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firestar5683
2026-05-05 10:48:08 -05:00
parent 026a2eb528
commit d9676ca194
8 changed files with 90 additions and 29 deletions
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selfdrive/controls/lib/longitudinal_planner.py
+1 -1
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@@ -285,7 +285,7 @@ class LongitudinalPlanner:
@property
def mlsim(self):
return self.generation in ("v8", "v10", "v11", "v12", "v13")
return self.generation in ("v8", "v10", "v11", "v12", "v13", "v14")
def get_mpc_mode(self) -> str:
if not self.mlsim:
selfdrive/controls/tests/test_longitudinal_planner.py
+46 -14
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@@ -105,7 +105,7 @@ def make_toggles(model_version: str = "v11"):
)
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_experimental_mlsim_uses_vehicle_min_accel_floor(model_version):
v_ego = 18.0
desired_accel = -1.0
@@ -126,7 +126,7 @@ def test_experimental_mlsim_uses_vehicle_min_accel_floor(model_version):
assert planner.output_a_target < comfort_min_accel
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_uses_close_raw_lead_when_tracking_lead_is_debounced(model_version):
v_ego = 5.0
@@ -151,7 +151,7 @@ def test_acc_mode_uses_close_raw_lead_when_tracking_lead_is_debounced(model_vers
)
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_matches_no_lead_baseline_for_far_vision_only_lead_without_tracking(model_version):
v_ego = 29.0
@@ -313,7 +313,7 @@ def test_vision_slow_stopped_lead_cap_ignores_far_high_speed_stop_candidate():
assert planner.get_vision_slow_stopped_lead_cap(lead, v_ego, -1.0, 1.45) is None
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_dynamic_t_follow_increases_modestly_for_closing_lead(model_version):
v_ego = 21.535
@@ -337,7 +337,7 @@ def test_dynamic_t_follow_increases_modestly_for_closing_lead(model_version):
assert planner.effective_t_follow < sm["starpilotPlan"].tFollow + 0.45
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_dynamic_t_follow_stays_near_base_for_far_highway_lead(model_version):
v_ego = 29.26
@@ -359,7 +359,7 @@ def test_dynamic_t_follow_stays_near_base_for_far_highway_lead(model_version):
assert planner.effective_t_follow == pytest.approx(sm["starpilotPlan"].tFollow, abs=0.02)
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_dynamic_t_follow_releases_toward_base_after_lead_opens(model_version):
v_ego = 21.535
@@ -387,7 +387,7 @@ def test_dynamic_t_follow_releases_toward_base_after_lead_opens(model_version):
assert planner.effective_t_follow == pytest.approx(sm["starpilotPlan"].tFollow, abs=0.02)
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_vision_lead_approach_cap_smooths_before_close_brake(model_version):
approach_v_ego = 21.535
close_v_ego = 21.435
@@ -424,7 +424,7 @@ def test_acc_mode_vision_lead_approach_cap_smooths_before_close_brake(model_vers
assert planner_close.output_a_target < planner_approach.output_a_target - 0.25
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_pretracking_vision_slow_lead_blocks_positive_catchup(model_version):
v_ego = 23.23
@@ -459,7 +459,7 @@ def test_acc_mode_pretracking_vision_slow_lead_blocks_positive_catchup(model_ver
assert planner_with_lead.output_a_target < -0.2
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_pretracking_vision_far_slower_lead_starts_braking_before_tracking(model_version):
v_ego = 21.48
@@ -500,7 +500,7 @@ def test_acc_mode_pretracking_vision_far_slower_lead_starts_braking_before_track
assert lead_outputs[-1] < no_lead_outputs[-1] - 0.15
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_pretracking_near_stopped_vision_lead_does_not_relax_when_confidence_is_midrange(model_version):
