}")
print(f"version : {report['version']}")
print(f"cases : {report['total']}")
print(f"passed : {report['passed']}")
print(f"failed : {report['failed']}")
print(f"report_sha256 : {report['report_sha256']}")
if getattr(args, "report", None):
report_path = Path(args.report)
report_path.parent.mkdir(parents=True, exist_ok=True)
report_path.write_text(
json.dumps(report, ensure_ascii=False, indent=2, sort_keys=True)
)
print(f"\nreport written: {report_path}", file=sys.stderr)
return 0 if report["failed"] == 0 and report["expected_report_hash_ok"] else 1
# ---------------------------------------------------------------------------
# ADR-0172 W3 — math-contemplation CLI lane
# ---------------------------------------------------------------------------

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@ -0,0 +1,71 @@
# ADR-0211: Conformal Falsification Bench
**Status:** Accepted
**Date:** 2026-06-06
**Domains:** `sensorium/environment/`, `evals/environment_falsification/`
**Depends on:** ADR-0198, ADR-0208, ADR-0209
## Context
ADR-0208 established `ObservationFrame` as a deterministic bundle of already
compiled afferent units. ADR-0209 established sensorimotor feedback as afferent
evidence. ADR-0198 established that real motor emission is fail-closed until a
verdict-enforcing efferent gate exists.
The missing contract was falsification: a replayable way to say, "this expected
environmental evidence was or was not observed," without turning observation
frames into fusion, memory mutation, hardware control, or learned truth.
## Decision
CORE will use the Conformal Falsification Bench as a Python-reference replay
contract:
```text
hypothesis / plan
-> ExpectedObservationFrame
-> actual ObservationFrame
-> FalsificationRun
-> replay-stable report
```
The v1 bench is exact and binary:
- `SUPPORTED` when every expected slot is present with the expected merge key and
no unexpected slot appears.
- `FALSIFIED` when any expected slot is missing, changed, or accompanied by
unexpected evidence.
## Contract
- `ObservationFrame` remains afferent-only evidence, not fusion and not a
mutable world model.
- `ExpectedObservationFrame` and `FalsificationRun` are replay artifacts, not
learned truth, reviewed memory, or pack mutation proposals.
- v1 verdicts are only `SUPPORTED` and `FALSIFIED`.
- No probabilistic confidence, numeric tolerance, hardware-noise envelope, or
learned latent is part of the v1 verdict.
- No motor/efferent unit, actuator trace, raw pixel buffer, PCM buffer, event
payload, decoded action payload, Vault mutation, or `generate/*` dependency is
allowed in the bench.
- Public API names are stable:
`ObservationUnitRef`, `ExpectedObservationFrame`, `FalsificationResidual`,
`FalsificationRun`, `build_expected_observation_frame`, and
`compare_expected_to_observation`.
## Consequences
The bench gives CORE a falsifiable environmental replay surface before any
hardware, motor, native backend, or learned world model is admitted. Later event
vision, witness-log import, tabletop lab, and motor governance work must feed or
consume this contract rather than bypass it.
## Proof Obligations
- Expected frame hashes are order-invariant and duplicate-safe.
- Raw payloads and efferent units are rejected before traces are built.
- Missing, unexpected, or changed evidence yields `FALSIFIED`.
- Exact matched evidence yields `SUPPORTED`.
- The bench does not import `generate`, mutate Vault, or call
`ModalityRegistry.decode`.
- `core eval environment-falsification --json` is hash-pinned.

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@ -256,6 +256,34 @@ not directly rewrite language packs, frames, identity axes, or operator code.
Identity manifold mutation by user prompt or correction is forbidden.
## Environmental falsification contract (ADR-0211)
`sensorium.environment.falsification` compares expected afferent evidence with
actual `ObservationFrame` evidence. It is a deterministic replay surface, not a
fusion layer, not reviewed memory, and not a mutable world model.
The v1 verdict set is closed:
```text
SUPPORTED | FALSIFIED
```
`SUPPORTED` means every expected slot matched by merge key and no unexpected
slot appeared. `FALSIFIED` means at least one expected slot was missing,
changed, or accompanied by unexpected evidence. Neither verdict promotes a
claim to reviewed memory or mutates packs, Vault state, identity axes, operator
code, or runtime policy.
