feat(perception): add integrated TGS graph shadow gate
This commit is contained in:
DCCONSTRUCTIONS
@@ -3,6 +3,7 @@ from __future__ import annotations
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import importlib.util
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import time
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from pathlib import Path
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from threading import Thread
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from unittest.mock import patch
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from k1link.perception.detector import DetectorFrameTiming
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@@ -157,3 +158,33 @@ def test_cyclic_gc_policy_collects_outside_hot_loop_and_restores_state() -> None
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"pre_collected": 3,
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"post_collected": 0,
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}
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def test_shared_start_barrier_publishes_readiness_and_waits_for_release(
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tmp_path: Path,
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) -> None:
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ready = tmp_path / "graph.ready"
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start = tmp_path / "start.signal"
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completed: list[bool] = []
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thread = Thread(
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target=lambda: (
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RUNNER.wait_for_shared_start(
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ready_file=ready,
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start_file=start,
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timeout_seconds=1.0,
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),
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completed.append(True),
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)
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)
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thread.start()
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deadline = time.monotonic() + 1.0
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while not ready.exists() and time.monotonic() < deadline:
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time.sleep(0.005)
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assert ready.read_text(encoding="utf-8") == "ready\n"
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assert completed == []
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start.write_text("start\n", encoding="utf-8")
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thread.join(timeout=1.0)
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assert completed == [True]
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@@ -0,0 +1,208 @@
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from __future__ import annotations
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import importlib.util
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import json
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import tarfile
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from pathlib import Path
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REPOSITORY_ROOT = Path(__file__).resolve().parents[1]
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EVIDENCE_PATH = (
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REPOSITORY_ROOT
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/ "experiments/perception/worker/m49_t3_travel/build_tgs_integrated_graph_evidence.py"
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)
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ARTIFACT_PATH = REPOSITORY_ROOT / "scripts/build_m49_tgs_integrated_graph_worker_artifact.py"
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def load_module(name: str, path: Path):
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spec = importlib.util.spec_from_file_location(name, path)
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assert spec is not None and spec.loader is not None
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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return module
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EVIDENCE = load_module("m49_tgs_integrated_evidence", EVIDENCE_PATH)
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ARTIFACT = load_module("m49_tgs_integrated_artifact", ARTIFACT_PATH)
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def test_integrated_gate_joins_all_frames_and_preserves_false_authority(tmp_path: Path) -> None:
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profile_path = tmp_path / "profile.json"
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profile_path.write_text(
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json.dumps(
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{
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"schema_version": EVIDENCE.PROFILE_SCHEMA,
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"profile_id": "test",
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"source": {
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"source_id": "RAVNOVES00",
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"source_pack_sha256": "a" * 64,
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"requested_source_rate_hz": 12.0,
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},
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"stages": {
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"reference_graph": {
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"graph_config_sha256": "b" * 64,
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"detector_profile_sha256": "z" * 64,
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},
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"tgs": {
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"profile_sha256": "c" * 64,
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"linked_accepted_result_id": "m49-tgs-full-shadow-" + "d" * 64,
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},
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},
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"acceptance": {
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"minimum_delivery_ratio": 1.0,
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"reference_world_state_fps": 11.79902,
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"maximum_world_state_fps_regression_fraction": 0.05,
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"minimum_effective_world_state_fps": 11.209069,
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"maximum_world_state_completion_p95_ms": 125.0,
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"candidate_stage_p95_ms_max": 25.0,
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"candidate_stage_p99_ms_max": 50.0,
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"combined_output_age_p99_ms_max": 125.0,
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"capacity_drop_count_max": 0,
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},
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"authority": {
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"visual_quality_accepted": False,
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"traversability_accepted": False,
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"physical_free_space_accepted": False,
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"commands_enabled": False,
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"actuation_allowed": False,
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"navigation_or_safety_accepted": False,
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"production_accepted": False,
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},
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}
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),
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encoding="utf-8",
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)
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graph_result = tmp_path / "graph-result.json"
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graph_result.write_text(
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json.dumps(
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{
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"schema_version": EVIDENCE.GRAPH_SCHEMA,
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"execution": {
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"admitted_frames": EVIDENCE.FRAME_COUNT,
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"delivered_world_states": EVIDENCE.FRAME_COUNT,
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"effective_world_state_fps": 11.75,
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"delivery_ratio": 1.0,
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"terminal_outcomes": {"delivered": EVIDENCE.FRAME_COUNT},
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"requested_source_rate_hz": 12.0,
