perf(perception): split safety and vegetation rates

This commit is contained in:
DCCONSTRUCTIONS
2026-08-28 12:59:34 +03:00
parent e1c3e7e90a
commit 7a3b0b84d0
7 changed files with 292 additions and 56 deletions
@@ -0,0 +1,80 @@
{
"schema_version": "missioncore.lab-v1-vegetation-integrated-shadow-profile/v2",
"profile_id": "lab-v1-ravnoves00-ddrnet-m49-integrated-multirate-shadow/v2",
"source": {
"source_id": "RAVNOVES00",
"expected_timeline_frames": 4489,
"requested_source_rate_hz": 12.0,
"shared_start_barrier": true,
"ground_truth_available": false
},
"stages": {
"m49_graph_tgs": {
"profile": "m49-tgs-integrated-graph-shadow-v1.json",
"profile_sha256": "b61e018b2d04eec58802e2d4186ce7a3dd3a15b254db106b57b609e903eeef80",
"candidate": "frozen-native-rf-detr-plus-cpu-tgs",
"parameters_unchanged": true,
"timeline_rate_hz": 12.0
},
"vegetation": {
"candidate_id": "ddrnet_39-goose-fine-64",
"candidate_key": "ddrnet",
"checkpoint_sha256": "b99c2838051bcd7b092fd3970aa62a77d5c0bbb809c9b9afb2ff4b0ebdaa4ee6",
"config_sha256": "96a427a8baae387b827ec9c0bf7ca42e3fb9114b8fa9a8671bbc9d10877670b9",
"policy_sha256": "b75c4ac841d7b4bcc57f7a9c8417ca2317d8ecfa499e72a9af8a8591a2ec0d35",
"provider_map_sha256": "f2b69046b6a740fd9532d2d88e7fabae7c20fb662f783c9502adc9026406f352",
"container_image": "ndc/mission-core-lab-v1-goose:sg3.2.0-cu117-v1",
"container_image_id": "sha256:591cb382c099eeb05e7ec16e2371e0b2da54d2bb5c49ec0f4ac88dbf72b0f0cd",
"timeline_rate_hz": 12.0,
"inference_rate_hz": 6.0,
"inference_stride": 2,
"held_evidence_fail_closed": true,
"semantic_output_persisted": false,
"one_heavy_vegetation_candidate_at_a_time": true
}
},
"acceptance": {
"minimum_graph_world_state_fps": 11.209069,
"minimum_vegetation_timeline_fps": 11.209069,
"minimum_vegetation_inference_fps": 5.604534,
"maximum_vegetation_inference_completion_p95_ms": 125.0,
"maximum_semantic_evidence_source_age_ms": 125.0,
"maximum_combined_output_age_p99_ms": 125.0,
"capacity_drop_count_max": 0,
"unaccounted_frame_count_max": 0
},
"telemetry": {
"sample_interval_seconds": 1.0,
"required_roles": [
"graph",
"triton",
"tgs",
"vegetation"
]
},
"invariants": {
"raw_fisheye_immutable": true,
"reference_graph_parameters_unchanged": true,
"tgs_parameters_unchanged": true,
"ddrnet_parameters_unchanged": true,
"safety_layers_remain_12hz": true,
"held_semantic_evidence_is_advisory_only": true,
"vegetation_source_buffer_bounded": true,
"vegetation_full_route_rgb_prefetch_allowed": false,
"ppliteseg_concurrent_run_allowed": false,
"camera_semantics_can_clear_rigid_geometry": false,
"canonical_triton_mutation_allowed": false,
"runtime_shared_source_frame_target": true,
"gauss_or_playcanvas_in_scope": false
},
"authority": {
"visual_quality_accepted": false,
"route_truth_available": false,
"traversability_accepted": false,
"physical_free_space_accepted": false,
"commands_enabled": false,
"actuation_allowed": false,
"navigation_or_safety_accepted": false,
"production_accepted": false
}
}
@@ -148,12 +148,12 @@ foreach ($directory in @("bin", "control", "graph", "tgs", "vegetation")) {
$releaseDocument = Get-Content -LiteralPath (Join-Path $payload "release.json") -Raw | ConvertFrom-Json
$expectedReleaseSchema = if ($VegetationLoadGate) {
"missioncore.lab-v1-vegetation-integrated-worker-release/v1"
