diff --git a/selfdrive/modeld/modeld.py b/selfdrive/modeld/modeld.py index 707b221bb9..8bc8bf01ab 100755 --- a/selfdrive/modeld/modeld.py +++ b/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() diff --git a/selfdrive/modeld/models/driving_policy.onnx b/selfdrive/modeld/models/driving_policy.onnx index 267fc92a3f..867a0d3b9b 100644 --- a/selfdrive/modeld/models/driving_policy.onnx +++ b/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 diff --git a/selfdrive/modeld/models/driving_vision.onnx b/selfdrive/modeld/models/driving_vision.onnx index 18f63358db..ce0dc927e7 100644 --- a/selfdrive/modeld/models/driving_vision.onnx +++ b/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