Steam Powered model (#36000)

* f3e67f3e-6079-48cf-92a4-dee5eebd1d73/360

* f3e67f3e-6079-48cf-92a4-dee5eebd1d73/400

* No more action head: a8f96b93-bde2-4e28-a732-4df21ebba968/400

selfdrive/modeld/modeld.py

@@ -102,15 +102,12 @@ class ModelState:
 
     self.full_features_buffer = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN,  ModelConstants.FEATURE_LEN), dtype=np.float32)
     self.full_desire = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32)
-    self.full_prev_desired_curv = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32)
     self.temporal_idxs = slice(-1-(ModelConstants.TEMPORAL_SKIP*(ModelConstants.INPUT_HISTORY_BUFFER_LEN-1)), None, ModelConstants.TEMPORAL_SKIP)
 
     # policy inputs
     self.numpy_inputs = {
       'desire': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32),
       'traffic_convention': np.zeros((1, ModelConstants.TRAFFIC_CONVENTION_LEN), dtype=np.float32),
-      'lateral_control_params': np.zeros((1, ModelConstants.LATERAL_CONTROL_PARAMS_LEN), dtype=np.float32),
-      'prev_desired_curv': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32),
       'features_buffer': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN,  ModelConstants.FEATURE_LEN), dtype=np.float32),
     }
 
@@ -143,7 +140,6 @@ class ModelState:
     self.numpy_inputs['desire'][:] = self.full_desire.reshape((1,ModelConstants.INPUT_HISTORY_BUFFER_LEN,ModelConstants.TEMPORAL_SKIP,-1)).max(axis=2)
 
     self.numpy_inputs['traffic_convention'][:] = inputs['traffic_convention']
-    self.numpy_inputs['lateral_control_params'][:] = inputs['lateral_control_params']
     imgs_cl = {name: self.frames[name].prepare(bufs[name], transforms[name].flatten()) for name in self.vision_input_names}
 
     if TICI and not USBGPU:
@@ -169,11 +165,6 @@ class ModelState:
     self.policy_output = self.policy_run(**self.policy_inputs).contiguous().realize().uop.base.buffer.numpy()
     policy_outputs_dict = self.parser.parse_policy_outputs(self.slice_outputs(self.policy_output, self.policy_output_slices))
 
-    # TODO model only uses last value now
-    self.full_prev_desired_curv[0,:-1] = self.full_prev_desired_curv[0,1:]
-    self.full_prev_desired_curv[0,-1,:] = policy_outputs_dict['desired_curvature'][0, :]
-    self.numpy_inputs['prev_desired_curv'][:] = 0*self.full_prev_desired_curv[0, self.temporal_idxs]
-
     combined_outputs_dict = {**vision_outputs_dict, **policy_outputs_dict}
     if SEND_RAW_PRED:
       combined_outputs_dict['raw_pred'] = np.concatenate([self.vision_output.copy(), self.policy_output.copy()])
@@ -292,7 +283,6 @@ def main(demo=False):
     frame_id = sm["roadCameraState"].frameId
     v_ego = max(sm["carState"].vEgo, 0.)
     lat_delay = sm["liveDelay"].lateralDelay + LAT_SMOOTH_SECONDS
-    lateral_control_params = np.array([v_ego, lat_delay], dtype=np.float32)
     if sm.updated["liveCalibration"] and sm.seen['roadCameraState'] and sm.seen['deviceState']:
       device_from_calib_euler = np.array(sm["liveCalibration"].rpyCalib, dtype=np.float32)
       dc = DEVICE_CAMERAS[(str(sm['deviceState'].deviceType), str(sm['roadCameraState'].sensor))]
@@ -325,7 +315,6 @@ def main(demo=False):
     inputs:dict[str, np.ndarray] = {
       'desire': vec_desire,
       'traffic_convention': traffic_convention,
-      'lateral_control_params': lateral_control_params,
     }
 
     mt1 = time.perf_counter()

selfdrive/modeld/models/driving_policy.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1af87c38492444521632a0e75839b5684ee46bf255b3474773784bffb9fe4f57
-size 15583374
+oid sha256:04b763fb71efe57a8a4c4168a8043ecd58939015026ded0dc755ded6905ac251
+size 12343523

selfdrive/modeld/models/driving_vision.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c824f68646a3b94f117f01c70dc8316fb466e05fbd42ccdba440b8a8dc86914b
-size 46265993
+oid sha256:e66bb8d53eced3786ed71a59b55ffc6810944cb217f0518621cc76303260a1ef
+size 46271991