diff --git a/.gitattributes b/.gitattributes index 69c40549a..df3fc49ed 100644 --- a/.gitattributes +++ b/.gitattributes @@ -3,8 +3,6 @@ # to move existing files into LFS: # git add --renormalize . *.onnx filter=lfs diff=lfs merge=lfs -text -*.thneed filter=lfs diff=lfs merge=lfs -text -*.pkl filter=lfs diff=lfs merge=lfs -text *.svg filter=lfs diff=lfs merge=lfs -text *.png filter=lfs diff=lfs merge=lfs -text *.gif filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore index f05911aef..a58a46fef 100644 --- a/.gitignore +++ b/.gitignore @@ -74,7 +74,6 @@ comma*.sh selfdrive/modeld/thneed/compile selfdrive/modeld/models/*.thneed selfdrive/modeld/models/*.pkl -sunnypilot/modeld/thneed/compile *.bz2 *.zst diff --git a/.gitmodules b/.gitmodules index f1f7c400d..10fa733cf 100644 --- a/.gitmodules +++ b/.gitmodules @@ -15,4 +15,4 @@ url = https://github.com/commaai/teleoprtc [submodule "tinygrad"] path = tinygrad_repo - url = https://github.com/commaai/tinygrad.git + url = https://github.com/tinygrad/tinygrad.git \ No newline at end of file diff --git a/SConstruct b/SConstruct index c07ed7ace..39f7d14d0 100644 --- a/SConstruct +++ b/SConstruct @@ -396,8 +396,6 @@ SConscript(['third_party/SConscript']) SConscript(['selfdrive/SConscript']) -SConscript(['sunnypilot/SConscript']) - if Dir('#tools/cabana/').exists() and GetOption('extras'): SConscript(['tools/replay/SConscript']) if arch != "larch64": diff --git a/cereal/custom.capnp b/cereal/custom.capnp index 5007d0675..b2575256d 100644 --- a/cereal/custom.capnp +++ b/cereal/custom.capnp @@ -64,11 +64,6 @@ struct ModelManagerSP @0xaedffd8f31e7b55d { progress @1 :Float32; eta @2 :UInt32; } - - enum Runner { - snpe @0; - tinygrad @1; - } struct ModelBundle { index @0 :UInt32; diff --git a/pyproject.toml b/pyproject.toml index a4782e229..7a889584a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -137,7 +137,7 @@ allow-direct-references = true [tool.pytest.ini_options] minversion = "6.0" -addopts = "--ignore=openpilot/ --ignore=opendbc/ --ignore=panda/ --ignore=rednose_repo/ --ignore=tinygrad_repo/ --ignore=teleoprtc_repo/ --ignore=msgq/ --ignore=sunnypilot/tinygrad_repo/ -Werror --strict-config --strict-markers --durations=10 -n auto --dist=loadgroup" +addopts = "--ignore=openpilot/ --ignore=opendbc/ --ignore=panda/ --ignore=rednose_repo/ --ignore=tinygrad_repo/ --ignore=teleoprtc_repo/ --ignore=msgq/ -Werror --strict-config --strict-markers --durations=10 -n auto --dist=loadgroup" cpp_files = "test_*" cpp_harness = "selfdrive/test/cpp_harness.py" python_files = "test_*.py" diff --git a/sunnypilot/SConscript b/sunnypilot/SConscript deleted file mode 100644 index 8bc5b84ef..000000000 --- a/sunnypilot/SConscript +++ /dev/null @@ -1 +0,0 @@ -SConscript(['modeld/SConscript']) \ No newline at end of file diff --git a/sunnypilot/modeld/.gitignore b/sunnypilot/modeld/.gitignore deleted file mode 100644 index 742d3d120..000000000 --- a/sunnypilot/modeld/.gitignore +++ /dev/null @@ -1 +0,0 @@ -*_pyx.cpp diff --git a/sunnypilot/modeld/SConscript b/sunnypilot/modeld/SConscript deleted file mode 100644 index a979c2161..000000000 --- a/sunnypilot/modeld/SConscript +++ /dev/null @@ -1,58 +0,0 @@ -import glob - -Import('env', 'envCython', 'arch', 'cereal', 'messaging', 'common', 'gpucommon', 'visionipc', 'transformations') -lenv = env.Clone() -lenvCython = envCython.Clone() - -libs = [cereal, messaging, visionipc, gpucommon, common, 'capnp', 'kj', 'pthread'] -frameworks = [] - -common_src = [ - "models/commonmodel.cc", - "transforms/loadyuv.cc", - "transforms/transform.cc", -] - -thneed_src_common = [ - "thneed/thneed_common.cc", - "thneed/serialize.cc", -] - -thneed_src_qcom = thneed_src_common + ["thneed/thneed_qcom2.cc"] -thneed_src_pc = thneed_src_common + ["thneed/thneed_pc.cc"] -thneed_src = thneed_src_qcom if arch == "larch64" else thneed_src_pc - -# SNPE except on Mac and ARM Linux -snpe_lib = [] -if arch != "Darwin" and arch != "aarch64": - common_src += ['runners/snpemodel.cc'] - snpe_lib += ['SNPE'] - -# OpenCL is a framework on Mac -if arch == "Darwin": - frameworks += ['OpenCL'] -else: - libs += ['OpenCL'] - -# Set path definitions -for pathdef, fn in {'TRANSFORM': 'transforms/transform.cl', 'LOADYUV': 'transforms/loadyuv.cl'}.items(): - for xenv in (lenv, lenvCython): - xenv['CXXFLAGS'].append(f'-D{pathdef}_PATH=\\"{File(fn).abspath}\\"') - -# Compile cython -snpe_rpath_qcom = "/data/pythonpath/third_party/snpe/larch64" -snpe_rpath_pc = f"{Dir('#').abspath}/third_party/snpe/x86_64-linux-clang" -snpe_rpath = lenvCython['RPATH'] + [snpe_rpath_qcom if arch == "larch64" else snpe_rpath_pc] - -cython_libs = envCython["LIBS"] + libs -snpemodel_lib = lenv.Library('snpemodel', ['runners/snpemodel.cc']) -commonmodel_lib = lenv.Library('commonmodel', common_src) - -lenvCython.Program('runners/runmodel_pyx.so', 'runners/runmodel_pyx.pyx', LIBS=cython_libs, FRAMEWORKS=frameworks) -lenvCython.Program('runners/snpemodel_pyx.so', 'runners/snpemodel_pyx.pyx', LIBS=[snpemodel_lib, snpe_lib, *cython_libs], FRAMEWORKS=frameworks, RPATH=snpe_rpath) -lenvCython.Program('models/commonmodel_pyx.so', 'models/commonmodel_pyx.pyx', LIBS=[commonmodel_lib, *cython_libs], FRAMEWORKS=frameworks) - -if arch == 'larch64' or GetOption('pc_thneed'): - thneed_lib = env.SharedLibrary('thneed', thneed_src, LIBS=[gpucommon, common, 'OpenCL', 'dl']) - thneedmodel_lib = env.Library('thneedmodel', ['runners/thneedmodel.cc']) - lenvCython.Program('runners/thneedmodel_pyx.so', 'runners/thneedmodel_pyx.pyx', LIBS=envCython["LIBS"]+[thneedmodel_lib, thneed_lib, gpucommon, common, 'dl', 'OpenCL']) diff --git a/sunnypilot/modeld/__init__.py b/sunnypilot/modeld/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/sunnypilot/modeld/constants.py b/sunnypilot/modeld/constants.py deleted file mode 100644 index bf74c2d1a..000000000 --- a/sunnypilot/modeld/constants.py +++ /dev/null @@ -1,86 +0,0 @@ -import numpy as np - -def index_function(idx, max_val=192, max_idx=32): - return (max_val) * ((idx/max_idx)**2) - -class ModelConstants: - # time and distance indices - IDX_N = 33 - T_IDXS = [index_function(idx, max_val=10.0) for idx in range(IDX_N)] - X_IDXS = [index_function(idx, max_val=192.0) for idx in range(IDX_N)] - LEAD_T_IDXS = [0., 2., 4., 6., 8., 10.] - LEAD_T_OFFSETS = [0., 2., 4.] - META_T_IDXS = [2., 4., 6., 8., 10.] - - # model inputs constants - MODEL_FREQ = 20 - FEATURE_LEN = 512 - FULL_HISTORY_BUFFER_LEN = 99 - HISTORY_BUFFER_LEN = 24 - DESIRE_LEN = 8 - TRAFFIC_CONVENTION_LEN = 2 - LAT_PLANNER_STATE_LEN = 4 - LATERAL_CONTROL_PARAMS_LEN = 2 - PREV_DESIRED_CURV_LEN = 1 - - # model outputs constants - FCW_THRESHOLDS_5MS2 = np.array([.05, .05, .15, .15, .15], dtype=np.float32) - FCW_THRESHOLDS_3MS2 = np.array([.7, .7], dtype=np.float32) - FCW_5MS2_PROBS_WIDTH = 5 - FCW_3MS2_PROBS_WIDTH = 2 - - DISENGAGE_WIDTH = 5 - POSE_WIDTH = 6 - WIDE_FROM_DEVICE_WIDTH = 3 - SIM_POSE_WIDTH = 6 - LEAD_WIDTH = 4 - LANE_LINES_WIDTH = 2 - ROAD_EDGES_WIDTH = 2 - PLAN_WIDTH = 15 - DESIRE_PRED_WIDTH = 8 - LAT_PLANNER_SOLUTION_WIDTH = 4 - DESIRED_CURV_WIDTH = 1 - - NUM_LANE_LINES = 4 - NUM_ROAD_EDGES = 2 - - LEAD_TRAJ_LEN = 6 - DESIRE_PRED_LEN = 4 - - PLAN_MHP_N = 5 - LEAD_MHP_N = 2 - PLAN_MHP_SELECTION = 1 - LEAD_MHP_SELECTION = 3 - - FCW_THRESHOLD_5MS2_HIGH = 0.15 - FCW_THRESHOLD_5MS2_LOW = 0.05 - FCW_THRESHOLD_3MS2 = 0.7 - - CONFIDENCE_BUFFER_LEN = 5 - RYG_GREEN = 0.01165 - RYG_YELLOW = 0.06157 - - POLY_PATH_DEGREE = 4 - -# model outputs slices -class Plan: - POSITION = slice(0, 3) - VELOCITY = slice(3, 6) - ACCELERATION = slice(6, 9) - T_FROM_CURRENT_EULER = slice(9, 12) - ORIENTATION_RATE = slice(12, 15) - -class Meta: - ENGAGED = slice(0, 1) - # next 2, 4, 6, 8, 10 seconds - GAS_DISENGAGE = slice(1, 31, 6) - BRAKE_DISENGAGE = slice(2, 31, 6) - STEER_OVERRIDE = slice(3, 31, 6) - HARD_BRAKE_3 = slice(4, 31, 6) - HARD_BRAKE_4 = slice(5, 31, 6) - HARD_BRAKE_5 = slice(6, 31, 6) - # next 0, 2, 4, 6, 8, 10 seconds - GAS_PRESS = slice(31, 55, 4) - BRAKE_PRESS = slice(32, 55, 4) - LEFT_BLINKER = slice(33, 55, 4) - RIGHT_BLINKER = slice(34, 55, 4) diff --git a/sunnypilot/modeld/fill_model_msg.py b/sunnypilot/modeld/fill_model_msg.py deleted file mode 100644 index 875f823d7..000000000 --- a/sunnypilot/modeld/fill_model_msg.py +++ /dev/null @@ -1,237 +0,0 @@ -import os -import capnp -import numpy as np -from cereal import log -from openpilot.sunnypilot.modeld.constants import ModelConstants, Plan, Meta -from openpilot.selfdrive.controls.lib.drive_helpers import MIN_SPEED - -SEND_RAW_PRED = os.getenv('SEND_RAW_PRED') - -ConfidenceClass = log.ModelDataV2.ConfidenceClass - -def curv_from_psis(psi_target, psi_rate, vego, delay): - vego = np.clip(vego, MIN_SPEED, np.inf) - curv_from_psi = psi_target / (vego * delay) # epsilon to prevent divide-by-zero - return 2*curv_from_psi - psi_rate / vego - -def get_curvature_from_plan(plan, vego, delay): - psi_target = np.interp(delay, ModelConstants.T_IDXS, plan[:, Plan.T_FROM_CURRENT_EULER][:, 2]) - psi_rate = plan[:, Plan.ORIENTATION_RATE][0, 2] - return curv_from_psis(psi_target, psi_rate, vego, delay) - -class PublishState: - def __init__(self): - self.disengage_buffer = np.zeros(ModelConstants.CONFIDENCE_BUFFER_LEN*ModelConstants.DISENGAGE_WIDTH, dtype=np.float32) - self.prev_brake_5ms2_probs = np.zeros(ModelConstants.FCW_5MS2_PROBS_WIDTH, dtype=np.float32) - self.prev_brake_3ms2_probs = np.zeros(ModelConstants.FCW_3MS2_PROBS_WIDTH, dtype=np.float32) - -def fill_xyzt(builder, t, x, y, z, x_std=None, y_std=None, z_std=None): - builder.t = t - builder.x = x.tolist() - builder.y = y.tolist() - builder.z = z.tolist() - if x_std is not None: - builder.xStd = x_std.tolist() - if y_std is not None: - builder.yStd = y_std.tolist() - if z_std is not None: - builder.zStd = z_std.tolist() - -def fill_xyvat(builder, t, x, y, v, a, x_std=None, y_std=None, v_std=None, a_std=None): - builder.t = t - builder.x = x.tolist() - builder.y = y.tolist() - builder.v = v.tolist() - builder.a = a.tolist() - if x_std is not None: - builder.xStd = x_std.tolist() - if y_std is not None: - builder.yStd = y_std.tolist() - if v_std is not None: - builder.vStd = v_std.tolist() - if a_std is not None: - builder.aStd = a_std.tolist() - -def fill_xyz_poly(builder, degree, x, y, z): - xyz = np.stack([x, y, z], axis=1) - coeffs = np.polynomial.polynomial.polyfit(ModelConstants.T_IDXS, xyz, deg=degree) - builder.xCoefficients = coeffs[:, 0].tolist() - builder.yCoefficients = coeffs[:, 1].tolist() - builder.zCoefficients = coeffs[:, 2].tolist() - -def fill_lane_line_meta(builder, lane_lines, lane_line_probs): - builder.leftY = lane_lines[1].y[0] - builder.leftProb = lane_line_probs[1] - builder.rightY = lane_lines[2].y[0] - builder.rightProb = lane_line_probs[2] - -def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._DynamicStructBuilder, - net_output_data: dict[str, np.ndarray], v_ego: float, delay: float, - publish_state: PublishState, vipc_frame_id: int, vipc_frame_id_extra: int, - frame_id: int, frame_drop: float, timestamp_eof: int, model_execution_time: float, - valid: bool) -> None: - frame_age = frame_id - vipc_frame_id if frame_id > vipc_frame_id else 0 - frame_drop_perc = frame_drop * 100 - extended_msg.valid = valid - base_msg.valid = valid - - desired_curv = float(get_curvature_from_plan(net_output_data['plan'][0], v_ego, delay)) - - driving_model_data = base_msg.drivingModelData - - driving_model_data.frameId = vipc_frame_id - driving_model_data.frameIdExtra = vipc_frame_id_extra - driving_model_data.frameDropPerc = frame_drop_perc - driving_model_data.modelExecutionTime = model_execution_time - - action = driving_model_data.action - action.desiredCurvature = desired_curv - - modelV2 = extended_msg.modelV2 - modelV2.frameId = vipc_frame_id - modelV2.frameIdExtra = vipc_frame_id_extra - modelV2.frameAge = frame_age - modelV2.frameDropPerc = frame_drop_perc - modelV2.timestampEof = timestamp_eof - modelV2.modelExecutionTime = model_execution_time - - # plan - position = modelV2.position - fill_xyzt(position, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.POSITION].T, *net_output_data['plan_stds'][0,:,Plan.POSITION].T) - velocity = modelV2.velocity - fill_xyzt(velocity, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.VELOCITY].T) - acceleration = modelV2.acceleration - fill_xyzt(acceleration, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.ACCELERATION].T) - orientation = modelV2.orientation - fill_xyzt(orientation, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.T_FROM_CURRENT_EULER].T) - orientation_rate = modelV2.orientationRate - fill_xyzt(orientation_rate, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.ORIENTATION_RATE].T) - - # temporal pose - temporal_pose = modelV2.temporalPose - temporal_pose.trans = net_output_data['plan'][0,0,Plan.VELOCITY].tolist() - temporal_pose.transStd = net_output_data['plan_stds'][0,0,Plan.VELOCITY].tolist() - temporal_pose.rot = net_output_data['plan'][0,0,Plan.ORIENTATION_RATE].tolist() - temporal_pose.rotStd = net_output_data['plan_stds'][0,0,Plan.ORIENTATION_RATE].tolist() - - # poly path - poly_path = driving_model_data.path - fill_xyz_poly(poly_path, ModelConstants.POLY_PATH_DEGREE, *net_output_data['plan'][0,:,Plan.POSITION].T) - - # lateral planning - action = modelV2.action - action.desiredCurvature = desired_curv - - # times at X_IDXS according to model plan - PLAN_T_IDXS = [np.nan] * ModelConstants.IDX_N - PLAN_T_IDXS[0] = 0.0 - plan_x = net_output_data['plan'][0,:,Plan.POSITION][:,0].tolist() - for xidx in range(1, ModelConstants.IDX_N): - tidx = 0 - # increment tidx until we find an element that's further away than the current xidx - while tidx < ModelConstants.IDX_N - 1 and plan_x[tidx+1] < ModelConstants.X_IDXS[xidx]: - tidx += 1 - if tidx == ModelConstants.IDX_N - 1: - # if the Plan doesn't extend far enough, set plan_t to the max value (10s), then break - PLAN_T_IDXS[xidx] = ModelConstants.T_IDXS[ModelConstants.IDX_N - 1] - break - # interpolate to find `t` for the current xidx - current_x_val = plan_x[tidx] - next_x_val = plan_x[tidx+1] - p = (ModelConstants.X_IDXS[xidx] - current_x_val) / (next_x_val - current_x_val) if abs(next_x_val - current_x_val) > 1e-9 else float('nan') - PLAN_T_IDXS[xidx] = p * ModelConstants.T_IDXS[tidx+1] + (1 - p) * ModelConstants.T_IDXS[tidx] - - # lane lines - modelV2.init('laneLines', 4) - for i in range(4): - lane_line = modelV2.laneLines[i] - fill_xyzt(lane_line, PLAN_T_IDXS, np.array(ModelConstants.X_IDXS), net_output_data['lane_lines'][0,i,:,0], net_output_data['lane_lines'][0,i,:,1]) - modelV2.laneLineStds = net_output_data['lane_lines_stds'][0,:,0,0].tolist() - modelV2.laneLineProbs = net_output_data['lane_lines_prob'][0,1::2].tolist() - - lane_line_meta = driving_model_data.laneLineMeta - fill_lane_line_meta(lane_line_meta, modelV2.laneLines, modelV2.laneLineProbs) - - # road edges - modelV2.init('roadEdges', 2) - for i in range(2): - road_edge = modelV2.roadEdges[i] - fill_xyzt(road_edge, PLAN_T_IDXS, np.array(ModelConstants.X_IDXS), net_output_data['road_edges'][0,i,:,0], net_output_data['road_edges'][0,i,:,1]) - modelV2.roadEdgeStds = net_output_data['road_edges_stds'][0,:,0,0].tolist() - - # leads - modelV2.init('leadsV3', 3) - for i in range(3): - lead = modelV2.leadsV3[i] - fill_xyvat(lead, ModelConstants.LEAD_T_IDXS, *net_output_data['lead'][0,i].T, *net_output_data['lead_stds'][0,i].T) - lead.prob = net_output_data['lead_prob'][0,i].tolist() - lead.probTime = ModelConstants.LEAD_T_OFFSETS[i] - - # meta - meta = modelV2.meta - meta.desireState = net_output_data['desire_state'][0].reshape(-1).tolist() - meta.desirePrediction = net_output_data['desire_pred'][0].reshape(-1).tolist() - meta.engagedProb = net_output_data['meta'][0,Meta.ENGAGED].item() - meta.init('disengagePredictions') - disengage_predictions = meta.disengagePredictions - disengage_predictions.t = ModelConstants.META_T_IDXS - disengage_predictions.brakeDisengageProbs = net_output_data['meta'][0,Meta.BRAKE_DISENGAGE].tolist() - disengage_predictions.gasDisengageProbs = net_output_data['meta'][0,Meta.GAS_DISENGAGE].tolist() - disengage_predictions.steerOverrideProbs = net_output_data['meta'][0,Meta.STEER_OVERRIDE].tolist() - disengage_predictions.brake3MetersPerSecondSquaredProbs = net_output_data['meta'][0,Meta.HARD_BRAKE_3].tolist() - disengage_predictions.brake4MetersPerSecondSquaredProbs = net_output_data['meta'][0,Meta.HARD_BRAKE_4].tolist() - disengage_predictions.brake5MetersPerSecondSquaredProbs = net_output_data['meta'][0,Meta.HARD_BRAKE_5].tolist() - disengage_predictions.gasPressProbs = net_output_data['meta'][0,Meta.GAS_PRESS].tolist() - disengage_predictions.brakePressProbs = net_output_data['meta'][0,Meta.BRAKE_PRESS].tolist() - - publish_state.prev_brake_5ms2_probs[:-1] = publish_state.prev_brake_5ms2_probs[1:] - publish_state.prev_brake_5ms2_probs[-1] = net_output_data['meta'][0,Meta.HARD_BRAKE_5][0] - publish_state.prev_brake_3ms2_probs[:-1] = publish_state.prev_brake_3ms2_probs[1:] - publish_state.prev_brake_3ms2_probs[-1] = net_output_data['meta'][0,Meta.HARD_BRAKE_3][0] - hard_brake_predicted = (publish_state.prev_brake_5ms2_probs > ModelConstants.FCW_THRESHOLDS_5MS2).all() and \ - (publish_state.prev_brake_3ms2_probs > ModelConstants.FCW_THRESHOLDS_3MS2).all() - meta.hardBrakePredicted = hard_brake_predicted.item() - - # confidence - if vipc_frame_id % (2*ModelConstants.MODEL_FREQ) == 0: - # any disengage prob - brake_disengage_probs = net_output_data['meta'][0,Meta.BRAKE_DISENGAGE] - gas_disengage_probs = net_output_data['meta'][0,Meta.GAS_DISENGAGE] - steer_override_probs = net_output_data['meta'][0,Meta.STEER_OVERRIDE] - any_disengage_probs = 1-((1-brake_disengage_probs)*(1-gas_disengage_probs)*(1-steer_override_probs)) - # independent disengage prob for each 2s slice - ind_disengage_probs = np.r_[any_disengage_probs[0], np.diff(any_disengage_probs) / (1 - any_disengage_probs[:-1])] - # rolling buf for 2, 4, 6, 8, 10s - publish_state.disengage_buffer[:-ModelConstants.DISENGAGE_WIDTH] = publish_state.disengage_buffer[ModelConstants.DISENGAGE_WIDTH:] - publish_state.disengage_buffer[-ModelConstants.DISENGAGE_WIDTH:] = ind_disengage_probs - - score = 0. - for i in range(ModelConstants.DISENGAGE_WIDTH): - score += publish_state.disengage_buffer[i*ModelConstants.DISENGAGE_WIDTH+ModelConstants.DISENGAGE_WIDTH-1-i].item() / ModelConstants.DISENGAGE_WIDTH - if score < ModelConstants.RYG_GREEN: - modelV2.confidence = ConfidenceClass.green - elif score < ModelConstants.RYG_YELLOW: - modelV2.confidence = ConfidenceClass.yellow - else: - modelV2.confidence = ConfidenceClass.red - - # raw prediction if enabled - if SEND_RAW_PRED: - modelV2.rawPredictions = net_output_data['raw_pred'].tobytes() - -def fill_pose_msg(msg: capnp._DynamicStructBuilder, net_output_data: dict[str, np.ndarray], - vipc_frame_id: int, vipc_dropped_frames: int, timestamp_eof: int, live_calib_seen: bool) -> None: - msg.valid = live_calib_seen & (vipc_dropped_frames < 1) - cameraOdometry = msg.cameraOdometry - - cameraOdometry.frameId = vipc_frame_id - cameraOdometry.timestampEof = timestamp_eof - - cameraOdometry.trans = net_output_data['pose'][0,:3].tolist() - cameraOdometry.rot = net_output_data['pose'][0,3:].tolist() - cameraOdometry.wideFromDeviceEuler = net_output_data['wide_from_device_euler'][0,:].tolist() - cameraOdometry.roadTransformTrans = net_output_data['road_transform'][0,:3].tolist() - cameraOdometry.transStd = net_output_data['pose_stds'][0,:3].tolist() - cameraOdometry.rotStd = net_output_data['pose_stds'][0,3:].tolist() - cameraOdometry.wideFromDeviceEulerStd = net_output_data['wide_from_device_euler_stds'][0,:].tolist() - cameraOdometry.roadTransformTransStd = net_output_data['road_transform_stds'][0,:3].tolist() diff --git a/sunnypilot/modeld/get_model_metadata.py b/sunnypilot/modeld/get_model_metadata.py deleted file mode 100755 index 144860204..000000000 --- a/sunnypilot/modeld/get_model_metadata.py +++ /dev/null @@ -1,28 +0,0 @@ -#!/usr/bin/env python3 -import sys -import pathlib -import onnx -import codecs -import pickle - -def get_name_and_shape(value_info:onnx.ValueInfoProto) -> tuple[str, tuple[int,...]]: - shape = tuple([int(dim.dim_value) for dim in value_info.type.tensor_type.shape.dim]) - name = value_info.name - return name, shape - -if __name__ == "__main__": - model_path = pathlib.Path(sys.argv[1]) - model = onnx.load(str(model_path)) - i = [x.key for x in model.metadata_props].index('output_slices') - output_slices = model.metadata_props[i].value - - metadata = {} - metadata['output_slices'] = pickle.loads(codecs.decode(output_slices.encode(), "base64")) - metadata['input_shapes'] = dict([get_name_and_shape(x) for x in model.graph.input]) - metadata['output_shapes'] = dict([get_name_and_shape(x) for x in model.graph.output]) - - metadata_path = model_path.parent / (model_path.stem + '_metadata.pkl') - with open(metadata_path, 'wb') as f: - pickle.dump(metadata, f) - - print(f'saved metadata to {metadata_path}') diff --git a/sunnypilot/modeld/modeld b/sunnypilot/modeld/modeld deleted file mode 100755 index e1cef4dcc..000000000 --- a/sunnypilot/modeld/modeld +++ /dev/null @@ -1,10 +0,0 @@ -#!/usr/bin/env bash - -DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" >/dev/null && pwd)" -cd "$DIR/../../" - -if [ -f "$DIR/libthneed.so" ]; then - export LD_PRELOAD="$DIR/libthneed.so" -fi - -exec "$DIR/modeld.py" "$@" diff --git a/sunnypilot/modeld/modeld.py b/sunnypilot/modeld/modeld.py deleted file mode 100755 index 1c14486e6..000000000 --- a/sunnypilot/modeld/modeld.py +++ /dev/null @@ -1,299 +0,0 @@ -#!/usr/bin/env python3 -import os -import time -import pickle -import numpy as np -import cereal.messaging as messaging -from cereal import car, log -from pathlib import Path -from setproctitle import setproctitle -from cereal.messaging import PubMaster, SubMaster -from msgq.visionipc import VisionIpcClient, VisionStreamType, VisionBuf -from opendbc.car.car_helpers import get_demo_car_params -from openpilot.common.swaglog import cloudlog -from openpilot.common.params import Params -from openpilot.common.filter_simple import FirstOrderFilter -from openpilot.common.realtime import config_realtime_process -from openpilot.common.transformations.camera import DEVICE_CAMERAS -from openpilot.common.transformations.model import get_warp_matrix -from openpilot.system import sentry -from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper -from openpilot.sunnypilot.modeld.runners import ModelRunner, Runtime -from openpilot.sunnypilot.modeld.parse_model_outputs import Parser -from openpilot.sunnypilot.modeld.