adopt pre-modelrevert clearpilot tree (d639e28) as the new head

Discard the modelrevert tree adoption (8b4b7e0) and the in-process park
short-circuits / cached-output / dashcam-idle work that came with it
(0dc8002, 37e095e). Restore the clearpilot tree as it stood at d639e28 —
the parked-controlsd manager-process split, the GPS-disable in locationd,
the controlsd UI hooks, the boardd ignition-edge safety_setter_thread
fix. After a full /data/params/d wipe and re-calibration drive, the
modelrevert-tree variant overcorrected on turns; reverting to the
parked-controlsd architecture (which Brian had previously vetted and
documented in 887b9c9 + 27cad05) and starting fresh.

Single new commit, no merge — file state matches d639e28 byte-for-byte.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-04-26 14:17:25 -05:00
parent 7a584a7e39
commit ab9158bfb7
22 changed files with 955 additions and 236 deletions
+3 -13
View File
@@ -7,7 +7,7 @@ import ctypes
import numpy as np
from pathlib import Path
from cereal import car, messaging
from cereal import messaging
from cereal.messaging import PubMaster, SubMaster
from cereal.visionipc import VisionIpcClient, VisionStreamType, VisionBuf
from openpilot.common.swaglog import cloudlog
@@ -128,15 +128,10 @@ def main():
assert vipc_client.is_connected()
cloudlog.warning(f"connected with buffer size: {vipc_client.buffer_len}")
sm = SubMaster(["liveCalibration", "carState"])
sm = SubMaster(["liveCalibration"])
pm = PubMaster(["driverStateV2"])
calib = np.zeros(CALIB_LEN, dtype=np.float32)
# CLEARPILOT: cache last model output to serve while gear is in park —
# mirrors the same trick modeld uses. Skips DSP inference on the driver
# camera when the car is stationary; downstream dmonitoringd still gets
# a fresh publish each frame.
last_model_output = None
# last = 0
while True:
@@ -148,13 +143,8 @@ def main():
if sm.updated["liveCalibration"]:
calib[:] = np.array(sm["liveCalibration"].rpyCalib)
parked = sm["carState"].gearShifter == car.CarState.GearShifter.park
t1 = time.perf_counter()
if parked and last_model_output is not None:
model_output, dsp_execution_time = last_model_output
else:
model_output, dsp_execution_time = model.run(buf, calib)
last_model_output = (model_output, dsp_execution_time)
model_output, dsp_execution_time = model.run(buf, calib)
t2 = time.perf_counter()
pm.send("driverStateV2", get_driverstate_packet(model_output, vipc_client.frame_id, vipc_client.timestamp_sof, t2 - t1, dsp_execution_time))
+6 -29
View File
@@ -134,15 +134,11 @@ def main(demo=False):
setproctitle(PROCESS_NAME)
config_realtime_process(7, 54)
import time as _time
cloudlog.warning("setting up CL context")
_t0 = _time.monotonic()
cl_context = CLContext()
_t1 = _time.monotonic()
cloudlog.warning("CL context ready in %.3fs; loading model", _t1 - _t0)
cloudlog.warning("CL context ready; loading model")
model = ModelState(cl_context)
_t2 = _time.monotonic()
cloudlog.warning("model loaded in %.3fs (total init %.3fs), modeld starting", _t2 - _t1, _t2 - _t0)
cloudlog.warning("models loaded, modeld starting")
# visionipc clients
while True:
@@ -183,10 +179,6 @@ def main(demo=False):
model_transform_main = np.zeros((3, 3), dtype=np.float32)
model_transform_extra = np.zeros((3, 3), dtype=np.float32)
live_calib_seen = False
# CLEARPILOT: cache last model output to serve while gear is in park — saves
# GPU inference cost while still giving downstream a constant publish rate so
# freq_ok / valid checks don't cascade.
last_model_output = None
nav_features = np.zeros(ModelConstants.NAV_FEATURE_LEN, dtype=np.float32)
nav_instructions = np.zeros(ModelConstants.NAV_INSTRUCTION_LEN, dtype=np.float32)
buf_main, buf_extra = None, None
@@ -241,12 +233,6 @@ def main(demo=False):
meta_extra = meta_main
sm.update(0)
# CLEARPILOT: constant 20fps. Variable-rate + standby logic removed — the
# variable-rate path caused freq_ok cascades in downstream consumers
# (calibrationd/locationd/paramsd). Running at the camera's native rate is
# simpler and keeps the full-stack localization chain happy.
desire = DH.desire
is_rhd = sm["driverMonitoringState"].isRHD
frame_id = sm["roadCameraState"].frameId
@@ -318,21 +304,12 @@ def main(demo=False):
**({'radar_tracks': radar_tracks,} if DISABLE_RADAR else {}),
}
# CLEARPILOT: in park, serve the cached last model output instead of running
# GPU inference. First cycle (no cache yet) still runs once so we have
# something to serve. Out-of-park resumes fresh inference every frame.
parked = sm['carState'].gearShifter == car.CarState.GearShifter.park
if parked and last_model_output is not None:
model_output = last_model_output
model_execution_time = 0.0
else:
mt1 = time.perf_counter()
model_output = model.run(buf_main, buf_extra, model_transform_main, model_transform_extra, inputs, prepare_only)
mt2 = time.perf_counter()
model_execution_time = mt2 - mt1
mt1 = time.perf_counter()
model_output = model.run(buf_main, buf_extra, model_transform_main, model_transform_extra, inputs, prepare_only)
mt2 = time.perf_counter()
model_execution_time = mt2 - mt1
if model_output is not None:
last_model_output = model_output
modelv2_send = messaging.new_message('modelV2')
posenet_send = messaging.new_message('cameraOdometry')
fill_model_msg(modelv2_send, model_output, publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id, frame_drop_ratio,