Forbidden in the falsification bench:
- raw pixels, PCM, event streams, byte payloads, actuator traces, or decoded
action payloads in traces;
- motor/efferent units in `ExpectedObservationFrame` or `FalsificationRun`;
- learned latents as substrate;
- probabilistic confidence, hardware-noise envelopes, or tolerance thresholds in
v1 verdicts;
- `generate/*` dependencies, Vault mutation, or `ModalityRegistry.decode`.
## Testing policy
Tests should protect load-bearing behavior:

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@ -0,0 +1,5 @@
"""Environment falsification eval lane."""
from evals.environment_falsification.report import build_environment_falsification_report
__all__ = ["build_environment_falsification_report"]

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@ -0,0 +1,3 @@
{
"report_sha256": "c97b2dca7282d0231f1b448add87256cc2f59d39c5cec5ac1350231541e07d0b"
}

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@ -0,0 +1,91 @@
{
"fixtures": [
{
"id": "supported_exact_multimodal",
"expected_verdict": "SUPPORTED",
"expected": {
"audio:left_tone": {
"modality": "audio",
"signal": {"id": "left_tone", "kind": "tone", "ms": 240, "hz": 180, "sweep": 0, "amp": 0.4}
},
"vision:corner": {
"modality": "vision",
"signal": {"id": "corner", "kind": "corner", "size": 32}
},
"sensorimotor:contact": {
"modality": "sensorimotor",
"signal": {
"id": "contact",
"pose_q": [10, -4, 3],
"velocity_q": [1, 0, -1],
"force_torque_q": [2, 3, 5],
"contact_q": [1, 0, 1, 0],
"actuator_state_q": [7, 8]
}
}
},
"actual": "same"
},
{
"id": "falsified_changed_contact",
"expected_verdict": "FALSIFIED",
"expected": {
"sensorimotor:contact": {
"modality": "sensorimotor",
"signal": {
"id": "contact_expected",
"pose_q": [10, -4, 3],
"velocity_q": [1, 0, -1],
"force_torque_q": [2, 3, 5],
"contact_q": [1, 0, 1, 0],
"actuator_state_q": [7, 8]
}
}
},
"actual": {
"sensorimotor:contact": {
"modality": "sensorimotor",
"signal": {
"id": "contact_actual",
"pose_q": [10, -4, 3],
"velocity_q": [1, 0, -1],
"force_torque_q": [2, 3, 5],
"contact_q": [0, 0, 0, 0],
"actuator_state_q": [7, 8]
}
}
}
},
{
"id": "falsified_missing_and_unexpected",
"expected_verdict": "FALSIFIED",
"expected": {
"audio:left_tone": {
"modality": "audio",
"signal": {"id": "left_tone_expected", "kind": "tone", "ms": 240, "hz": 180, "sweep": 0, "amp": 0.4}
},
"vision:box": {
"modality": "vision",
"signal": {"id": "box_expected", "kind": "contour_box", "size": 32}
}
},
"actual": {
"audio:left_tone": {
"modality": "audio",
"signal": {"id": "left_tone_actual", "kind": "tone", "ms": 240, "hz": 180, "sweep": 0, "amp": 0.4}
},
"sensorimotor:unexpected_contact": {
"modality": "sensorimotor",
"signal": {
"id": "unexpected_contact",
"pose_q": [0, 0, 1],
"velocity_q": [0, 0, 0],
"force_torque_q": [1, 1, 1],
"contact_q": [1],
"actuator_state_q": [2]
}
}
}
}
]
}

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@ -0,0 +1,135 @@
"""Deterministic environmental falsification replay report."""