"missioncore.lab-v1-vegetation-integrated-worker-release/v2"
} else {
"missioncore.m49-tgs-integrated-graph-worker-release/v1"
}
$expectedTransition = if ($VegetationLoadGate) {
"lab-v1-vegetation-m49-integrated-shadow/v1"
"lab-v1-vegetation-m49-integrated-multirate-shadow/v2"
} else {
"m49-tgs-native-risk-integrated-shadow/v1"
}
@@ -380,7 +380,7 @@ try {
& docker create --name $tgsName --network none --cpus 16 --memory 24g `
--read-only --security-opt "no-new-privileges:true" --cap-drop ALL `
--pids-limit 256 --tmpfs "/tmp:rw,noexec,nosuid,size=1g" `
--pids-limit 256 --tmpfs "/tmp:rw,noexec,nosuid,size=2g" `
-e ("M49_SOURCE_RATE_HZ={0}" -f $rate) `
--entrypoint /bin/bash `
--volume ($dockerRelease + ":/release:ro") `
@@ -412,8 +412,11 @@ try {
--video-sha256 $videoSha256 `
--runtime-video-cache /tmp/vegetation-right.mp4 `
--source-rate-hz $rate `
--minimum-effective-fps 11.209069 `
--maximum-completion-p95-ms 125.0 `
--inference-stride 2 `
--minimum-effective-timeline-fps 11.209069 `
--minimum-effective-inference-fps 5.604534 `
--maximum-inference-completion-p95-ms 125.0 `
--maximum-evidence-source-age-ms 125.0 `
--shared-start-ready-file /shared/control/vegetation.ready `
--shared-start-file /shared/control/start.signal `
--frame-ledger /shared/vegetation/frames.jsonl `
@@ -559,7 +562,7 @@ try {
--volume ($dockerRelease + ":/release:ro") `
--volume ($dockerRun + ":/shared:rw") `
$ParityImageTag /release/build_vegetation_integrated_graph_evidence.py `
--profile /release/lab-v1-vegetation-integrated-shadow-v1.json `
--profile /release/lab-v1-vegetation-integrated-multirate-shadow-v2.json `
--m49-result /shared/m49-result.json `
--graph-frames /shared/graph/frames.jsonl `
--tgs-timing /shared/tgs/tgs-full-timing.tsv `
@@ -588,7 +591,7 @@ if (-not (Test-Path -LiteralPath $resultPath -PathType Leaf)) {
$result = Get-Content -LiteralPath $resultPath -Raw | ConvertFrom-Json
$summary = [ordered]@{
schema_version = if ($VegetationLoadGate) {
"missioncore.lab-v1-vegetation-integrated-worker-summary/v1"
"missioncore.lab-v1-vegetation-integrated-worker-summary/v2"
} else {
"missioncore.m49-tgs-integrated-graph-worker-summary/v1"
}
@@ -28,8 +28,8 @@ from run_goose_vegetation_benchmark import (
validate_contracts,
)
SCHEMA = "missioncore.lab-v1-vegetation-integrated-load/v1"
FRAME_SCHEMA = "missioncore.lab-v1-vegetation-integrated-frame/v1"
SCHEMA = "missioncore.lab-v1-vegetation-integrated-load/v2"
FRAME_SCHEMA = "missioncore.lab-v1-vegetation-integrated-frame/v2"
FRAME_COUNT = 4_489
AUTHORITY = {
"ground_truth": False,
@@ -57,8 +57,11 @@ def parse_args() -> argparse.Namespace:
parser.add_argument("--video-sha256", required=True)
parser.add_argument("--runtime-video-cache", type=Path, required=True)
parser.add_argument("--source-rate-hz", type=float, required=True)
parser.add_argument("--minimum-effective-fps", type=float, required=True)
parser.add_argument("--maximum-completion-p95-ms", type=float, required=True)
parser.add_argument("--inference-stride", type=int, required=True)
parser.add_argument("--minimum-effective-timeline-fps", type=float, required=True)
parser.add_argument("--minimum-effective-inference-fps", type=float, required=True)
parser.add_argument("--maximum-inference-completion-p95-ms", type=float, required=True)
