Rocket league model (#24869)

* dd9a502d-c8e2-4831-b365-804b0ae0739d/600 80041070-d276-4fed-bdb9-0075e5442908/420

* no elementwise op

* 9dabf0fe-2e60-44bf-8d3a-d20a74aca072/600 ae746590-0bb5-4a16-80db-15f02d314f03/300 c4663a12-b499-4c9b-90dd-b169e3948cb1/60

* explicit slice

* some copies are useful

* 1456d261-d232-4654-8885-4d9fde883894/440 c06eba55-1931-4e00-9d63-acad00161be0/700 af2eb6ba-1935-4318-aaf8-868db81a4932/425

* 154f663e-d3e9-4020-ad49-0e640588ebbe/399 badb5e69-504f-4544-a99e-ba75ed204b74/800 08330327-7663-4874-af7a-dcbd2c994ba7/800

* set steer rate cost to 1.0

* smaller temporal size

* Update model reg

* update model ref again

* This did upload somehow

* Update steer rate cost

Co-authored-by: Yassine Yousfi <yyousfi1@binghamton.edu>
old-commit-hash: 9283040d84
taco
HaraldSchafer 3 years ago committed by GitHub
parent 07c859d384
commit b0b1aff5cc
  1. 1
      selfdrive/car/body/interface.py
  2. 1
      selfdrive/car/chrysler/interface.py
  3. 1
      selfdrive/car/ford/interface.py
  4. 1
      selfdrive/car/gm/interface.py
  5. 1
      selfdrive/car/honda/interface.py
  6. 1
      selfdrive/car/hyundai/interface.py
  7. 1
      selfdrive/car/mazda/interface.py
  8. 1
      selfdrive/car/nissan/interface.py
  9. 1
      selfdrive/car/subaru/interface.py
  10. 1
      selfdrive/car/tesla/interface.py
  11. 1
      selfdrive/car/tests/test_car_interfaces.py
  12. 1
      selfdrive/car/tests/test_models.py
  13. 1
      selfdrive/car/toyota/interface.py
  14. 1
      selfdrive/car/volkswagen/interface.py
  15. 7
      selfdrive/controls/lib/lateral_planner.py
  16. 2
      selfdrive/controls/plannerd.py
  17. 2
      selfdrive/modeld/models/driving.h
  18. 4
      selfdrive/modeld/models/supercombo.dlc
  19. 4
      selfdrive/modeld/models/supercombo.onnx
  20. 2
      selfdrive/modeld/thneed/compile.cc
  21. 8
      selfdrive/modeld/thneed/optimizer.cc
  22. 2
      selfdrive/test/process_replay/model_replay_ref_commit
  23. 2
      selfdrive/test/process_replay/ref_commit

@ -19,7 +19,6 @@ class CarInterface(CarInterfaceBase):
ret.minSteerSpeed = -math.inf
ret.maxLateralAccel = math.inf # TODO: set to a reasonable value
ret.steerRatio = 0.5
ret.steerRateCost = 0.5
ret.steerLimitTimer = 1.0
ret.steerActuatorDelay = 0.

@ -20,7 +20,6 @@ class CarInterface(CarInterfaceBase):
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.15, 0.30], [0.03, 0.05]]
ret.lateralTuning.pid.kf = 0.00006 # full torque for 10 deg at 80mph means 0.00007818594
ret.steerActuatorDelay = 0.1
ret.steerRateCost = 0.7
ret.steerLimitTimer = 0.4
if candidate in (CAR.JEEP_CHEROKEE, CAR.JEEP_CHEROKEE_2019):

@ -59,7 +59,6 @@ class CarInterface(CarInterfaceBase):
# LCA can steer down to zero
ret.minSteerSpeed = 0.
ret.steerRateCost = 1.0
ret.centerToFront = ret.wheelbase * 0.44
ret.rotationalInertia = scale_rot_inertia(ret.mass, ret.wheelbase)

@ -63,7 +63,6 @@ class CarInterface(CarInterfaceBase):
ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0.], [0.]]
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.2], [0.00]]
ret.lateralTuning.pid.kf = 0.00004 # full torque for 20 deg at 80mph means 0.00007818594
ret.steerRateCost = 1.0
ret.steerActuatorDelay = 0.1 # Default delay, not measured yet
ret.longitudinalTuning.kpBP = [5., 35.]