from __future__ import annotations
import json
from pathlib import Path
from typing import Any
import numpy as np
from evals.audio_sensorium.synth import synthesize as synthesize_audio
from evals.sensorimotor_sensorium.synth import synthesize as synthesize_sensorimotor
from evals.vision_sensorium.synth import synthesize as synthesize_vision
from sensorium.audio.canonical import canonicalize as canonicalize_audio
from sensorium.audio.compiler import AudioCompiler
from sensorium.audio.checksum import sha256_json
from sensorium.environment import (
ObservationUnitRef,
build_expected_observation_frame,
build_observation_frame,
compare_expected_to_observation,
)
from sensorium.sensorimotor.compiler import SensorimotorCompiler
from sensorium.vision import VisionCompiler, canonicalize_image
from sensorium.vision.grid import iter_tile_signals
_ROOT = Path(__file__).resolve().parent
_AUDIO_SR = 24_000
def _load_json(name: str) -> dict[str, Any]:
return json.loads((_ROOT / name).read_text(encoding="utf-8"))
def _trace_safe(value: object) -> bool:
if isinstance(value, (np.ndarray, bytes, bytearray)):
return False
if isinstance(value, dict):
return all(_trace_safe(child) for child in value.values())
if isinstance(value, (list, tuple)):
return all(_trace_safe(child) for child in value)
return True
def _compile_unit(spec: dict[str, Any]):
modality = spec["modality"]
signal = spec["signal"]
if modality == "audio":
return AudioCompiler().compile_signal(
canonicalize_audio(synthesize_audio(signal), _AUDIO_SR)
)
if modality == "vision":
image = canonicalize_image(synthesize_vision(signal))
tile = iter_tile_signals(image)[0]
return VisionCompiler().compile_tile(tile)
if modality == "sensorimotor":
return SensorimotorCompiler().compile_signal(synthesize_sensorimotor(signal))
raise ValueError(f"unsupported falsification fixture modality: {modality!r}")
def _refs(spec: dict[str, Any]) -> tuple[ObservationUnitRef, ...]:
return tuple(
ObservationUnitRef(slot_id=slot_id, unit=_compile_unit(unit_spec))
for slot_id, unit_spec in sorted(spec.items())
)
def _actual_spec(case: dict[str, Any]) -> dict[str, Any]:
actual = case["actual"]
if actual == "same":
return case["expected"]
return actual
def _case_report(index: int, case: dict[str, Any]) -> dict[str, object]:
expected_refs = _refs(case["expected"])
actual_refs = _refs(_actual_spec(case))
expected = build_expected_observation_frame(
monotonic_tick=index,
source_clock="environment-falsification-fixture",
unit_refs=expected_refs,
causal_parent_ids=(),
)
actual = build_observation_frame(
monotonic_tick=index,
source_clock="environment-falsification-fixture",
units=tuple(ref.unit for ref in actual_refs),
causal_parent_ids=(expected.expected_id,),
)
run = compare_expected_to_observation(expected, actual, actual_refs=actual_refs)
expected_verdict = str(case["expected_verdict"])
row = {
"id": case["id"],
"expected_verdict": expected_verdict,
"actual_verdict": run.verdict,
"verdict_ok": run.verdict == expected_verdict,
"trace_hygiene_ok": _trace_safe(run.as_dict()),
"expected_sha256": expected.expected_sha256,
"actual_trace_hash": actual.trace_hash,
"run_trace_hash": run.trace_hash,
"residual": run.residual.as_dict(),
}
return row
def _report_hash(report_without_hash: dict[str, object]) -> str:
return sha256_json(report_without_hash)
def build_environment_falsification_report() -> dict[str, object]:
fixtures = _load_json("fixtures.json")["fixtures"]
cases = [_case_report(idx, case) for idx, case in enumerate(fixtures)]
passed = sum(
1
for case in cases
if case["verdict_ok"] is True and case["trace_hygiene_ok"] is True
)
report = {
"lane": "environment-falsification",
"version": "v1",
"total": len(cases),
"passed": passed,
"failed": len(cases) - passed,
"cases": cases,
}
report["report_sha256"] = _report_hash(report)
expected_hashes = _load_json("expected_hashes.json")
report["expected_report_sha256"] = expected_hashes["report_sha256"]
report["expected_report_hash_ok"] = report["report_sha256"] == expected_hashes["report_sha256"]
if not report["expected_report_hash_ok"]:
report["failed"] = int(report["failed"]) + 1
return report
__all__ = ["build_environment_falsification_report"]

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@ -1,6 +1,26 @@
"""Environmental observation contracts for sensorium units."""
from sensorium.environment.falsification import (
ChangedSlot,
ExpectedObservationFrame,
FalsificationResidual,
FalsificationRun,
ObservationUnitRef,
build_expected_observation_frame,
compare_expected_to_observation,
)
from sensorium.environment.frame import ObservationFrame, build_observation_frame
from sensorium.environment.harness import build_fixture_observation_frame
__all__ = ["ObservationFrame", "build_fixture_observation_frame", "build_observation_frame"]
__all__ = [
"ChangedSlot",
"ExpectedObservationFrame",
"FalsificationResidual",
"FalsificationRun",
"ObservationFrame",
"ObservationUnitRef",
"build_expected_observation_frame",
"build_fixture_observation_frame",
"build_observation_frame",
"compare_expected_to_observation",
]

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@ -0,0 +1,307 @@
"""Deterministic expected-vs-actual environmental falsification.