parser.add_argument("--maximum-evidence-source-age-ms", type=float, required=True)
parser.add_argument("--shared-start-ready-file", type=Path, required=True)
parser.add_argument("--shared-start-file", type=Path, required=True)
parser.add_argument("--shared-start-timeout-seconds", type=float, default=600.0)
@@ -139,12 +142,16 @@ def run() -> int:
args = parse_args()
if not torch.cuda.is_available():
raise IntegratedLoadError("CUDA is required for Worker 006 qualification")
if (
not math.isfinite(args.source_rate_hz)
or args.source_rate_hz <= 0
or args.minimum_effective_fps <= 0
or args.maximum_completion_p95_ms <= 0
or args.shared_start_timeout_seconds <= 0
positive_finite_values = (
args.source_rate_hz,
args.minimum_effective_timeline_fps,
args.minimum_effective_inference_fps,
args.maximum_inference_completion_p95_ms,
args.maximum_evidence_source_age_ms,
args.shared_start_timeout_seconds,
)
if args.inference_stride <= 0 or any(
not math.isfinite(value) or value <= 0 for value in positive_finite_values
):
raise IntegratedLoadError("integrated-load thresholds must be positive and finite")
validate_sha256(args.release_sha256, "release")
@@ -192,9 +199,13 @@ def run() -> int:
start_ns = time.monotonic_ns()
started_utc_ns = time.time_ns()
completion_ages_ms: list[float] = []
inference_completion_ages_ms: list[float] = []
evidence_source_ages_ms: list[float] = []
stage_latencies_ms: list[float] = []
inference_latencies_ms: list[float] = []
late_deadline_count = 0
inference_frame_count = 0
last_inference_sequence = -1
args.frame_ledger.parent.mkdir(parents=True, exist_ok=True)
with args.frame_ledger.open("x", encoding="utf-8") as ledger:
for sequence in range(FRAME_COUNT):
@@ -204,14 +215,30 @@ def run() -> int:
time.sleep(remaining_ns / 1_000_000_000.0)
admitted_ns = time.monotonic_ns()
source = decode_source(source_capture, expected_size)
tensor, _ = preprocess(source)
_, inference_ms = infer(model, tensor)
inference_executed = sequence % args.inference_stride == 0
inference_ms: float | None = None
if inference_executed:
tensor, _ = preprocess(source)
_, inference_ms = infer(model, tensor)
last_inference_sequence = sequence
inference_frame_count += 1
if last_inference_sequence < 0:
raise IntegratedLoadError("semantic evidence is unavailable for the timeline")
completed_ns = time.monotonic_ns()
completion_age_ms = (completed_ns - scheduled_ns) / 1_000_000.0
stage_ms = (completed_ns - admitted_ns) / 1_000_000.0
semantic_source_scheduled_ns = start_ns + round(
last_inference_sequence * interval_ns
)
evidence_source_age_ms = (
completed_ns - semantic_source_scheduled_ns
) / 1_000_000.0
completion_ages_ms.append(completion_age_ms)
evidence_source_ages_ms.append(evidence_source_age_ms)
stage_latencies_ms.append(stage_ms)
inference_latencies_ms.append(inference_ms)
if inference_ms is not None:
inference_latencies_ms.append(inference_ms)
inference_completion_ages_ms.append(completion_age_ms)
if sequence + 1 < FRAME_COUNT and completed_ns > start_ns + round(
(sequence + 1) * interval_ns
):
@@ -225,7 +252,10 @@ def run() -> int:
"completed_monotonic_ns": completed_ns,
"completion_age_ms": round(completion_age_ms, 6),
"stage_ms": round(stage_ms, 6),
"inference_ms": round(inference_ms, 6),
"inference_executed": inference_executed,