v_ego = 20.35
@@ -534,7 +534,7 @@ def test_acc_mode_pretracking_near_stopped_vision_lead_does_not_relax_when_confi
assert planner_with_lead.output_a_target < -0.45
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_tracked_pace_matched_lead_caps_positive_catchup(model_version):
v_ego = 28.7
@@ -568,7 +568,7 @@ def test_acc_mode_tracked_pace_matched_lead_caps_positive_catchup(model_version)
assert planner_with_lead.output_a_target < 0.08
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_low_speed_vision_stop_buffer_sets_should_stop_before_tiny_gap(model_version):
v_ego = 3.8
@@ -591,7 +591,7 @@ def test_acc_mode_low_speed_vision_stop_buffer_sets_should_stop_before_tiny_gap(
assert planner.output_a_target < -1.0
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_standstill_moving_lead_does_not_force_resume_while_should_stop(model_version):
v_ego = 0.0
@@ -615,7 +615,7 @@ def test_standstill_moving_lead_does_not_force_resume_while_should_stop(model_ve
assert planner.output_a_target < 0.1
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13"])
@pytest.mark.parametrize("model_version", ["v11", "v12", "v13", "v14"])
def test_acc_mode_damps_far_radar_mild_lead_brake_more_than_close_brake(model_version):
far_v_ego = 29.26
far_v_cruise = 32.22
@@ -690,6 +690,7 @@ def test_modeld_action_passes_tomb_raider_longitudinal_params(monkeypatch):
v_ego=5.0,
mlsim=True,
is_v9=True,
is_v14=False,
starpilot_toggles=toggles,
)
@@ -701,6 +702,37 @@ def test_modeld_action_passes_tomb_raider_longitudinal_params(monkeypatch):
assert action.shouldStop
def test_modeld_action_uses_direct_action_head_for_v14(monkeypatch):
monkeypatch.setenv("DEBUG", "0")
fake_commonmodel = types.ModuleType("openpilot.selfdrive.modeld.models.commonmodel_pyx")
fake_commonmodel.DrivingModelFrame = object
fake_commonmodel.CLContext = object
monkeypatch.setitem(sys.modules, fake_commonmodel.__name__, fake_commonmodel)
from openpilot.selfdrive.modeld import modeld
prev_action = log.ModelDataV2.Action.new_message()
prev_action.desiredCurvature = 0.05
prev_action.desiredAcceleration = -0.2
toggles = SimpleNamespace(vEgoStopping=0.42)
action = modeld.get_action_from_model(
{"action": np.array([[12.0, -0.8]], dtype=np.float32)},
prev_action,
lat_action_t=0.2,
long_action_t=0.73,
v_ego=5.0,
mlsim=True,
is_v9=False,
is_v14=True,
starpilot_toggles=toggles,
)
assert action.desiredCurvature == pytest.approx(0.12)
assert action.desiredAcceleration < -0.2
assert not action.shouldStop
def test_allow_throttle_hysteresis_filters_gas_prob_chatter():
v_ego = 10.0
selfdrive/modeld/modeld.py
+36 -7
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@@ -99,7 +99,23 @@ def _canonical_model_id(model_id: str) -> str:
def get_action_from_model(model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action,
lat_action_t: float, long_action_t: float, v_ego: float, mlsim: bool, is_v9: bool, starpilot_toggles) -> log.ModelDataV2.Action:
lat_action_t: float, long_action_t: float, v_ego: float, mlsim: bool,
is_v9: bool, is_v14: bool, starpilot_toggles) -> log.ModelDataV2.Action:
if is_v14:
desired_curv_unscaled, desired_accel = model_output['action'][0]
desired_curvature = float(desired_curv_unscaled) / 100.0
should_stop = (v_ego < 0.3 and desired_accel < 0.1)
desired_accel = smooth_value(float(desired_accel), prev_action.desiredAcceleration, LONG_SMOOTH_SECONDS)
if v_ego > MIN_LAT_CONTROL_SPEED:
desired_curvature = smooth_value(desired_curvature, prev_action.desiredCurvature, LAT_SMOOTH_SECONDS)
else:
desired_curvature = prev_action.desiredCurvature
