IQ.Pilot Release Commit @ 98a2c61

iqpilot/selfdrive/controls/lib/longcontrol.py

@@ -91,9 +91,5 @@ class LongControl:
                                        freeze_integrator=gas_override)
         self.smooth.reset()
 
-    if gas_override:
-      # safety blocks braking while the gas is pressed, and a blocked tx drops the whole frame
-      output_accel = max(output_accel, 0.0)
-
     self.last_output_accel = np.clip(output_accel, accel_limits[0], accel_limits[1])
     return self.last_output_accel

iqpilot/selfdrive/controls/lib/neural_network_feed_forward/tests/test_network.py

@@ -16,17 +16,17 @@ from iqpilot.selfdrive.controls.lib.latcontrol_torque import TORQUE_NN_MODEL_PAT
 # layers). Used as a fallback so the loader logic is still exercised when no trained
 # models are shipped (they are removed pending retraining and re-added over time).
 _SYNTHETIC_MODEL = {
-  "input_size": 4,
+  "input_size": 18,
   "output_size": 1,
-  "input_mean": [[0.0], [0.0], [0.0], [0.0]],
-  "input_std": [[1.0], [1.0], [1.0], [1.0]],
+  "input_mean": [[0.0]] * 18,
+  "input_std": [[1.0]] * 18,
   "layers": [
-    {"dense_1_W": [[0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5, 0.5]], "dense_1_b": [[0.0], [0.0]], "activation": "sigmoid"},
+    {"dense_1_W": [[0.5] * 18, [0.5] * 18], "dense_1_b": [[0.0], [0.0]], "activation": "sigmoid"},
     {"dense_2_W": [[2.0, 2.0]], "dense_2_b": [[-1.0]], "activation": "identity"},
   ],
 }
 
-MODEL_FILES = sorted(f for f in os.listdir(TORQUE_NN_MODEL_PATH) if f.endswith(".json"))
+MODEL_FILES = sorted(f for f in os.listdir(TORQUE_NN_MODEL_PATH) if f.endswith(".json")) if os.path.isdir(TORQUE_NN_MODEL_PATH) else []
 if MODEL_FILES:
   _MODEL_DIR = TORQUE_NN_MODEL_PATH
   _NAMES = MODEL_FILES

iqpilot/selfdrive/controls/lib/neural_network_feed_forward/tests/test_nnff_assembly.py

@@ -15,15 +15,9 @@ from iqpilot.common.params import Params
 from iqpilot.common.pid import PIDController
 from iqpilot.selfdrive.iqmodeld.config import ModelConstants
 from iqpilot.selfdrive.controls.lib.latcontrol_torque import NeuralNetworkFeedForward
-from iqpilot.selfdrive.controls.lib.latcontrol_torque import TORQUE_NN_MODEL_PATH
+from iqpilot.selfdrive.controls.lib.neural_network_feed_forward.tests.test_network import _MODEL_DIR, _NAMES
 
-_REAL_MODEL = next((f for f in sorted(os.listdir(TORQUE_NN_MODEL_PATH))
-                    if f.endswith(".json") and f != "MOCK.json"), None)
-
-# Models are shipped separately and re-added as retrained; with none present,
-# NNFF is a no-op (falls back to stock torque FF), so the assembly tests skip.
-pytestmark = pytest.mark.skipif(_REAL_MODEL is None,
-                                reason="no NNFF models present (nuked pending retraining)")
+_REAL_MODEL = next((f for f in _NAMES if f != "MOCK.json"), _NAMES[0])
 
 
 def _torque_fn():
@@ -53,7 +47,7 @@ def _model_v2():
 
 def _make_controller(model_file):
   Params().put_bool("NeuralNetworkFeedForward", True)
-  path = os.path.join(TORQUE_NN_MODEL_PATH, model_file)
+  path = os.path.join(_MODEL_DIR, model_file)
   cp = SimpleNamespace(steerActuatorDelay=0.15)
   cp_iq = SimpleNamespace(iqLateralNet=SimpleNamespace(
     model=SimpleNamespace(path=path, name=os.path.splitext(model_file)[0])))
@@ -84,7 +78,10 @@ class TestControllerWiring:
   def test_mock_model_reports_absent(self):
     nnff = _make_controller("MOCK.json")
     assert nnff.has_nn_model is False
-    assert nnff.model.input_size >= 2  # MOCK still loads as a valid net
+    if "MOCK.json" in _NAMES:
+      assert nnff.model.input_size >= 2
+    else:
+      assert nnff.model is None
 
   def test_update_returns_finite_torque(self):
     nnff = _make_controller(_REAL_MODEL)

iqpilot/selfdrive/controls/tests/test_longcontrol.py

@@ -1,5 +1,7 @@
+from types import SimpleNamespace
+
 from iqpilot.cereal import custom
-from iqpilot.selfdrive.controls.lib.longcontrol import LongCtrlState, long_control_state_trans
+from iqpilot.selfdrive.controls.lib.longcontrol import LongControl, LongCtrlState, long_control_state_trans
 
 
 class TestLongControlStateTransition:
@@ -41,3 +43,30 @@ def test_engage():
   next_state = long_control_state_trans(CP_IQ, active, current_state,
                              should_stop=False, brake_pressed=False, cruise_standstill=False)
   assert next_state == LongCtrlState.pid
+
+
+def test_gas_override_preserves_negative_accel_command():
+  pid_calls = []
+  control = object.__new__(LongControl)
+  control.CP = SimpleNamespace(stopAccel=-0.55)
+  control.CP_IQ = SimpleNamespace(enableGasInterceptor=False)
+  control.long_control_state = LongCtrlState.pid
+  control.pid = SimpleNamespace(
+    update=lambda error, **kwargs: pid_calls.append((error, kwargs)) or -0.5,
+    reset=lambda: None,
+  )
+  control.last_output_accel = -0.4
+  control.stopping_decel_rate = 1.0
+  control.smooth = SimpleNamespace(enabled=False, update=lambda: None, reset=lambda: None)
+  car_state = SimpleNamespace(
+    vEgo=15.0,
+    aEgo=0.0,
+    brakePressed=False,
+    standstill=False,
+    cruiseState=SimpleNamespace(standstill=False),
+  )
+
+  output = control.update(True, car_state, -0.5, False, (-3.5, 2.0), gas_override=True)
+
+  assert output == -0.5
+  assert pid_calls == [(-0.5, {"speed": 15.0, "feedforward": -0.5, "freeze_integrator": True})]