"inference_ms": round(inference_ms, 6) if inference_ms is not None else None,
"semantic_source_sequence": last_inference_sequence,
"semantic_evidence_source_age_ms": round(evidence_source_age_ms, 6),
}
ledger.write(json.dumps(row, sort_keys=True, separators=(",", ":")) + "\n")
if sequence % 64 == 0:
@@ -237,13 +267,23 @@ def run() -> int:
completed_ns = time.monotonic_ns()
wall_seconds = (completed_ns - start_ns) / 1_000_000_000.0
effective_fps = FRAME_COUNT / wall_seconds
effective_timeline_fps = FRAME_COUNT / wall_seconds
effective_inference_fps = inference_frame_count / wall_seconds
completion = distribution(completion_ages_ms)
inference_completion = distribution(inference_completion_ages_ms)
evidence_source_age = distribution(evidence_source_ages_ms)
expected_inference_frames = (FRAME_COUNT + args.inference_stride - 1) // args.inference_stride
checks = {
"all_frames_accounted": len(completion_ages_ms) == FRAME_COUNT,
"minimum_effective_fps": effective_fps >= args.minimum_effective_fps,
"maximum_completion_p95_ms": completion["p95"]
<= args.maximum_completion_p95_ms,
"exact_multirate_schedule": inference_frame_count == expected_inference_frames,
"minimum_effective_timeline_fps": effective_timeline_fps
>= args.minimum_effective_timeline_fps,
"minimum_effective_inference_fps": effective_inference_fps
>= args.minimum_effective_inference_fps,
"maximum_inference_completion_p95_ms": inference_completion["p95"]
<= args.maximum_inference_completion_p95_ms,
"maximum_evidence_source_age_ms": evidence_source_age["maximum"]
<= args.maximum_evidence_source_age_ms,
"zero_capacity_drops": len(completion_ages_ms) == FRAME_COUNT,
"authority_remains_false": all(value is False for value in AUTHORITY.values()),
}
@@ -266,10 +306,15 @@ def run() -> int:
"checkpoint_sha256": checkpoint_sha256,
},
"execution": {
"run_mode": "source-paced-integrated-shadow/v1",
"run_mode": "source-paced-multirate-integrated-shadow/v2",
"started_utc_ns": started_utc_ns,
"wall_seconds": round(wall_seconds, 6),
"effective_fps": round(effective_fps, 6),
"effective_fps": round(effective_timeline_fps, 6),
"effective_timeline_fps": round(effective_timeline_fps, 6),
"effective_inference_fps": round(effective_inference_fps, 6),
"inference_stride": args.inference_stride,
"inference_frame_count": inference_frame_count,
"held_evidence_frame_count": FRAME_COUNT - inference_frame_count,
"frame_count": FRAME_COUNT,
"capacity_drop_count": 0,
"deadline_miss_count": late_deadline_count,
@@ -292,6 +337,8 @@ def run() -> int:
"prewarm_latency_ms_first": round(warmup_latencies_ms[0], 6),
"prewarm_latency_ms_last": round(warmup_latencies_ms[-1], 6),
"completion_age_ms": completion,
"inference_completion_age_ms": inference_completion,
"semantic_evidence_source_age_ms": evidence_source_age,
"stage_ms": distribution(stage_latencies_ms),
"inference_ms": distribution(inference_latencies_ms),
},
@@ -311,8 +358,12 @@ def run() -> int:
"runner_sha256": sha256(Path(__file__)),
},
"predeclared_thresholds": {
"minimum_effective_fps": args.minimum_effective_fps,
"maximum_completion_p95_ms": args.maximum_completion_p95_ms,
"minimum_effective_timeline_fps": args.minimum_effective_timeline_fps,
"minimum_effective_inference_fps": args.minimum_effective_inference_fps,
"maximum_inference_completion_p95_ms": (
args.maximum_inference_completion_p95_ms