This module compares already-compiled afferent units. It does not compile raw
signals, decode motor commands, fuse modalities, mutate Vault state, or create a
world model.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import Iterable
import numpy as np
from sensorium.audio.checksum import sha256_json
from sensorium.compiler.protocol import CompilationUnitLike, MergeKey
from sensorium.environment.frame import ObservationFrame
_UNSAFE_ATTRS = ("pixels", "samples", "pcm", "waveform", "raw_bytes", "action_trace")
def _reject_unsafe_unit(unit: CompilationUnitLike) -> None:
if bool(getattr(unit, "efferent", False)):
raise ValueError("efferent action traces are not environmental evidence units")
if str(getattr(unit, "pack_id", "")).startswith("motor"):
raise ValueError("motor/efferent packs are not environmental evidence units")
for attr in _UNSAFE_ATTRS:
if hasattr(unit, attr):
value = getattr(unit, attr)
if isinstance(value, (np.ndarray, bytes, bytearray)):
raise TypeError(f"unsafe environmental evidence payload on unit: {attr}")
def _merge_key_record(key: MergeKey) -> list[str]:
return [str(key[0]), str(key[1]), str(key[2])]
def _unit_record(unit: CompilationUnitLike) -> dict[str, object]:
_reject_unsafe_unit(unit)
return {
"merge_key": _merge_key_record(unit.merge_key),
"canonical_sha256": unit.canonical_sha256,
"ir_sha256": unit.ir_sha256,
"pack_id": unit.pack_id,
"pack_manifest_sha256": unit.pack_manifest_sha256,
"projection_sha256": unit.projection_sha256,
"versor_condition": float(unit.versor_condition),
}
@dataclass(frozen=True, slots=True)
class ObservationUnitRef:
"""Slot-labelled reference to one compiled afferent unit."""
slot_id: str
unit: CompilationUnitLike
def __post_init__(self) -> None:
if not self.slot_id.strip():
raise ValueError("ObservationUnitRef.slot_id is required")
_reject_unsafe_unit(self.unit)
@property
def merge_key(self) -> MergeKey:
return self.unit.merge_key
def as_dict(self) -> dict[str, object]:
return {
"slot_id": self.slot_id,
"unit": _unit_record(self.unit),
}
def _canonical_refs(refs: Iterable[ObservationUnitRef]) -> tuple[ObservationUnitRef, ...]:
ordered = sorted(tuple(refs), key=lambda r: (r.slot_id, r.merge_key))
deduped: list[ObservationUnitRef] = []
seen_pairs: set[tuple[str, MergeKey]] = set()
seen_slots: dict[str, MergeKey] = {}
for ref in ordered:
key = (ref.slot_id, ref.merge_key)
if key in seen_pairs:
continue
if ref.slot_id in seen_slots and seen_slots[ref.slot_id] != ref.merge_key:
raise ValueError(f"conflicting units for observation slot: {ref.slot_id}")
seen_pairs.add(key)
seen_slots[ref.slot_id] = ref.merge_key
deduped.append(ref)
return tuple(deduped)
@dataclass(frozen=True, slots=True)
class ExpectedObservationFrame:
"""Replay-stable expectation over afferent observation slots."""
expected_id: str
monotonic_tick: int
source_clock: str
unit_refs: tuple[ObservationUnitRef, ...]
causal_parent_ids: tuple[str, ...]
expected_sha256: str
def as_dict(self) -> dict[str, object]:
return {
"expected_id": self.expected_id,
"monotonic_tick": self.monotonic_tick,
"source_clock": self.source_clock,
"unit_refs": [ref.as_dict() for ref in self.unit_refs],
"causal_parent_ids": list(self.causal_parent_ids),
"expected_sha256": self.expected_sha256,
}
def build_expected_observation_frame(
*,
monotonic_tick: int,
source_clock: str,
unit_refs: Iterable[ObservationUnitRef],
causal_parent_ids: tuple[str, ...] = (),
) -> ExpectedObservationFrame:
if monotonic_tick < 0:
raise ValueError("monotonic_tick must be non-negative")
canonical_refs = _canonical_refs(unit_refs)
payload = {
"kind": "ExpectedObservationFrame",
"monotonic_tick": int(monotonic_tick),
"source_clock": str(source_clock),
"causal_parent_ids": list(causal_parent_ids),
"unit_refs": [ref.as_dict() for ref in canonical_refs],
}
expected_sha256 = sha256_json(payload)
expected_id = sha256_json({
"kind": "ExpectedObservationFrame.id",
"monotonic_tick": int(monotonic_tick),
"source_clock": str(source_clock),
"expected_sha256": expected_sha256,
})
return ExpectedObservationFrame(
expected_id=expected_id,
monotonic_tick=int(monotonic_tick),
source_clock=str(source_clock),
unit_refs=canonical_refs,
causal_parent_ids=tuple(causal_parent_ids),
expected_sha256=expected_sha256,
)
@dataclass(frozen=True, slots=True)
class ChangedSlot:
"""One slot whose compiled evidence changed."""