@ -319,7 +319,6 @@ class CarInterface(CarInterfaceBase):
tire_stiffness_factor=tire_stiffness_factor)
ret.steerActuatorDelay = 0.1
ret.steerRateCost = 0.5
ret.steerLimitTimer = 0.8
return ret

@ -43,7 +43,6 @@ class CarInterface(CarInterfaceBase):
ret.dashcamOnly = not os.path.exists('/data/enable-ev6')
ret.steerActuatorDelay = 0.1 # Default delay
ret.steerRateCost = 0.5
ret.steerLimitTimer = 0.4
tire_stiffness_factor = 1.

@ -25,7 +25,6 @@ class CarInterface(CarInterfaceBase):
ret.dashcamOnly = candidate not in (CAR.CX5_2022, CAR.CX9_2021)
ret.steerActuatorDelay = 0.1
ret.steerRateCost = 1.0
ret.steerLimitTimer = 0.8
tire_stiffness_factor = 0.70 # not optimized yet

@ -14,7 +14,6 @@ class CarInterface(CarInterfaceBase):
ret.safetyConfigs = [get_safety_config(car.CarParams.SafetyModel.nissan)]
ret.steerLimitTimer = 1.0
ret.steerRateCost = 0.5
ret.steerActuatorDelay = 0.1

@ -22,7 +22,6 @@ class CarInterface(CarInterfaceBase):
ret.dashcamOnly = candidate in PREGLOBAL_CARS
ret.steerRateCost = 0.7
ret.steerLimitTimer = 0.4
if candidate == CAR.ASCENT:

@ -42,7 +42,6 @@ class CarInterface(CarInterfaceBase):
ret.steerLimitTimer = 1.0
ret.steerActuatorDelay = 0.25
ret.steerRateCost = 0.5
if candidate in (CAR.AP2_MODELS, CAR.AP1_MODELS):
ret.mass = 2100. + STD_CARGO_KG

@ -33,7 +33,6 @@ class TestCarInterfaces(unittest.TestCase):
assert car_interface
self.assertGreater(car_params.mass, 1)
self.assertGreater(car_params.steerRateCost, 1e-3)
if car_params.steerControlType != car.CarParams.SteerControlType.angle:
tuning = car_params.lateralTuning.which()

@ -121,7 +121,6 @@ class TestCarModelBase(unittest.TestCase):
# make sure car params are within a valid range
self.assertGreater(self.CP.mass, 1)
self.assertGreater(self.CP.steerRateCost, 1e-3)
if self.CP.steerControlType != car.CarParams.SteerControlType.angle:
tuning = self.CP.lateralTuning.which()

@ -213,7 +213,6 @@ class CarInterface(CarInterfaceBase):
ret.mass = 4305. * CV.LB_TO_KG + STD_CARGO_KG
set_lat_tune(ret.lateralTuning, LatTunes.PID_J)
ret.steerRateCost = 1.
ret.centerToFront = ret.wheelbase * 0.44
# TODO: get actual value, for now starting with reasonable value for

@ -45,7 +45,6 @@ class CarInterface(CarInterfaceBase):
# Global lateral tuning defaults, can be overridden per-vehicle
ret.steerActuatorDelay = 0.1
ret.steerRateCost = 1.0
ret.steerLimitTimer = 0.4
ret.steerRatio = 15.6 # Let the params learner figure this out
tire_stiffness_factor = 1.0 # Let the params learner figure this out

@ -11,13 +11,12 @@ from cereal import log
class LateralPlanner:
def __init__(self, CP, use_lanelines=True, wide_camera=False):
def __init__(self, use_lanelines=True, wide_camera=False):
self.use_lanelines = use_lanelines
self.LP = LanePlanner(wide_camera)
self.DH = DesireHelper()
self.last_cloudlog_t = 0
self.steer_rate_cost = CP.steerRateCost
self.solution_invalid_cnt = 0
self.path_xyz = np.zeros((TRAJECTORY_SIZE, 3))
@ -59,12 +58,12 @@ class LateralPlanner:
# Calculate final driving path and set MPC costs
if self.use_lanelines:
d_path_xyz = self.LP.get_d_path(v_ego, self.t_idxs, self.path_xyz)
self.lat_mpc.set_weights(MPC_COST_LAT.PATH, MPC_COST_LAT.HEADING, self.steer_rate_cost)
self.lat_mpc.set_weights(MPC_COST_LAT.PATH, MPC_COST_LAT.HEADING, MPC_COST_LAT.STEER_RATE)
else:
d_path_xyz = self.path_xyz
# Heading cost is useful at low speed, otherwise end of plan can be off-heading
heading_cost = interp(v_ego, [5.0, 10.0], [MPC_COST_LAT.HEADING, 0.15])
self.lat_mpc.set_weights(MPC_COST_LAT.PATH, heading_cost, self.steer_rate_cost)
self.lat_mpc.set_weights(MPC_COST_LAT.PATH, heading_cost, MPC_COST_LAT.STEER_RATE)
y_pts = np.interp(v_ego * self.t_idxs[:LAT_MPC_N + 1], np.linalg.norm(d_path_xyz, axis=1), d_path_xyz[:, 1])
heading_pts = np.interp(v_ego * self.t_idxs[:LAT_MPC_N + 1], np.linalg.norm(self.path_xyz, axis=1), self.plan_yaw)