),
"maximum_evidence_source_age_ms": args.maximum_evidence_source_age_ms,
"capacity_drop_count_max": 0,
},
"checks": checks,
@@ -15,10 +15,10 @@ from typing import Any
import numpy as np
PROFILE_SCHEMA = "missioncore.lab-v1-vegetation-integrated-shadow-profile/v1"
PROFILE_SCHEMA = "missioncore.lab-v1-vegetation-integrated-shadow-profile/v2"
M49_SCHEMA = "missioncore.m49-tgs-integrated-graph-shadow-result/v1"
VEGETATION_SCHEMA = "missioncore.lab-v1-vegetation-integrated-load/v1"
RESULT_SCHEMA = "missioncore.lab-v1-vegetation-integrated-shadow-result/v1"
VEGETATION_SCHEMA = "missioncore.lab-v1-vegetation-integrated-load/v2"
RESULT_SCHEMA = "missioncore.lab-v1-vegetation-integrated-shadow-result/v2"
FRAME_COUNT = 4_489
@@ -92,22 +92,51 @@ def tgs_completion_ages(path: Path) -> list[float]:
return values
def vegetation_completion_ages(path: Path) -> list[float]:
values: list[float] = []
def vegetation_frame_metrics(
path: Path, *, inference_stride: int, source_rate_hz: float
) -> dict[str, object]:
completion_ages: list[float] = []
evidence_source_ages: list[float] = []
inference_count = 0
with path.open("r", encoding="utf-8") as stream:
for expected, line in enumerate(stream):
row = json.loads(line)
if row.get("schema_version") != "missioncore.lab-v1-vegetation-integrated-frame/v1":
if row.get("schema_version") != "missioncore.lab-v1-vegetation-integrated-frame/v2":
raise VegetationIntegratedError("vegetation frame schema changed")
if row.get("sequence") != expected:
raise VegetationIntegratedError("vegetation frame sequence changed")
age = row.get("completion_age_ms")
if not isinstance(age, (int, float)) or not math.isfinite(age) or age < 0:
raise VegetationIntegratedError("vegetation completion age is invalid")
values.append(float(age))
if len(values) != FRAME_COUNT:
inference_executed = row.get("inference_executed")
expected_inference = expected % inference_stride == 0
if inference_executed is not expected_inference:
raise VegetationIntegratedError("vegetation inference schedule changed")
expected_source = expected - (expected % inference_stride)
if row.get("semantic_source_sequence") != expected_source:
raise VegetationIntegratedError("vegetation evidence source changed")
evidence_age = row.get("semantic_evidence_source_age_ms")
expected_evidence_age = float(age) + (
(expected - expected_source) * 1000.0 / source_rate_hz
)
if (
not isinstance(evidence_age, (int, float))
or not math.isfinite(evidence_age)
or evidence_age < 0
or abs(float(evidence_age) - expected_evidence_age) > 0.001
):
raise VegetationIntegratedError("vegetation evidence source age changed")
completion_ages.append(float(age))
evidence_source_ages.append(float(evidence_age))
inference_count += int(expected_inference)
if len(completion_ages) != FRAME_COUNT:
raise VegetationIntegratedError("vegetation frame ledger is incomplete")
return values
return {
"completion_ages": completion_ages,
"evidence_source_ages": evidence_source_ages,
"inference_count": inference_count,
"held_count": FRAME_COUNT - inference_count,
}
_SIZE = re.compile(r"^\s*([0-9.]+)\s*([kmgt]?i?b)\s*$", re.IGNORECASE)
@@ -200,9 +229,17 @@ def build(
if vegetation.get("schema_version") != VEGETATION_SCHEMA:
raise VegetationIntegratedError("vegetation load result schema changed")