slot_id: str
expected_merge_key: MergeKey
actual_merge_key: MergeKey
def as_dict(self) -> dict[str, object]:
return {
"slot_id": self.slot_id,
"expected_merge_key": _merge_key_record(self.expected_merge_key),
"actual_merge_key": _merge_key_record(self.actual_merge_key),
}
@dataclass(frozen=True, slots=True)
class FalsificationResidual:
"""Exact slot/set delta between expectation and observation."""
matched: tuple[str, ...]
missing: tuple[str, ...]
unexpected: tuple[str, ...]
changed: tuple[ChangedSlot, ...]
residual_sha256: str
@property
def is_supported(self) -> bool:
return not self.missing and not self.unexpected and not self.changed
def as_dict(self) -> dict[str, object]:
return {
"matched": list(self.matched),
"missing": list(self.missing),
"unexpected": list(self.unexpected),
"changed": [change.as_dict() for change in self.changed],
"residual_sha256": self.residual_sha256,
}
@dataclass(frozen=True, slots=True)
class FalsificationRun:
"""Trace-safe result of one expected-vs-actual comparison."""
expected_id: str
actual_frame_id: str
verdict: str
residual: FalsificationResidual
expected_sha256: str
actual_trace_hash: str
trace_hash: str
def as_dict(self) -> dict[str, object]:
return {
"expected_id": self.expected_id,
"actual_frame_id": self.actual_frame_id,
"verdict": self.verdict,
"residual": self.residual.as_dict(),
"expected_sha256": self.expected_sha256,
"actual_trace_hash": self.actual_trace_hash,
"trace_hash": self.trace_hash,
}
def _refs_by_slot(refs: Iterable[ObservationUnitRef]) -> dict[str, ObservationUnitRef]:
return {ref.slot_id: ref for ref in _canonical_refs(refs)}
def _actual_refs_from_frame(actual: ObservationFrame) -> tuple[ObservationUnitRef, ...]:
return tuple(
ObservationUnitRef(
slot_id="unassigned:" + ":".join(unit.merge_key),
unit=unit,
)
for unit in actual.units
)
def compare_expected_to_observation(
expected: ExpectedObservationFrame,
actual: ObservationFrame,
*,
actual_refs: Iterable[ObservationUnitRef] | None = None,
) -> FalsificationRun:
"""Compare expected slot evidence with an actual afferent observation frame."""
