adopt modelrevert tree as the new clearpilot baseline

Replaces clearpilot's working state wholesale with the modelrevert branch's
tree (modelrevert tip cea422b). Discards the parked-controlsd manager-process
split and the two session READMEs that documented it; keeps the simpler
in-process park short-circuits (controlsd state_control, plannerd, frogpilot_process)
and the cached-output decimation (modeld, dmonitoringmodeld) that achieve
the same goal with less moving parts. Also brings in the locationd GPS
ignore, the calibrationd valid=calStatus gate, and the model-revert lineage's
controlsd / paramsd / torqued / events.py / carstate.py / interfaces.py.

This is a single new commit on clearpilot (no merge), so the branch advances
linearly while the file state matches modelrevert exactly.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

selfdrive/modeld/modeld.py

@@ -134,11 +134,15 @@ 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()
-  cloudlog.warning("CL context ready; loading model")
+  _t1 = _time.monotonic()
+  cloudlog.warning("CL context ready in %.3fs; loading model", _t1 - _t0)
   model = ModelState(cl_context)
-  cloudlog.warning("models loaded, modeld starting")
+  _t2 = _time.monotonic()
+  cloudlog.warning("model loaded in %.3fs (total init %.3fs), modeld starting", _t2 - _t1, _t2 - _t0)
 
   # visionipc clients
   while True:
@@ -179,6 +183,10 @@ 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
@@ -233,6 +241,12 @@ 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
@@ -304,12 +318,21 @@ def main(demo=False):
       **({'radar_tracks': radar_tracks,} if DISABLE_RADAR 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
+    # 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
 
     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,