source_rate_hz = float(profile["source"]["requested_source_rate_hz"])
inference_stride = int(profile["stages"]["vegetation"]["inference_stride"])
graph_ages = graph_completion_ages(graph_frames_path)
tgs_ages = tgs_completion_ages(tgs_timing_path)
vegetation_ages = vegetation_completion_ages(vegetation_frames_path)
vegetation_frames = vegetation_frame_metrics(
vegetation_frames_path,
inference_stride=inference_stride,
source_rate_hz=source_rate_hz,
)
vegetation_ages = vegetation_frames["completion_ages"]
assert isinstance(vegetation_ages, list)
combined_ages = [
max(graph, tgs, semantic)
for graph, tgs, semantic in zip(
@@ -240,6 +277,14 @@ def build(
vegetation.get("source", {}).get("requested_source_rate_hz")
== profile["source"]["requested_source_rate_hz"]
),
"vegetation_load_gate_passed": vegetation.get("integrated_load_gate_passed") is True,
"vegetation_multirate_schedule_frozen": (
vegetation_execution.get("inference_stride") == inference_stride
and vegetation_execution.get("inference_frame_count")
== vegetation_frames["inference_count"]
and vegetation_execution.get("held_evidence_frame_count")
== vegetation_frames["held_count"]
),
"exact_three_layer_sequence_join": len(combined_ages) == FRAME_COUNT,
"all_graph_frames_delivered": (
m49_accounting.get("graph_admitted") == FRAME_COUNT
@@ -253,12 +298,24 @@ def build(
m49_performance.get("effective_world_state_fps", 0.0)
)
>= float(acceptance["minimum_graph_world_state_fps"]),
"minimum_vegetation_fps": float(vegetation_execution.get("effective_fps", 0.0))
>= float(acceptance["minimum_vegetation_fps"]),
"maximum_vegetation_completion_p95_ms": float(
vegetation_timing.get("completion_age_ms", {}).get("p95", math.inf)
"minimum_vegetation_timeline_fps": float(
vegetation_execution.get("effective_timeline_fps", 0.0)
)
<= float(acceptance["maximum_vegetation_completion_p95_ms"]),
>= float(acceptance["minimum_vegetation_timeline_fps"]),
"minimum_vegetation_inference_fps": float(
vegetation_execution.get("effective_inference_fps", 0.0)
)
>= float(acceptance["minimum_vegetation_inference_fps"]),
"maximum_vegetation_inference_completion_p95_ms": float(
vegetation_timing.get("inference_completion_age_ms", {}).get(
"p95", math.inf
)
)
<= float(acceptance["maximum_vegetation_inference_completion_p95_ms"]),
"maximum_semantic_evidence_source_age_ms": max(
vegetation_frames["evidence_source_ages"]
)
<= float(acceptance["maximum_semantic_evidence_source_age_ms"]),
"maximum_combined_output_age_p99_ms": combined["p99"]
<= float(acceptance["maximum_combined_output_age_p99_ms"]),
"zero_capacity_drops": (
@@ -304,8 +361,19 @@ def build(
"performance": {
"graph_tgs": m49_performance,
"vegetation": {
"effective_fps": vegetation_execution.get("effective_fps"),
"effective_timeline_fps": vegetation_execution.get(
"effective_timeline_fps"
),
"effective_inference_fps": vegetation_execution.get(
"effective_inference_fps"
),
"completion_age_ms": vegetation_timing.get("completion_age_ms"),
"inference_completion_age_ms": vegetation_timing.get(
"inference_completion_age_ms"
),
"semantic_evidence_source_age_ms": distribution(
vegetation_frames["evidence_source_ages"]
),
"stage_ms": vegetation_timing.get("stage_ms"),
"inference_ms": vegetation_timing.get("inference_ms"),
"resource": vegetation.get("resource"),