actual_ref_tuple = (
_actual_refs_from_frame(actual)
if actual_refs is None
else _canonical_refs(actual_refs)
)
actual_frame_keys = {unit.merge_key for unit in actual.units}
for ref in actual_ref_tuple:
if ref.merge_key not in actual_frame_keys:
raise ValueError(f"actual ref is not present in ObservationFrame: {ref.slot_id}")
expected_by_slot = _refs_by_slot(expected.unit_refs)
actual_by_slot = _refs_by_slot(actual_ref_tuple)
for unit in actual.units:
if unit.merge_key not in {ref.merge_key for ref in actual_ref_tuple}:
synthetic = ObservationUnitRef(
slot_id="unassigned:" + ":".join(unit.merge_key),
unit=unit,
)
actual_by_slot[synthetic.slot_id] = synthetic
matched: list[str] = []
missing: list[str] = []
changed: list[ChangedSlot] = []
for slot_id, exp_ref in expected_by_slot.items():
act_ref = actual_by_slot.get(slot_id)
if act_ref is None:
missing.append(slot_id)
elif act_ref.merge_key == exp_ref.merge_key:
matched.append(slot_id)
else:
changed.append(ChangedSlot(slot_id, exp_ref.merge_key, act_ref.merge_key))
unexpected = sorted(set(actual_by_slot) - set(expected_by_slot))
residual_payload = {
"matched": sorted(matched),
"missing": sorted(missing),
"unexpected": unexpected,
"changed": [change.as_dict() for change in sorted(changed, key=lambda c: c.slot_id)],
}
residual = FalsificationResidual(
matched=tuple(residual_payload["matched"]),
missing=tuple(residual_payload["missing"]),
unexpected=tuple(unexpected),
changed=tuple(sorted(changed, key=lambda c: c.slot_id)),
residual_sha256=sha256_json(residual_payload),
)
verdict = "SUPPORTED" if residual.is_supported else "FALSIFIED"
trace_payload = {
"kind": "FalsificationRun",
"expected_id": expected.expected_id,
"actual_frame_id": actual.frame_id,
"expected_sha256": expected.expected_sha256,
"actual_trace_hash": actual.trace_hash,
"verdict": verdict,
"residual_sha256": residual.residual_sha256,
}
return FalsificationRun(
expected_id=expected.expected_id,
actual_frame_id=actual.frame_id,
verdict=verdict,
residual=residual,
expected_sha256=expected.expected_sha256,
actual_trace_hash=actual.trace_hash,
trace_hash=sha256_json(trace_payload),
)
__all__ = [
"ChangedSlot",
"ExpectedObservationFrame",
"FalsificationResidual",
"FalsificationRun",
"ObservationUnitRef",
"build_expected_observation_frame",
"compare_expected_to_observation",
]

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from __future__ import annotations
import builtins
from dataclasses import dataclass
from pathlib import Path
import numpy as np
import pytest
from sensorium.environment import (
ObservationUnitRef,
build_expected_observation_frame,
build_observation_frame,
compare_expected_to_observation,
)
@dataclass(frozen=True, slots=True)
class _Unit:
canonical_sha256: str
ir_sha256: str
pack_id: str
pack_manifest_sha256: str
projection_sha256: str
versor: np.ndarray
versor_condition: float = 0.0
@property
def merge_key(self) -> tuple[str, str, str]:
return (self.canonical_sha256, self.ir_sha256, self.projection_sha256)
def _unit(name: str, pack_id: str = "vision_core_v1") -> _Unit:
v = np.zeros(32, dtype=np.float32)
v[0] = 1.0
return _Unit(name, f"ir-{name}", pack_id, "manifest", f"proj-{name}", v)
def _ref(slot: str, name: str, pack_id: str = "vision_core_v1") -> ObservationUnitRef:
return ObservationUnitRef(slot, _unit(name, pack_id))
def test_adr_0211_contract_is_documented():
root = Path(__file__).resolve().parents[1]
adr = root / "docs" / "decisions" / "ADR-0211-conformal-falsification-bench.md"
runtime = root / "docs" / "runtime_contracts.md"
assert adr.exists()
adr_text = adr.read_text(encoding="utf-8")
runtime_text = runtime.read_text(encoding="utf-8")
assert "`ObservationFrame` remains afferent-only evidence" in adr_text
assert "SUPPORTED" in adr_text
assert "FALSIFIED" in adr_text
assert "Environmental falsification contract (ADR-0211)" in runtime_text
def test_expected_frame_hash_is_order_invariant_and_duplicate_safe():
a = _ref("slot:a", "a")
b = _ref("slot:b", "b")
f1 = build_expected_observation_frame(
monotonic_tick=1,
source_clock="fixture",
unit_refs=(a, b, a),
)
f2 = build_expected_observation_frame(
monotonic_tick=1,
source_clock="fixture",
unit_refs=(b, a),
)
assert f1.expected_sha256 == f2.expected_sha256
assert f1.expected_id == f2.expected_id
assert len(f1.unit_refs) == 2
def test_raw_payloads_are_rejected():
@dataclass(frozen=True, slots=True)
class BadUnit(_Unit):
pixels: bytes = b"raw"