@ -22,7 +22,7 @@ def plannerd_thread(sm=None, pm=None):
cloudlog.event("e2e mode", on=use_lanelines)
longitudinal_planner = Planner(CP)
lateral_planner = LateralPlanner(CP, use_lanelines=use_lanelines, wide_camera=wide_camera)
lateral_planner = LateralPlanner(use_lanelines=use_lanelines, wide_camera=wide_camera)
if sm is None:
sm = messaging.SubMaster(['carState', 'controlsState', 'radarState', 'modelV2'],

@ -245,7 +245,7 @@ struct ModelOutput {
constexpr int OUTPUT_SIZE = sizeof(ModelOutput) / sizeof(float);
#ifdef TEMPORAL
constexpr int TEMPORAL_SIZE = 512;
constexpr int TEMPORAL_SIZE = 512+256;
#else
constexpr int TEMPORAL_SIZE = 0;
#endif

@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:027cbb1fabae369878271cb0e3505071a8bdaa07473fad9a0b2e8d695c5dc1ff
size 76725611
oid sha256:4c2cb3a3054f3292bbe538d6b793908dc2e234c200802d41b6766d3cb51b0b44
size 101662751

@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:484976ea5bd4ddcabc82e95faf30d7311a27802c1e337472558699fa2395a499
size 77472267
oid sha256:96b60d0bfd1386c93b4f79195aa1c5e77b23e0250578a308ee2c58857ed5eb49
size 102570834

@ -5,7 +5,7 @@
#include "selfdrive/modeld/thneed/thneed.h"
#include "system/hardware/hw.h"
#define TEMPORAL_SIZE 512
#define TEMPORAL_SIZE 512+256
#define DESIRE_LEN 8
#define TRAFFIC_CONVENTION_LEN 2

@ -9,7 +9,7 @@
extern map<cl_program, string> g_program_source;
static int is_same_size_image(cl_mem a, cl_mem b) {
/*static int is_same_size_image(cl_mem a, cl_mem b) {
size_t a_width, a_height, a_depth, a_array_size, a_row_pitch, a_slice_pitch;
clGetImageInfo(a, CL_IMAGE_WIDTH, sizeof(a_width), &a_width, NULL);
clGetImageInfo(a, CL_IMAGE_HEIGHT, sizeof(a_height), &a_height, NULL);
@ -29,7 +29,7 @@ static int is_same_size_image(cl_mem a, cl_mem b) {
return (a_width == b_width) && (a_height == b_height) &&
(a_depth == b_depth) && (a_array_size == b_array_size) &&
(a_row_pitch == b_row_pitch) && (a_slice_pitch == b_slice_pitch);
}
}*/
static cl_mem make_image_like(cl_context context, cl_mem val) {
cl_image_format format;
@ -138,7 +138,7 @@ int Thneed::optimize() {
// delete useless copy layers
// saves ~0.7 ms
if (kq[i]->name == "concatenation" || kq[i]->name == "flatten") {
/*if (kq[i]->name == "concatenation" || kq[i]->name == "flatten") {
string in = kq[i]->args[kq[i]->get_arg_num("input")];
string out = kq[i]->args[kq[i]->get_arg_num("output")];
if (is_same_size_image(*(cl_mem*)in.data(), *(cl_mem*)out.data())) {
@ -148,7 +148,7 @@ int Thneed::optimize() {
kq.erase(kq.begin()+i); --i;
}
}
}*/
// NOTE: if activations/accumulation are done in the wrong order, this will be wrong

@ -1 +1 @@
512a9d4596c8faba304d6f7ded2ce77837357b65
629eaa7b26d1721a71547f9de880f99732cb27f3

@ -1 +1 @@
1d66eed104dbc124c4e5679f5dddf40197b86ce9
ed1dfb8b155ebcd8fdad4e06462b3bb7869fc67b

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