@@ -317,6 +385,8 @@ def build(
"graph_frames": m49_accounting.get("graph_delivered"),
"tgs_frames": m49_accounting.get("tgs_timeline_frames"),
"vegetation_frames": vegetation_execution.get("frame_count"),
"vegetation_inference_frames": vegetation_frames["inference_count"],
"vegetation_held_evidence_frames": vegetation_frames["held_count"],
"capacity_drop_count": int(m49_accounting.get("tgs_capacity_drops", 0))
+ int(vegetation_execution.get("capacity_drop_count", 0)),
},
@@ -5,6 +5,9 @@ readonly BINARY=/shared/bin/run_tgs_full_shadow
readonly INPUT_ROOT=/shared/tgs/inputs
readonly OUTPUT_ROOT=/shared/tgs/outputs/causal_rolling_1s
readonly TIMING_PATH=/shared/tgs/tgs-full-timing.tsv
readonly RUNTIME_ROOT=/tmp/m49-tgs-runtime
readonly RUNTIME_OUTPUT_ROOT=${RUNTIME_ROOT}/outputs
readonly RUNTIME_TIMING_PATH=${RUNTIME_ROOT}/tgs-full-timing.tsv
readonly READY_FILE=/shared/control/tgs.ready
readonly START_FILE=/shared/control/start.signal
readonly SOURCE_RATE_HZ=${M49_SOURCE_RATE_HZ:-12.0}
@@ -15,12 +18,20 @@ test -f "${INPUT_ROOT}/schedule.tsv"
test ! -e /shared/tgs/outputs
test ! -e "${TIMING_PATH}"
test ! -e "${READY_FILE}"
mkdir -p "${OUTPUT_ROOT}"
exec /usr/bin/time -v "${BINARY}" \
test ! -e "${RUNTIME_ROOT}"
mkdir -p "${RUNTIME_OUTPUT_ROOT}"
/usr/bin/time -v "${BINARY}" \
"${INPUT_ROOT}/profiles/causal_rolling_1s" \
"${INPUT_ROOT}/schedule.tsv" \
"${OUTPUT_ROOT}" \
"${TIMING_PATH}" \
"${RUNTIME_OUTPUT_ROOT}" \
"${RUNTIME_TIMING_PATH}" \
"${SOURCE_RATE_HZ}" \
"${READY_FILE}" \
"${START_FILE}"
test -f "${RUNTIME_TIMING_PATH}"
mkdir -p "${OUTPUT_ROOT}"
copy_started=$(date +%s%N)
cp -R "${RUNTIME_OUTPUT_ROOT}/." "${OUTPUT_ROOT}/"
cp "${RUNTIME_TIMING_PATH}" "${TIMING_PATH}"
copy_completed=$(date +%s%N)
echo "[TGS-FULL] evidence_copy_ms=$(((copy_completed - copy_started) / 1000000))"
@@ -46,7 +46,7 @@ SOURCES = M49_SOURCES + (
Path("config/perception/lab-v1-goose-vegetation-benchmark-v1.json"),
Path("config/perception/lab-v1-vegetation-mission-policy-v1.json"),
Path("config/perception/lab-v1-vegetation-provider-label-map-v1.json"),
Path("config/perception/lab-v1-vegetation-integrated-shadow-v1.json"),
Path("config/perception/lab-v1-vegetation-integrated-multirate-shadow-v2.json"),
)
@@ -85,9 +85,9 @@ def build_artifact(
wheel_destination.write_bytes(wheel.read_bytes())
copied.append(wheel_destination)
release = {
"schema_version": "missioncore.lab-v1-vegetation-integrated-worker-release/v1",
"schema_version": "missioncore.lab-v1-vegetation-integrated-worker-release/v2",
"patch_id": patch_id,
"transition": "lab-v1-vegetation-m49-integrated-shadow/v1",
"transition": "lab-v1-vegetation-m49-integrated-multirate-shadow/v2",
"code_revision": selected_revision,
"worker_id": "worker-006",
"source_pack_sha256": (
@@ -98,6 +98,8 @@ def build_artifact(
),
"expected_frames": 4489,
"requested_source_rate_hz": 12.0,
"semantic_inference_rate_hz": 6.0,
"semantic_inference_stride": 2,
"native_engine_sha256": (
"b8a40b3580edff001ec9680de68707242294ff590ab296000fae371f1083f695"
),
@@ -54,12 +54,15 @@ def test_three_layer_gate_joins_exact_frames_and_preserves_false_authority(
"config_sha256": "c" * 64,
"policy_sha256": "d" * 64,
"provider_map_sha256": "e" * 64,
"inference_stride": 2,
},
},
"acceptance": {
"minimum_graph_world_state_fps": 11.2,
"minimum_vegetation_fps": 11.2,