with pytest.raises(TypeError, match="unsafe environmental evidence payload"):
ObservationUnitRef(
"bad",
BadUnit("a", "ir-a", "vision_core_v1", "manifest", "proj-a", np.zeros(32, dtype=np.float32)),
)
def test_efferent_and_motor_units_are_rejected():
@dataclass(frozen=True, slots=True)
class ActionUnit(_Unit):
efferent: bool = True
with pytest.raises(ValueError, match="efferent"):
ObservationUnitRef(
"action",
ActionUnit("m", "ir-m", "motor_test", "manifest", "proj-m", np.zeros(32, dtype=np.float32)),
)
with pytest.raises(ValueError, match="motor"):
ObservationUnitRef("motor", _unit("m", "motor_test"))
def test_exact_expected_vs_actual_match_is_supported():
refs = (_ref("slot:a", "a"), _ref("slot:b", "b"))
expected = build_expected_observation_frame(
monotonic_tick=2,
source_clock="fixture",
unit_refs=refs,
)
actual = build_observation_frame(
monotonic_tick=2,
source_clock="fixture",
units=[ref.unit for ref in refs],
)
run = compare_expected_to_observation(expected, actual, actual_refs=refs)
assert run.verdict == "SUPPORTED"
assert run.residual.matched == ("slot:a", "slot:b")
assert run.residual.missing == ()
assert run.residual.unexpected == ()
assert run.residual.changed == ()
def test_missing_unexpected_and_changed_slots_are_falsified():
expected_refs = (
_ref("slot:a", "a"),
_ref("slot:b", "b"),
_ref("slot:c", "c"),
)
actual_refs = (
_ref("slot:a", "a"),
_ref("slot:b", "b2"),
_ref("slot:d", "d"),
)
expected = build_expected_observation_frame(
monotonic_tick=3,
source_clock="fixture",
unit_refs=expected_refs,
)
actual = build_observation_frame(
monotonic_tick=3,
source_clock="fixture",
units=[ref.unit for ref in actual_refs],
)
run = compare_expected_to_observation(expected, actual, actual_refs=actual_refs)
assert run.verdict == "FALSIFIED"
assert run.residual.matched == ("slot:a",)
assert run.residual.missing == ("slot:c",)
assert run.residual.unexpected == ("slot:d",)
assert len(run.residual.changed) == 1
assert run.residual.changed[0].slot_id == "slot:b"
def test_run_trace_is_hash_only():
refs = (_ref("slot:a", "a"),)
expected = build_expected_observation_frame(
monotonic_tick=4,
source_clock="fixture",
unit_refs=refs,
)
actual = build_observation_frame(
monotonic_tick=4,
source_clock="fixture",
units=[ref.unit for ref in refs],
)
payload = compare_expected_to_observation(expected, actual, actual_refs=refs).as_dict()
assert "versor" not in str(payload)
assert "pixels" not in str(payload)
assert "command" not in str(payload)
def test_comparator_does_not_import_generate_or_call_decode(monkeypatch):
refs = (_ref("slot:a", "a"),)
expected = build_expected_observation_frame(
monotonic_tick=5,
source_clock="fixture",
unit_refs=refs,
)
actual = build_observation_frame(
monotonic_tick=5,
source_clock="fixture",
units=[ref.unit for ref in refs],
)
original_import = builtins.__import__
def guarded_import(name, *args, **kwargs):
if name.startswith("generate"):
raise AssertionError("falsification comparator must not import generate")
return original_import(name, *args, **kwargs)
monkeypatch.setattr(builtins, "__import__", guarded_import)
from sensorium.registry import ModalityRegistry
monkeypatch.setattr(
ModalityRegistry,
"decode",
lambda *args, **kwargs: (_ for _ in ()).throw(AssertionError("decode called")),
)
run = compare_expected_to_observation(expected, actual, actual_refs=refs)
assert run.verdict == "SUPPORTED"

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from __future__ import annotations
import json
from core.cli import main
from evals.environment_falsification import build_environment_falsification_report
def test_environment_falsification_report_passes_expected_fixtures():
report = build_environment_falsification_report()
assert report["lane"] == "environment-falsification"
assert report["failed"] == 0
assert report["expected_report_hash_ok"] is True
assert {case["actual_verdict"] for case in report["cases"]} == {"SUPPORTED", "FALSIFIED"}
def test_core_eval_environment_falsification_json(capsys):
assert main(["eval", "environment-falsification", "--json"]) == 0
out = capsys.readouterr().out
report = json.loads(out)
assert report["lane"] == "environment-falsification"
assert report["failed"] == 0
def test_core_eval_environment_falsification_text_summary(capsys):
assert main(["eval", "environment-falsification"]) == 0
out = capsys.readouterr().out
assert "lane : environment-falsification" in out
assert "failed : 0" in out