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>

selfdrive/modeld/modeld.py

@@ -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,