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},
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"identity": {
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"inputs": {
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"graph_config": "b" * 64,
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"detector_profile": "z" * 64,
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}
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},
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"metrics": {
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"world_state_completion_age_ms": {"p95": 40.0},
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"gpu": {"sample_count": 2},
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},
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"evidence_integrity_gate_passed": True,
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}
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),
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encoding="utf-8",
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)
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graph_frames = tmp_path / "graph-frames.jsonl"
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graph_frames.write_text(
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"".join(
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json.dumps(
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{
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"source_envelope": {"sequence": index},
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"completion_age_ns": 40_000_000,
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}
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)
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+ "\n"
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for index in range(EVIDENCE.FRAME_COUNT)
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),
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encoding="utf-8",
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)
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tgs_result = tmp_path / "tgs-result.json"
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tgs_result.write_text(
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json.dumps(
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{
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"schema_version": EVIDENCE.TGS_SCHEMA,
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"status": "passed",
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"config_sha256": "c" * 64,
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"timeline": {
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"frame_count": EVIDENCE.FRAME_COUNT,
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"available_lidar_frame_count": 3928,
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},
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"performance": {
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"candidate_tgs_ms": {"p95": 2.0, "p99": 3.0},
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"completion_age_ms": {"p99": 5.0},
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"capacity_drop_count": 0,
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},
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}
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),
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encoding="utf-8",
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)
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tgs_timing = tmp_path / "tgs-timing.tsv"
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tgs_timing.write_text(
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"timeline_frame_index\tcompletion_age_ms\n"
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+ "".join(f"{index}\t5.0\n" for index in range(EVIDENCE.FRAME_COUNT)),
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encoding="utf-8",
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)
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telemetry = tmp_path / "telemetry.jsonl"
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telemetry.write_text(
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"".join(
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json.dumps(
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{
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"role": role,
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"cpu_percent": "10.0%",
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"memory_usage": "1GiB / 64GiB",
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"memory_percent": "1.56%",
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}
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)
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+ "\n"
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for role in ("graph", "tgs", "triton")
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),
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encoding="utf-8",
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)
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output = tmp_path / "result.json"
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result = EVIDENCE.build(
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profile_path=profile_path,
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graph_result_path=graph_result,
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graph_frames_path=graph_frames,
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tgs_result_path=tgs_result,
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tgs_timing_path=tgs_timing,
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telemetry_path=telemetry,
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output_path=output,
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release_sha256="e" * 64,
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)
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assert result["status"] == "passed"
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assert result["source"]["joined_frame_count"] == EVIDENCE.FRAME_COUNT
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assert result["performance"]["combined_output_age_ms"]["p99"] == 40.0
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assert result["checks"]["authority_remains_false"] is True
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assert result["production_accepted"] is False
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def test_worker_artifact_is_deterministic_and_excludes_gauss(monkeypatch, tmp_path: Path) -> None:
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def fake_wheel(_source_root: Path, output: Path) -> Path:
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output.mkdir(parents=True, exist_ok=True)
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wheel = output / ARTIFACT.WHEEL_NAME
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wheel.write_bytes(b"clean committed wheel\n")
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return wheel
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monkeypatch.setattr(ARTIFACT, "build_wheel", fake_wheel)
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revision = "f" * 40
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first = ARTIFACT.build_artifact(
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"mission-core-m49-integrated-unit-001",
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tmp_path / "first",
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revision=revision,
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source_root=REPOSITORY_ROOT,
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)
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second = ARTIFACT.build_artifact(
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"mission-core-m49-integrated-unit-001",
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tmp_path / "second",
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revision=revision,
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source_root=REPOSITORY_ROOT,
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)
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assert Path(first["artifact"]).read_bytes() == Path(second["artifact"]).read_bytes()
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with tarfile.open(first["artifact"], "r:gz") as archive:
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names = set(archive.getnames())
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release_stream = archive.extractfile("payload/release.json")
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assert release_stream is not None
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release = json.loads(release_stream.read())
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assert not any("gauss" in name.lower() or "playcanvas" in name.lower() for name in names)
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assert release["scope"]["gauss_or_playcanvas_action"] == "none"
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assert all(value is False for value in release["authority"].values())
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