"maximum_vegetation_completion_p95_ms": 125.0,
"minimum_vegetation_timeline_fps": 11.2,
"minimum_vegetation_inference_fps": 5.6,
"maximum_vegetation_inference_completion_p95_ms": 125.0,
"maximum_semantic_evidence_source_age_ms": 125.0,
"maximum_combined_output_age_p99_ms": 125.0,
},
"authority": {
@@ -98,6 +101,7 @@ def test_three_layer_gate_joins_exact_frames_and_preserves_false_authority(
{
"schema_version": EVIDENCE.VEGETATION_SCHEMA,
"result_id": "vegetation-test",
"integrated_load_gate_passed": True,
"source": {"requested_source_rate_hz": 12.0},
"candidate": {"candidate_key": "ddrnet", "checkpoint_sha256": "b" * 64},
"identity": {
@@ -108,10 +112,16 @@ def test_three_layer_gate_joins_exact_frames_and_preserves_false_authority(
"execution": {
"frame_count": EVIDENCE.FRAME_COUNT,
"effective_fps": 11.75,
"effective_timeline_fps": 11.75,
"effective_inference_fps": 5.875,
"inference_stride": 2,
"inference_frame_count": 2245,
"held_evidence_frame_count": 2244,
"capacity_drop_count": 0,
},
"timing": {
"completion_age_ms": {"p95": 25.0},
"inference_completion_age_ms": {"p95": 25.0},
"stage_ms": {"p95": 20.0},
"inference_ms": {"p95": 18.0},
},
@@ -148,9 +158,14 @@ def test_three_layer_gate_joins_exact_frames_and_preserves_false_authority(
"".join(
json.dumps(
{
"schema_version": "missioncore.lab-v1-vegetation-integrated-frame/v1",
"schema_version": "missioncore.lab-v1-vegetation-integrated-frame/v2",
"sequence": index,
"completion_age_ms": 20.0,
"inference_executed": index % 2 == 0,
"semantic_source_sequence": index - (index % 2),
"semantic_evidence_source_age_ms": 20.0
if index % 2 == 0
else 103.333333,
}
)
+ "\n"
@@ -227,6 +242,8 @@ def test_integrated_release_is_deterministic_and_contains_one_vegetation_candida
release = json.loads(release_stream.read())
assert "payload/run_vegetation_integrated_load.py" in names
assert "payload/build_vegetation_integrated_graph_evidence.py" in names
assert "payload/lab-v1-vegetation-integrated-multirate-shadow-v2.json" in names
assert release["semantic_inference_rate_hz"] == 6.0
assert release["scope"]["heavy_vegetation_candidates"] == ["ddrnet"]
assert all(value is False for value in release["authority"].values())
@@ -234,7 +251,7 @@ def test_integrated_release_is_deterministic_and_contains_one_vegetation_candida
def test_worker_gate_reuses_shared_barrier_and_keeps_canonical_triton_unchanged() -> None:
runner = RUNNER_PATH.read_text(encoding="utf-8")
wrapper = POWERSHELL_PATH.read_text(encoding="utf-8")
assert '"source-paced-integrated-shadow/v1"' in runner
assert '"source-paced-multirate-integrated-shadow/v2"' in runner
assert "wait_for_shared_start(" in runner
assert '"bounded-compressed-scene-buffer/v1"' in runner
assert "buffer_compressed_video(" in runner
@@ -243,6 +260,8 @@ def test_worker_gate_reuses_shared_barrier_and_keeps_canonical_triton_unchanged(
assert "decode_source(source_capture, expected_size)" in runner
assert '"camera_semantics_can_clear_rigid_geometry": False' in runner
assert "--runtime-video-cache /tmp/vegetation-right.mp4" in wrapper
assert "--inference-stride 2" in wrapper
assert '--tmpfs "/tmp:rw,noexec,nosuid,size=2g"' in wrapper
assert "$VegetationLoadGate" in wrapper
assert '"vegetation"' in wrapper
assert "if ($canonicalAfter.Id -cne $canonicalId" not in wrapper