return log.ModelDataV2.Action(desiredCurvature=float(desired_curvature),
desiredAcceleration=float(desired_accel),
shouldStop=bool(should_stop))
plan = model_output['plan'][0]
if 'planplus' in model_output:
recovery_power = getattr(starpilot_toggles, "recovery_power", 1.0)
@@ -158,6 +174,8 @@ class ModelState:
numpy_inputs['features_buffer'] = np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.FEATURE_LEN), dtype=np.float32)
if 'action_t' in input_shapes:
numpy_inputs['action_t'] = np.zeros(input_shapes['action_t'], dtype=np.float32)
if 'prev_action' in input_shapes:
numpy_inputs['prev_action'] = np.zeros(input_shapes['prev_action'], dtype=np.float32)
# Optional inputs for non-v11 (and some v10/v9 variants)
# Lateral control params
@@ -285,8 +303,9 @@ class ModelState:
self.is_v10 = (self.policy_generation == "v10")
self.is_v12 = (self.policy_generation == "v12")
self.is_v13 = (self.policy_generation == "v13")
self.is_v14 = (self.policy_generation == "v14")
self.is_v9 = (self.policy_generation == "v9")
self.mlsim = (self.policy_generation in ("v8", "v10", "v11", "v12", "v13"))
self.mlsim = (self.policy_generation in ("v8", "v10", "v11", "v12", "v13", "v14"))
self.policy_has_plan = 'plan' in self.policy_output_slices
self.frames = {name: DrivingModelFrame(context, ModelConstants.TEMPORAL_SKIP) for name in self.vision_input_names}
@@ -311,7 +330,7 @@ class ModelState:
self.off_policy_output: np.ndarray | None = None
off_policy_metadata = None
if self.policy_generation in ("v12", "v13") or OFF_POLICY_METADATA_PATH.is_file() or OFF_POLICY_PKL_PATH.is_file():
if self.policy_generation in ("v12", "v13", "v14") or OFF_POLICY_METADATA_PATH.is_file() or OFF_POLICY_PKL_PATH.is_file():
resolved_off_policy_meta = ensure_artifact(OFF_POLICY_METADATA_PATH, "driving_off_policy_metadata.pkl", optional=True)
if resolved_off_policy_meta is not None:
with open(resolved_off_policy_meta, 'rb') as f:
@@ -386,6 +405,11 @@ class ModelState:
if self.off_policy_enabled and 'action_t' in self.off_policy_numpy_inputs:
self.off_policy_numpy_inputs['action_t'][:] = inputs['action_t']
if 'prev_action' in self.numpy_inputs:
self.numpy_inputs['prev_action'][:] = inputs['prev_action']
if self.off_policy_enabled and 'prev_action' in self.off_policy_numpy_inputs:
self.off_policy_numpy_inputs['prev_action'][:] = inputs['prev_action']
if 'lateral_control_params' in self.numpy_inputs:
self.numpy_inputs['lateral_control_params'][:] = inputs['lateral_control_params']
if self.off_policy_enabled and 'lateral_control_params' in self.off_policy_numpy_inputs:
@@ -425,14 +449,14 @@ class ModelState:
self.full_prev_desired_curv[0,-1,:] = policy_outputs_dict['desired_curvature'][0, :]
if self.prev_desired_curv_key is not None:
# v9/v10/v11/v12/v13 models expect zeros for prev_desired_curv(s); others use history
if self.is_v9 or self.is_v10 or self.is_v11 or self.is_v12 or self.is_v13:
# v9/v10/v11/v12/v13/v14 models expect zeros for prev_desired_curv(s); others use history
if self.is_v9 or self.is_v10 or self.is_v11 or self.is_v12 or self.is_v13 or self.is_v14:
self.numpy_inputs[self.prev_desired_curv_key][:] = 0 * self.full_prev_desired_curv[0, self.temporal_idxs]
else:
self.numpy_inputs[self.prev_desired_curv_key][:] = self.full_prev_desired_curv[0, self.temporal_idxs]
if self.off_policy_enabled and self.off_policy_prev_desired_curv_key is not None:
if self.is_v9 or self.is_v12 or self.is_v13:
if self.is_v9 or self.is_v12 or self.is_v13 or self.is_v14:
self.off_policy_numpy_inputs[self.off_policy_prev_desired_curv_key][:] = 0 * self.full_prev_desired_curv[0, self.temporal_idxs]
else:
self.off_policy_numpy_inputs[self.off_policy_prev_desired_curv_key][:] = self.full_prev_desired_curv[0, self.temporal_idxs]
@@ -611,6 +635,11 @@ def main(demo=False):
}
if 'action_t' in model.numpy_inputs or (model.off_policy_enabled and 'action_t' in model.off_policy_numpy_inputs):
inputs['action_t'] = np.array([lat_action_t, long_action_t], dtype=np.float32)
if 'prev_action' in model.numpy_inputs or (model.off_policy_enabled and 'prev_action' in model.off_policy_numpy_inputs):
inputs['prev_action'] = np.array([
prev_action.desiredCurvature * max(1.0, v_ego) ** 2,
prev_action.desiredAcceleration,
], dtype=np.float32)
# Include optional inputs only if the loaded model expects them
if 'lateral_control_params' in model.numpy_inputs:
inputs['lateral_control_params'] = lateral_control_params
@@ -630,7 +659,7 @@ def main(demo=False):
model_output, prev_action,
lat_action_t,
long_action_t,
v_ego, model.mlsim, model.is_v9, starpilot_toggles,
v_ego, model.mlsim, model.is_v9, model.is_v14, starpilot_toggles,
)
prev_action = action
fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
selfdrive/ui/layouts/settings/starpilot/driving_model.py
+1 -1
View File
@@ -723,7 +723,7 @@ class StarPilotDrivingModelLayout(_SettingsPage):
f"{key}_driving_vision_metadata.pkl",
]
if version in {"v12", "v13"}:
if version in {"v12", "v13", "v14"}:
files.extend(
[
f"{key}_driving_off_policy_tinygrad.pkl",
selfdrive/ui/mici/layouts/settings/driving_model.py
+1 -1
View File
@@ -725,7 +725,7 @@ class DrivingModelBigButton(BigButton):
f"{key}_driving_vision_metadata.pkl",
]
if version in {"v12", "v13"}:
if version in {"v12", "v13", "v14"}:
files.extend([
f"{key}_driving_off_policy_tinygrad.pkl",
f"{key}_driving_off_policy_metadata.pkl",
starpilot/assets/model_manager.py
+2 -2
View File
@@ -18,7 +18,7 @@ from openpilot.starpilot.common.starpilot_utilities import delete_file
from openpilot.starpilot.common.starpilot_variables import MODELS_PATH
MANIFEST_CANDIDATES = ("v21",)
TINYGRAD_VERSIONS = {"v8", "v9", "v10", "v11", "v12", "v13"}
TINYGRAD_VERSIONS = {"v8", "v9", "v10", "v11", "v12", "v13", "v14"}
DEFAULT_MODEL_KEY = "sc2"
MODEL_KEY_CANONICAL_MAP = {
"sc": DEFAULT_MODEL_KEY,
@@ -192,7 +192,7 @@ class ModelManager:
f"{model_key}_driving_vision_metadata.pkl",
]
if model_version in {"v12", "v13"}:
if model_version in {"v12", "v13", "v14"}:
filenames += [
f"{model_key}_driving_off_policy_tinygrad.pkl",
f"{model_key}_driving_off_policy_metadata.pkl",
starpilot/common/starpilot_variables.py
+1 -1
View File
@@ -983,7 +983,7 @@ class StarPilotVariables:
if isinstance(toggle.model_version, bytes):
toggle.model_version = toggle.model_version.decode("utf-8", "ignore")
toggle.classic_model = toggle.model_version in {"v1", "v2", "v3", "v4"}
toggle.tinygrad_model = toggle.model_version in {"v8", "v9", "v10", "v11", "v12", "v13"}
toggle.tinygrad_model = toggle.model_version in {"v8", "v9", "v10", "v11", "v12", "v13", "v14"}
toggle.tomb_raider = toggle.model == "space-lab"
toggle.model_ui = self.get_value("ModelUI")
starpilot/system/the_pond/the_pond.py
+2 -2
View File
@@ -4339,14 +4339,14 @@ def setup(app):
if f"{model_key}.thneed" in on_disk_files:
return True
if model_version in ("v8", "v9", "v10", "v11", "v12", "v13"):
if model_version in ("v8", "v9", "v10", "v11", "v12", "v13", "v14"):
required_files = {
f"{model_key}_driving_policy_tinygrad.pkl",
f"{model_key}_driving_vision_tinygrad.pkl",
f"{model_key}_driving_policy_metadata.pkl",
f"{model_key}_driving_vision_metadata.pkl",
}
if model_version in ("v12", "v13"):
if model_version in ("v12", "v13", "v14"):
required_files |= {
f"{model_key}_driving_off_policy_tinygrad.pkl",
f"{model_key}_driving_off_policy_metadata.pkl",