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState -from openpilot.sunnypilot.modeld.constants import ModelConstants -from openpilot.sunnypilot.modeld.models.commonmodel_pyx import DrivingModelFrame, CLContext - -PROCESS_NAME = "sunnypilot.modeld.modeld" -SEND_RAW_PRED = os.getenv('SEND_RAW_PRED') - -MODEL_PATHS = { - ModelRunner.THNEED: Path(__file__).parent / 'models/supercombo.thneed', - ModelRunner.ONNX: Path(__file__).parent / 'models/supercombo.onnx'} - -METADATA_PATH = Path(__file__).parent / 'models/supercombo_metadata.pkl' - - -class FrameMeta: - frame_id: int = 0 - timestamp_sof: int = 0 - timestamp_eof: int = 0 - - def __init__(self, vipc=None): - if vipc is not None: - self.frame_id, self.timestamp_sof, self.timestamp_eof = vipc.frame_id, vipc.timestamp_sof, vipc.timestamp_eof - -class ModelState: - frame: DrivingModelFrame - wide_frame: DrivingModelFrame - inputs: dict[str, np.ndarray] - output: np.ndarray - prev_desire: np.ndarray # for tracking the rising edge of the pulse - model: ModelRunner - - def __init__(self, context: CLContext): - self.frame = DrivingModelFrame(context) - self.wide_frame = DrivingModelFrame(context) - self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32) - self.full_features_20Hz = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.FEATURE_LEN), dtype=np.float32) - self.desire_20Hz = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN + 1, ModelConstants.DESIRE_LEN), dtype=np.float32) - - # img buffers are managed in openCL transform code - self.inputs = { - 'desire': np.zeros(ModelConstants.DESIRE_LEN * (ModelConstants.HISTORY_BUFFER_LEN+1), dtype=np.float32), - 'traffic_convention': np.zeros(ModelConstants.TRAFFIC_CONVENTION_LEN, dtype=np.float32), - 'features_buffer': np.zeros(ModelConstants.HISTORY_BUFFER_LEN * ModelConstants.FEATURE_LEN, dtype=np.float32), - } - - with open(METADATA_PATH, 'rb') as f: - model_metadata = pickle.load(f) - - self.output_slices = model_metadata['output_slices'] - net_output_size = model_metadata['output_shapes']['outputs'][1] - self.output = np.zeros(net_output_size, dtype=np.float32) - self.parser = Parser() - - self.model = ModelRunner(MODEL_PATHS, self.output, Runtime.GPU, False, context) - self.model.addInput("input_imgs", None) - self.model.addInput("big_input_imgs", None) - for k,v in self.inputs.items(): - self.model.addInput(k, v) - - def slice_outputs(self, model_outputs: np.ndarray) -> dict[str, np.ndarray]: - parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in self.output_slices.items()} - if SEND_RAW_PRED: - parsed_model_outputs['raw_pred'] = model_outputs.copy() - return parsed_model_outputs - - def run(self, buf: VisionBuf, wbuf: VisionBuf, transform: np.ndarray, transform_wide: np.ndarray, - inputs: dict[str, np.ndarray], prepare_only: bool) -> dict[str, np.ndarray] | None: - # Model decides when action is completed, so desire input is just a pulse triggered on rising edge - inputs['desire'][0] = 0 - new_desire = np.where(inputs['desire'] - self.prev_desire > .99, inputs['desire'], 0) - self.prev_desire[:] = inputs['desire'] - - self.desire_20Hz[:-1] = self.desire_20Hz[1:] - self.desire_20Hz[-1] = new_desire - self.inputs['desire'][:] = self.desire_20Hz.reshape((25,4,-1)).max(axis=1).flatten() - - self.inputs['traffic_convention'][:] = inputs['traffic_convention'] - - self.model.setInputBuffer("input_imgs", self.frame.prepare(buf, transform.flatten(), self.model.getCLBuffer("input_imgs"))) - self.model.setInputBuffer("big_input_imgs", self.wide_frame.prepare(wbuf, transform_wide.flatten(), self.model.getCLBuffer("big_input_imgs"))) - - if prepare_only: - return None - - self.model.execute() - outputs = self.parser.parse_outputs(self.slice_outputs(self.output)) - - self.full_features_20Hz[:-1] = self.full_features_20Hz[1:] - self.full_features_20Hz[-1] = outputs['hidden_state'][0, :] - - idxs = np.arange(-4,-100,-4)[::-1] - self.inputs['features_buffer'][:] = self.full_features_20Hz[idxs].flatten() - return outputs - - -def main(demo=False): - cloudlog.warning("modeld init") - - sentry.set_tag("daemon", PROCESS_NAME) - cloudlog.bind(daemon=PROCESS_NAME) - setproctitle(PROCESS_NAME) - config_realtime_process(7, 54) - - cloudlog.warning("setting up CL context") - cl_context = CLContext() - cloudlog.warning("CL context ready; loading model") - model = ModelState(cl_context) - cloudlog.warning("models loaded, modeld starting") - - # visionipc clients - while True: - available_streams = VisionIpcClient.available_streams("camerad", block=False) - if available_streams: - use_extra_client = VisionStreamType.VISION_STREAM_WIDE_ROAD in available_streams and VisionStreamType.VISION_STREAM_ROAD in available_streams - main_wide_camera = VisionStreamType.VISION_STREAM_ROAD not in available_streams - break - time.sleep(.1) - - vipc_client_main_stream = VisionStreamType.VISION_STREAM_WIDE_ROAD if main_wide_camera else VisionStreamType.VISION_STREAM_ROAD - vipc_client_main = VisionIpcClient("camerad", vipc_client_main_stream, True, cl_context) - vipc_client_extra = VisionIpcClient("camerad", VisionStreamType.VISION_STREAM_WIDE_ROAD, False, cl_context) - cloudlog.warning(f"vision stream set up, main_wide_camera: {main_wide_camera}, use_extra_client: {use_extra_client}") - - while not vipc_client_main.connect(False): - time.sleep(0.1) - while use_extra_client and not vipc_client_extra.connect(False): - time.sleep(0.1) - - cloudlog.warning(f"connected main cam with buffer size: {vipc_client_main.buffer_len} ({vipc_client_main.width} x {vipc_client_main.height})") - if use_extra_client: - cloudlog.warning(f"connected extra cam with buffer size: {vipc_client_extra.buffer_len} ({vipc_client_extra.width} x {vipc_client_extra.height})") - - # messaging - pm = PubMaster(["modelV2", "drivingModelData", "cameraOdometry"]) - sm = SubMaster(["deviceState", "carState", "roadCameraState", "liveCalibration", "driverMonitoringState", "carControl"]) - - publish_state = PublishState() - params = Params() - - # setup filter to track dropped frames - frame_dropped_filter = FirstOrderFilter(0., 10., 1. / ModelConstants.MODEL_FREQ) - frame_id = 0 - last_vipc_frame_id = 0 - run_count = 0 - - model_transform_main = np.zeros((3, 3), dtype=np.float32) - model_transform_extra = np.zeros((3, 3), dtype=np.float32) - live_calib_seen = False - buf_main, buf_extra = None, None - meta_main = FrameMeta() - meta_extra = FrameMeta() - - - if demo: - CP = get_demo_car_params() - else: - CP = messaging.log_from_bytes(params.get("CarParams", block=True), car.CarParams) - cloudlog.info("modeld got CarParams: %s", CP.carName) - - # TODO this needs more thought, use .2s extra for now to estimate other delays - steer_delay = CP.steerActuatorDelay + .2 - - DH = DesireHelper() - - while True: - # Keep receiving frames until we are at least 1 frame ahead of previous extra frame - while meta_main.timestamp_sof < meta_extra.timestamp_sof + 25000000: - buf_main = vipc_client_main.recv() - meta_main = FrameMeta(vipc_client_main) - if buf_main is None: - break - - if buf_main is None: - cloudlog.debug("vipc_client_main no frame") - continue - - if use_extra_client: - # Keep receiving extra frames until frame id matches main camera - while True: - buf_extra = vipc_client_extra.recv() - meta_extra = FrameMeta(vipc_client_extra) - if buf_extra is None or meta_main.timestamp_sof < meta_extra.timestamp_sof + 25000000: - break - - if buf_extra is None: - cloudlog.debug("vipc_client_extra no frame") - continue - - if abs(meta_main.timestamp_sof - meta_extra.timestamp_sof) > 10000000: - cloudlog.error(f"frames out of sync! main: {meta_main.frame_id} ({meta_main.timestamp_sof / 1e9:.5f}),\ - extra: {meta_extra.frame_id} ({meta_extra.timestamp_sof / 1e9:.5f})") - - else: - # Use single camera - buf_extra = buf_main - meta_extra = meta_main - - sm.update(0) - desire = DH.desire - is_rhd = sm["driverMonitoringState"].isRHD - frame_id = sm["roadCameraState"].frameId - v_ego = max(sm["carState"].vEgo, 0.) - 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))] - model_transform_main = get_warp_matrix(device_from_calib_euler, dc.ecam.intrinsics if main_wide_camera else dc.fcam.intrinsics, False).astype(np.float32) - model_transform_extra = get_warp_matrix(device_from_calib_euler, dc.ecam.intrinsics, True).astype(np.float32) - live_calib_seen = True - - traffic_convention = np.zeros(2) - traffic_convention[int(is_rhd)] = 1 - - vec_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32) - if desire >= 0 and desire < ModelConstants.DESIRE_LEN: - vec_desire[desire] = 1 - - # tracked dropped frames - vipc_dropped_frames = max(0, meta_main.frame_id - last_vipc_frame_id - 1) - frames_dropped = frame_dropped_filter.update(min(vipc_dropped_frames, 10)) - if run_count < 10: # let frame drops warm up - frame_dropped_filter.x = 0. - frames_dropped = 0. - run_count = run_count + 1 - - frame_drop_ratio = frames_dropped / (1 + frames_dropped) - prepare_only = vipc_dropped_frames > 0 - if prepare_only: - cloudlog.error(f"skipping model eval. Dropped {vipc_dropped_frames} frames") - - inputs:dict[str, np.ndarray] = { - 'desire': vec_desire, - 'traffic_convention': traffic_convention, - } - - mt1 = time.perf_counter() - model_output = model.run(buf_main, buf_extra, model_transform_main, model_transform_extra, inputs, prepare_only) - mt2 = time.perf_counter() - model_execution_time = mt2 - mt1 - - if model_output is not None: - modelv2_send = messaging.new_message('modelV2') - drivingdata_send = messaging.new_message('drivingModelData') - posenet_send = messaging.new_message('cameraOdometry') - fill_model_msg(drivingdata_send, modelv2_send, model_output, v_ego, steer_delay, - publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id, - frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, live_calib_seen) - - desire_state = modelv2_send.modelV2.meta.desireState - l_lane_change_prob = desire_state[log.Desire.laneChangeLeft] - r_lane_change_prob = desire_state[log.Desire.laneChangeRight] - lane_change_prob = l_lane_change_prob + r_lane_change_prob - DH.update(sm['carState'], sm['carControl'].latActive, lane_change_prob) - modelv2_send.modelV2.meta.laneChangeState = DH.lane_change_state - modelv2_send.modelV2.meta.laneChangeDirection = DH.lane_change_direction - drivingdata_send.drivingModelData.meta.laneChangeState = DH.lane_change_state - drivingdata_send.drivingModelData.meta.laneChangeDirection = DH.lane_change_direction - - fill_pose_msg(posenet_send, model_output, meta_main.frame_id, vipc_dropped_frames, meta_main.timestamp_eof, live_calib_seen) - pm.send('modelV2', modelv2_send) - pm.send('drivingModelData', drivingdata_send) - pm.send('cameraOdometry', posenet_send) - - last_vipc_frame_id = meta_main.frame_id - - -if __name__ == "__main__": - try: - import argparse - parser = argparse.ArgumentParser() - parser.add_argument('--demo', action='store_true', help='A boolean for demo mode.') - args = parser.parse_args() - main(demo=args.demo) - except KeyboardInterrupt: - cloudlog.warning(f"child {PROCESS_NAME} got SIGINT") - except Exception: - sentry.capture_exception() - raise diff --git a/sunnypilot/modeld/models/README.md b/sunnypilot/modeld/models/README.md deleted file mode 100644 index 9e11ca825..000000000 --- a/sunnypilot/modeld/models/README.md +++ /dev/null @@ -1,62 +0,0 @@ -## Neural networks in openpilot -To view the architecture of the ONNX networks, you can use [netron](https://netron.app/) - -## Supercombo -### Supercombo input format (Full size: 799906 x float32) -* **image stream** - * Two consecutive images (256 * 512 * 3 in RGB) recorded at 20 Hz : 393216 = 2 * 6 * 128 * 256 - * Each 256 * 512 image is represented in YUV420 with 6 channels : 6 * 128 * 256 - * Channels 0,1,2,3 represent the full-res Y channel and are represented in numpy as Y[::2, ::2], Y[::2, 1::2], Y[1::2, ::2], and Y[1::2, 1::2] - * Channel 4 represents the half-res U channel - * Channel 5 represents the half-res V channel -* **wide image stream** - * Two consecutive images (256 * 512 * 3 in RGB) recorded at 20 Hz : 393216 = 2 * 6 * 128 * 256 - * Each 256 * 512 image is represented in YUV420 with 6 channels : 6 * 128 * 256 - * Channels 0,1,2,3 represent the full-res Y channel and are represented in numpy as Y[::2, ::2], Y[::2, 1::2], Y[1::2, ::2], and Y[1::2, 1::2] - * Channel 4 represents the half-res U channel - * Channel 5 represents the half-res V channel -* **desire** - * one-hot encoded buffer to command model to execute certain actions, bit needs to be sent for the past 5 seconds (at 20FPS) : 100 * 8 -* **traffic convention** - * one-hot encoded vector to tell model whether traffic is right-hand or left-hand traffic : 2 -* **feature buffer** - * A buffer of intermediate features that gets appended to the current feature to form a 5 seconds temporal context (at 20FPS) : 99 * 512 - - -### Supercombo output format (Full size: XXX x float32) -Read [here](https://github.com/commaai/openpilot/blob/90af436a121164a51da9fa48d093c29f738adf6a/selfdrive/modeld/models/driving.h#L236) for more. - - -## Driver Monitoring Model -* .onnx model can be run with onnx runtimes -* .dlc file is a pre-quantized model and only runs on qualcomm DSPs - -### input format -* single image W = 1440 H = 960 luminance channel (Y) from the planar YUV420 format: - * full input size is 1440 * 960 = 1382400 - * normalized ranging from 0.0 to 1.0 in float32 (onnx runner) or ranging from 0 to 255 in uint8 (snpe runner) -* camera calibration angles (roll, pitch, yaw) from liveCalibration: 3 x float32 inputs - -### output format -* 84 x float32 outputs = 2 + 41 * 2 ([parsing example](https://github.com/commaai/openpilot/blob/22ce4e17ba0d3bfcf37f8255a4dd1dc683fe0c38/selfdrive/modeld/models/dmonitoring.cc#L33)) - * for each person in the front seats (2 * 41) - * face pose: 12 = 6 + 6 - * face orientation [pitch, yaw, roll] in camera frame: 3 - * face position [dx, dy] relative to image center: 2 - * normalized face size: 1 - * standard deviations for above outputs: 6 - * face visible probability: 1 - * eyes: 20 = (8 + 1) + (8 + 1) + 1 + 1 - * eye position and size, and their standard deviations: 8 - * eye visible probability: 1 - * eye closed probability: 1 - * wearing sunglasses probability: 1 - * face occluded probability: 1 - * touching wheel probability: 1 - * paying attention probability: 1 - * (deprecated) distracted probabilities: 2 - * using phone probability: 1 - * distracted probability: 1 - * common outputs 2 - * poor camera vision probability: 1 - * left hand drive probability: 1 diff --git a/sunnypilot/modeld/models/commonmodel.cc b/sunnypilot/modeld/models/commonmodel.cc deleted file mode 100644 index 8df11fdf1..000000000 --- a/sunnypilot/modeld/models/commonmodel.cc +++ /dev/null @@ -1,69 +0,0 @@ -#include "sunnypilot/modeld/models/commonmodel.h" - -#include -#include - -#include "common/clutil.h" - -DrivingModelFrame::DrivingModelFrame(cl_device_id device_id, cl_context context) : ModelFrame(device_id, context) { - input_frames = std::make_unique(buf_size); - //input_frames_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, buf_size, NULL, &err)); - img_buffer_20hz_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, 5*frame_size_bytes, NULL, &err)); - region.origin = 4 * frame_size_bytes; - region.size = frame_size_bytes; - last_img_cl = CL_CHECK_ERR(clCreateSubBuffer(img_buffer_20hz_cl, CL_MEM_READ_WRITE, CL_BUFFER_CREATE_TYPE_REGION, ®ion, &err)); - - loadyuv_init(&loadyuv, context, device_id, MODEL_WIDTH, MODEL_HEIGHT); - init_transform(device_id, context, MODEL_WIDTH, MODEL_HEIGHT); -} - -uint8_t* DrivingModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection, cl_mem* output) { - run_transform(yuv_cl, MODEL_WIDTH, MODEL_HEIGHT, frame_width, frame_height, frame_stride, frame_uv_offset, projection); - - for (int i = 0; i < 4; i++) { - CL_CHECK(clEnqueueCopyBuffer(q, img_buffer_20hz_cl, img_buffer_20hz_cl, (i+1)*frame_size_bytes, i*frame_size_bytes, frame_size_bytes, 0, nullptr, nullptr)); - } - loadyuv_queue(&loadyuv, q, y_cl, u_cl, v_cl, last_img_cl); - - if (output == NULL) { - CL_CHECK(clEnqueueReadBuffer(q, img_buffer_20hz_cl, CL_TRUE, 0, frame_size_bytes, &input_frames[0], 0, nullptr, nullptr)); - CL_CHECK(clEnqueueReadBuffer(q, last_img_cl, CL_TRUE, 0, frame_size_bytes, &input_frames[MODEL_FRAME_SIZE], 0, nullptr, nullptr)); - clFinish(q); - return &input_frames[0]; - } else { - copy_queue(&loadyuv, q, img_buffer_20hz_cl, *output, 0, 0, frame_size_bytes); - copy_queue(&loadyuv, q, last_img_cl, *output, 0, frame_size_bytes, frame_size_bytes); - - // NOTE: Since thneed is using a different command queue, this clFinish is needed to ensure the image is ready. - clFinish(q); - return NULL; - } -} - -DrivingModelFrame::~DrivingModelFrame() { - deinit_transform(); - loadyuv_destroy(&loadyuv); - CL_CHECK(clReleaseMemObject(img_buffer_20hz_cl)); - CL_CHECK(clReleaseMemObject(last_img_cl)); - CL_CHECK(clReleaseCommandQueue(q)); -} - - -MonitoringModelFrame::MonitoringModelFrame(cl_device_id device_id, cl_context context) : ModelFrame(device_id, context) { - input_frames = std::make_unique(buf_size); - //input_frame_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, buf_size, NULL, &err)); - - init_transform(device_id, context, MODEL_WIDTH, MODEL_HEIGHT); -} -uint8_t* MonitoringModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection, cl_mem* output) { - run_transform(yuv_cl, MODEL_WIDTH, MODEL_HEIGHT, frame_width, frame_height, frame_stride, frame_uv_offset, projection); - CL_CHECK(clEnqueueReadBuffer(q, y_cl, CL_TRUE, 0, MODEL_FRAME_SIZE * sizeof(uint8_t), input_frames.get(), 0, nullptr, nullptr)); - clFinish(q); - //return &y_cl; - return input_frames.get(); -} - -MonitoringModelFrame::~MonitoringModelFrame() { - deinit_transform(); - CL_CHECK(clReleaseCommandQueue(q)); -} diff --git a/sunnypilot/modeld/models/commonmodel.h b/sunnypilot/modeld/models/commonmodel.h deleted file mode 100644 index e55f78e24..000000000 --- a/sunnypilot/modeld/models/commonmodel.h +++ /dev/null @@ -1,98 +0,0 @@ -#pragma once - -#include -#include -#include - -#include - -#define CL_USE_DEPRECATED_OPENCL_1_2_APIS -#ifdef __APPLE__ -#include -#else -#include -#endif - -#include "common/mat.h" -#include "selfdrive/modeld/transforms/loadyuv.h" -#include "selfdrive/modeld/transforms/transform.h" - -class ModelFrame { -public: - ModelFrame(cl_device_id device_id, cl_context context) { - q = CL_CHECK_ERR(clCreateCommandQueue(context, device_id, 0, &err)); - } - virtual ~ModelFrame() {} - virtual uint8_t* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection, cl_mem* output) { return NULL; } - /* - uint8_t* buffer_from_cl(cl_mem *in_frames, int buffer_size) { - CL_CHECK(clEnqueueReadBuffer(q, *in_frames, CL_TRUE, 0, buffer_size, input_frames.get(), 0, nullptr, nullptr)); - clFinish(q); - return &input_frames[0]; - } - */ - - int MODEL_WIDTH; - int MODEL_HEIGHT; - int MODEL_FRAME_SIZE; - int buf_size; - -protected: - cl_mem y_cl, u_cl, v_cl; - Transform transform; - cl_command_queue q; - std::unique_ptr input_frames; - - void init_transform(cl_device_id device_id, cl_context context, int model_width, int model_height) { - y_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, model_width * model_height, NULL, &err)); - u_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, (model_width / 2) * (model_height / 2), NULL, &err)); - v_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, (model_width / 2) * (model_height / 2), NULL, &err)); - transform_init(&transform, context, device_id); - } - - void deinit_transform() { - transform_destroy(&transform); - CL_CHECK(clReleaseMemObject(v_cl)); - CL_CHECK(clReleaseMemObject(u_cl)); - CL_CHECK(clReleaseMemObject(y_cl)); - } - - void run_transform(cl_mem yuv_cl, int model_width, int model_height, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) { - transform_queue(&transform, q, - yuv_cl, frame_width, frame_height, frame_stride, frame_uv_offset, - y_cl, u_cl, v_cl, model_width, model_height, projection); - } -}; - -class DrivingModelFrame : public ModelFrame { -public: - DrivingModelFrame(cl_device_id device_id, cl_context context); - ~DrivingModelFrame(); - uint8_t* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection, cl_mem* output); - - const int MODEL_WIDTH = 512; - const int MODEL_HEIGHT = 256; - const int MODEL_FRAME_SIZE = MODEL_WIDTH * MODEL_HEIGHT * 3 / 2; - const int buf_size = MODEL_FRAME_SIZE * 2; - const size_t frame_size_bytes = MODEL_FRAME_SIZE * sizeof(uint8_t); - -private: - LoadYUVState loadyuv; - cl_mem img_buffer_20hz_cl, last_img_cl;//, input_frames_cl; - cl_buffer_region region; -}; - -class MonitoringModelFrame : public ModelFrame { -public: - MonitoringModelFrame(cl_device_id device_id, cl_context context); - ~MonitoringModelFrame(); - uint8_t* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection, cl_mem* output); - - const int MODEL_WIDTH = 1440; - const int MODEL_HEIGHT = 960; - const int MODEL_FRAME_SIZE = MODEL_WIDTH * MODEL_HEIGHT; - const int buf_size = MODEL_FRAME_SIZE; - -private: - // cl_mem input_frame_cl; -}; diff --git a/sunnypilot/modeld/models/commonmodel.pxd b/sunnypilot/modeld/models/commonmodel.pxd deleted file mode 100644 index abcf10cec..000000000 --- a/sunnypilot/modeld/models/commonmodel.pxd +++ /dev/null @@ -1,26 +0,0 @@ -# distutils: language = c++ - -from msgq.visionipc.visionipc cimport cl_device_id, cl_context, cl_mem - -cdef extern from "common/mat.h": - cdef struct mat3: - float v[9] - -cdef extern from "common/clutil.h": - cdef unsigned long CL_DEVICE_TYPE_DEFAULT - cl_device_id cl_get_device_id(unsigned long) - cl_context cl_create_context(cl_device_id) - -cdef extern from "sunnypilot/modeld/models/commonmodel.h": - cppclass ModelFrame: - int buf_size - # unsigned char * buffer_from_cl(cl_mem*, int); - unsigned char * prepare(cl_mem, int, int, int, int, mat3, cl_mem*) - - cppclass DrivingModelFrame: - int buf_size - DrivingModelFrame(cl_device_id, cl_context) - - cppclass MonitoringModelFrame: - int buf_size - MonitoringModelFrame(cl_device_id, cl_context) diff --git a/sunnypilot/modeld/models/commonmodel_pyx.pxd b/sunnypilot/modeld/models/commonmodel_pyx.pxd deleted file mode 100644 index 0bb798625..000000000 --- a/sunnypilot/modeld/models/commonmodel_pyx.pxd +++ /dev/null @@ -1,13 +0,0 @@ -# distutils: language = c++ - -from msgq.visionipc.visionipc cimport cl_mem -from msgq.visionipc.visionipc_pyx cimport CLContext as BaseCLContext - -cdef class CLContext(BaseCLContext): - pass - -cdef class CLMem: - cdef cl_mem * mem - - @staticmethod - cdef create(void*) diff --git a/sunnypilot/modeld/models/commonmodel_pyx.pyx b/sunnypilot/modeld/models/commonmodel_pyx.pyx deleted file mode 100644 index 771555420..000000000 --- a/sunnypilot/modeld/models/commonmodel_pyx.pyx +++ /dev/null @@ -1,76 +0,0 @@ -# distutils: language = c++ -# cython: c_string_encoding=ascii, language_level=3 - -import numpy as np -cimport numpy as cnp -from libc.string cimport memcpy -from libc.stdint cimport uintptr_t - -from msgq.visionipc.visionipc cimport cl_mem -from msgq.visionipc.visionipc_pyx cimport VisionBuf, CLContext as BaseCLContext -from sunnypilot.modeld.models.commonmodel cimport CL_DEVICE_TYPE_DEFAULT, cl_get_device_id, cl_create_context -from sunnypilot.modeld.models.commonmodel cimport mat3, ModelFrame as cppModelFrame, DrivingModelFrame as cppDrivingModelFrame, MonitoringModelFrame as cppMonitoringModelFrame - - -cdef class CLContext(BaseCLContext): - def __cinit__(self): - self.device_id = cl_get_device_id(CL_DEVICE_TYPE_DEFAULT) - self.context = cl_create_context(self.device_id) - -cdef class CLMem: - @staticmethod - cdef create(void * cmem): - mem = CLMem() - mem.mem = cmem - return mem - - @property - def mem_address(self): - return (self.mem) - -def cl_from_visionbuf(VisionBuf buf): - return CLMem.create(&buf.buf.buf_cl) - - -cdef class ModelFrame: - cdef cppModelFrame * frame - cdef int buf_size - - def __dealloc__(self): - del self.frame - - def prepare(self, VisionBuf buf, float[:] projection, CLMem output): - cdef mat3 cprojection - memcpy(cprojection.v, &projection[0], 9*sizeof(float)) - cdef unsigned char * data - if output is None: - data = self.frame.prepare(buf.buf.buf_cl, buf.width, buf.height, buf.stride, buf.uv_offset, cprojection, NULL) - else: - data = self.frame.prepare(buf.buf.buf_cl, buf.width, buf.height, buf.stride, buf.uv_offset, cprojection, output.mem) - if not data: - return None - - return np.asarray( data) - # return CLMem.create(data) - - # def buffer_from_cl(self, CLMem in_frames): - # cdef unsigned char * data2 - # data2 = self.frame.buffer_from_cl(in_frames.mem, self.buf_size) - # return np.asarray( data2) - - -cdef class DrivingModelFrame(ModelFrame): - cdef cppDrivingModelFrame * _frame - - def __cinit__(self, CLContext context): - self._frame = new cppDrivingModelFrame(context.device_id, context.context) - self.frame = (self._frame) - self.buf_size = self._frame.buf_size - -cdef class MonitoringModelFrame(ModelFrame): - cdef cppMonitoringModelFrame * _frame - - def __cinit__(self, CLContext context): - self._frame = new cppMonitoringModelFrame(context.device_id, context.context) - self.frame = (self._frame) - self.buf_size = self._frame.buf_size diff --git a/sunnypilot/modeld/models/supercombo.onnx b/sunnypilot/modeld/models/supercombo.onnx deleted file mode 100644 index 384072f42..000000000 --- a/sunnypilot/modeld/models/supercombo.onnx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:0c896681fd6851de3968433e12f37834429eba265e938cf383200be3e5835cec -size 49096168 diff --git a/sunnypilot/modeld/models/supercombo.thneed b/sunnypilot/modeld/models/supercombo.thneed deleted file mode 100644 index 4f48547c7..000000000 --- a/sunnypilot/modeld/models/supercombo.thneed +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:af2cb689ec9e31292f759b561e70e4558a38f778558dff39ccff460ccafc0d52 -size 49849624 diff --git a/sunnypilot/modeld/models/supercombo_metadata.pkl b/sunnypilot/modeld/models/supercombo_metadata.pkl deleted file mode 100644 index d4783c250..000000000 --- a/sunnypilot/modeld/models/supercombo_metadata.pkl +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:441f2865017c07ee0dfb2488c5d86aab00df7ff5c5ec163959f35c33d74b65e6 -size 594 diff --git a/sunnypilot/modeld/parse_model_outputs.py b/sunnypilot/modeld/parse_model_outputs.py deleted file mode 100644 index ad664efc5..000000000 --- a/sunnypilot/modeld/parse_model_outputs.py +++ /dev/null @@ -1,103 +0,0 @@ -import numpy as np -from openpilot.sunnypilot.modeld.constants import ModelConstants - -def safe_exp(x, out=None): - # -11 is around 10**14, more causes float16 overflow - return np.exp(np.clip(x, -np.inf, 11), out=out) - -def sigmoid(x): - return 1. / (1. + safe_exp(-x)) - -def softmax(x, axis=-1): - x -= np.max(x, axis=axis, keepdims=True) - if x.dtype == np.float32 or x.dtype == np.float64: - safe_exp(x, out=x) - else: - x = safe_exp(x) - x /= np.sum(x, axis=axis, keepdims=True) - return x - -class Parser: - def __init__(self, ignore_missing=False): - self.ignore_missing = ignore_missing - - def check_missing(self, outs, name): - if name not in outs and not self.ignore_missing: - raise ValueError(f"Missing output {name}") - return name not in outs - - def parse_categorical_crossentropy(self, name, outs, out_shape=None): - if self.check_missing(outs, name): - return - raw = outs[name] - if out_shape is not None: - raw = raw.reshape((raw.shape[0],) + out_shape) - outs[name] = softmax(raw, axis=-1) - - def parse_binary_crossentropy(self, name, outs): - if self.check_missing(outs, name): - return - raw = outs[name] - outs[name] = sigmoid(raw) - - def parse_mdn(self, name, outs, in_N=0, out_N=1, out_shape=None): - if self.check_missing(outs, name): - return - raw = outs[name] - raw = raw.reshape((raw.shape[0], max(in_N, 1), -1)) - - n_values = (raw.shape[2] - out_N)//2 - pred_mu = raw[:,:,:n_values] - pred_std = safe_exp(raw[:,:,n_values: 2*n_values]) - - if in_N > 1: - weights = np.zeros((raw.shape[0], in_N, out_N), dtype=raw.dtype) - for i in range(out_N): - weights[:,:,i - out_N] = softmax(raw[:,:,i - out_N], axis=-1) - - if out_N == 1: - for fidx in range(weights.shape[0]): - idxs = np.argsort(weights[fidx][:,0])[::-1] - weights[fidx] = weights[fidx][idxs] - pred_mu[fidx] = pred_mu[fidx][idxs] - pred_std[fidx] = pred_std[fidx][idxs] - full_shape = tuple([raw.shape[0], in_N] + list(out_shape)) - outs[name + '_weights'] = weights - outs[name + '_hypotheses'] = pred_mu.reshape(full_shape) - outs[name + '_stds_hypotheses'] = pred_std.reshape(full_shape) - - pred_mu_final = np.zeros((raw.shape[0], out_N, n_values), dtype=raw.dtype) - pred_std_final = np.zeros((raw.shape[0], out_N, n_values), dtype=raw.dtype) - for fidx in range(weights.shape[0]): - for hidx in range(out_N): - idxs = np.argsort(weights[fidx,:,hidx])[::-1] - pred_mu_final[fidx, hidx] = pred_mu[fidx, idxs[0]] - pred_std_final[fidx, hidx] = pred_std[fidx, idxs[0]] - else: - pred_mu_final = pred_mu - pred_std_final = pred_std - - if out_N > 1: - final_shape = tuple([raw.shape[0], out_N] + list(out_shape)) - else: - final_shape = tuple([raw.shape[0],] + list(out_shape)) - outs[name] = pred_mu_final.reshape(final_shape) - outs[name + '_stds'] = pred_std_final.reshape(final_shape) - - def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]: - self.parse_mdn('plan', outs, in_N=ModelConstants.PLAN_MHP_N, out_N=ModelConstants.PLAN_MHP_SELECTION, - out_shape=(ModelConstants.IDX_N,ModelConstants.PLAN_WIDTH)) - self.parse_mdn('lane_lines', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_LANE_LINES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH)) - self.parse_mdn('road_edges', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_ROAD_EDGES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH)) - self.parse_mdn('pose', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,)) - self.parse_mdn('road_transform', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,)) - self.parse_mdn('wide_from_device_euler', outs, in_N=0, out_N=0, out_shape=(ModelConstants.WIDE_FROM_DEVICE_WIDTH,)) - self.parse_mdn('lead', outs, in_N=ModelConstants.LEAD_MHP_N, out_N=ModelConstants.LEAD_MHP_SELECTION, - out_shape=(ModelConstants.LEAD_TRAJ_LEN,ModelConstants.LEAD_WIDTH)) - if 'lat_planner_solution' in outs: - self.parse_mdn('lat_planner_solution', outs, in_N=0, out_N=0, out_shape=(ModelConstants.IDX_N,ModelConstants.LAT_PLANNER_SOLUTION_WIDTH)) - for k in ['lead_prob', 'lane_lines_prob', 'meta']: - self.parse_binary_crossentropy(k, outs) - self.parse_categorical_crossentropy('desire_state', outs, out_shape=(ModelConstants.DESIRE_PRED_WIDTH,)) - self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(ModelConstants.DESIRE_PRED_LEN,ModelConstants.DESIRE_PRED_WIDTH)) - return outs diff --git a/sunnypilot/modeld/runners/__init__.py b/sunnypilot/modeld/runners/__init__.py deleted file mode 100644 index 3f4507e4e..000000000 --- a/sunnypilot/modeld/runners/__init__.py +++ /dev/null @@ -1,27 +0,0 @@ -import os -from openpilot.system.hardware import TICI -from openpilot.sunnypilot.modeld.runners.runmodel_pyx import RunModel, Runtime -assert Runtime - -USE_THNEED = int(os.getenv('USE_THNEED', str(int(TICI)))) -USE_SNPE = int(os.getenv('USE_SNPE', str(int(TICI)))) - -class ModelRunner(RunModel): - THNEED = 'THNEED' - SNPE = 'SNPE' - ONNX = 'ONNX' - - def __new__(cls, paths, *args, **kwargs): - if ModelRunner.THNEED in paths and USE_THNEED: - from openpilot.sunnypilot.modeld.runners.thneedmodel_pyx import ThneedModel as Runner - runner_type = ModelRunner.THNEED - elif ModelRunner.SNPE in paths and USE_SNPE: - from openpilot.sunnypilot.modeld.runners.snpemodel_pyx import SNPEModel as Runner - runner_type = ModelRunner.SNPE - elif ModelRunner.ONNX in paths: - from openpilot.sunnypilot.modeld.runners.onnxmodel import ONNXModel as Runner - runner_type = ModelRunner.ONNX - else: - raise Exception("Couldn't select a model runner, make sure to pass at least one valid model path") - - return Runner(str(paths[runner_type]), *args, **kwargs) diff --git a/sunnypilot/modeld/runners/onnxmodel.py b/sunnypilot/modeld/runners/onnxmodel.py deleted file mode 100644 index 7637e4192..000000000 --- a/sunnypilot/modeld/runners/onnxmodel.py +++ /dev/null @@ -1,71 +0,0 @@ -import os -import onnx -import sys -import numpy as np -from typing import Any - -from openpilot.sunnypilot.modeld.runners.runmodel_pyx import RunModel -from openpilot.sunnypilot.modeld.runners.ort_helpers import convert_fp16_to_fp32, ORT_TYPES_TO_NP_TYPES - - -def create_ort_session(path, fp16_to_fp32): - os.environ["OMP_NUM_THREADS"] = "4" - os.environ["OMP_WAIT_POLICY"] = "PASSIVE" - - import onnxruntime as ort - print("Onnx available providers: ", ort.get_available_providers(), file=sys.stderr) - options = ort.SessionOptions() - options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_DISABLE_ALL - - provider: str | tuple[str, dict[Any, Any]] - if 'OpenVINOExecutionProvider' in ort.get_available_providers() and 'ONNXCPU' not in os.environ: - provider = 'OpenVINOExecutionProvider' - elif 'CUDAExecutionProvider' in ort.get_available_providers() and 'ONNXCPU' not in os.environ: - options.intra_op_num_threads = 2 - provider = ('CUDAExecutionProvider', {'cudnn_conv_algo_search': 'EXHAUSTIVE'}) - else: - options.intra_op_num_threads = 2 - options.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL - options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL - provider = 'CPUExecutionProvider' - - model_data = convert_fp16_to_fp32(onnx.load(path)) if fp16_to_fp32 else path - print("Onnx selected provider: ", [provider], file=sys.stderr) - ort_session = ort.InferenceSession(model_data, options, providers=[provider]) - print("Onnx using ", ort_session.get_providers(), file=sys.stderr) - return ort_session - - -class ONNXModel(RunModel): - def __init__(self, path, output, runtime, use_tf8, cl_context): - self.inputs = {} - self.output = output - - self.session = create_ort_session(path, fp16_to_fp32=True) - self.input_names = [x.name for x in self.session.get_inputs()] - self.input_shapes = {x.name: [1, *x.shape[1:]] for x in self.session.get_inputs()} - self.input_dtypes = {x.name: ORT_TYPES_TO_NP_TYPES[x.type] for x in self.session.get_inputs()} - - # run once to initialize CUDA provider - if "CUDAExecutionProvider" in self.session.get_providers(): - self.session.run(None, {k: np.zeros(self.input_shapes[k], dtype=self.input_dtypes[k]) for k in self.input_names}) - print("ready to run onnx model", self.input_shapes, file=sys.stderr) - - def addInput(self, name, buffer): - assert name in self.input_names - self.inputs[name] = buffer - - def setInputBuffer(self, name, buffer): - assert name in self.inputs - self.inputs[name] = buffer - - def getCLBuffer(self, name): - return None - - def execute(self): - inputs = {k: v.view(self.input_dtypes[k]) for k,v in self.inputs.items()} - inputs = {k: v.reshape(self.input_shapes[k]).astype(self.input_dtypes[k]) for k,v in inputs.items()} - outputs = self.session.run(None, inputs) - assert len(outputs) == 1, "Only single model outputs are supported" - self.output[:] = outputs[0] - return self.output diff --git a/sunnypilot/modeld/runners/ort_helpers.py b/sunnypilot/modeld/runners/ort_helpers.py deleted file mode 100644 index 26afb0356..000000000 --- a/sunnypilot/modeld/runners/ort_helpers.py +++ /dev/null @@ -1,36 +0,0 @@ -import onnx -import onnxruntime as ort -import numpy as np -import itertools - -ORT_TYPES_TO_NP_TYPES = {'tensor(float16)': np.float16, 'tensor(float)': np.float32, 'tensor(uint8)': np.uint8} - -def attributeproto_fp16_to_fp32(attr): - float32_list = np.frombuffer(attr.raw_data, dtype=np.float16) - attr.data_type = 1 - attr.raw_data = float32_list.astype(np.float32).tobytes() - -def convert_fp16_to_fp32(model): - for i in model.graph.initializer: - if i.data_type == 10: - attributeproto_fp16_to_fp32(i) - for i in itertools.chain(model.graph.input, model.graph.output): - if i.type.tensor_type.elem_type == 10: - i.type.tensor_type.elem_type = 1 - for i in model.graph.node: - if i.op_type == 'Cast' and i.attribute[0].i == 10: - i.attribute[0].i = 1 - for a in i.attribute: - if hasattr(a, 't'): - if a.t.data_type == 10: - attributeproto_fp16_to_fp32(a.t) - return model.SerializeToString() - - -def make_onnx_cpu_runner(model_path): - options = ort.SessionOptions() - options.intra_op_num_threads = 4 - options.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL - options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL - model_data = convert_fp16_to_fp32(onnx.load(model_path)) - return ort.InferenceSession(model_data, options, providers=['CPUExecutionProvider']) diff --git a/sunnypilot/modeld/runners/run.h b/sunnypilot/modeld/runners/run.h deleted file mode 100644 index 84d99fd10..000000000 --- a/sunnypilot/modeld/runners/run.h +++ /dev/null @@ -1,4 +0,0 @@ -#pragma once - -#include "sunnypilot/modeld/runners/runmodel.h" -#include "sunnypilot/modeld/runners/snpemodel.h" diff --git a/sunnypilot/modeld/runners/runmodel.h b/sunnypilot/modeld/runners/runmodel.h deleted file mode 100644 index 18cc180cb..000000000 --- a/sunnypilot/modeld/runners/runmodel.h +++ /dev/null @@ -1,49 +0,0 @@ -#pragma once - -#include -#include -#include -#include - -#include "common/clutil.h" -#include "common/swaglog.h" - -#define USE_CPU_RUNTIME 0 -#define USE_GPU_RUNTIME 1 -#define USE_DSP_RUNTIME 2 - -struct ModelInput { - const std::string name; - float *buffer; - int size; - - ModelInput(const std::string _name, float *_buffer, int _size) : name(_name), buffer(_buffer), size(_size) {} - virtual void setBuffer(float *_buffer, int _size) { - assert(size == _size || size == 0); - buffer = _buffer; - size = _size; - } -}; - -class RunModel { -public: - std::vector> inputs; - - virtual ~RunModel() {} - virtual void execute() {} - virtual void* getCLBuffer(const std::string name) { return nullptr; } - - virtual void addInput(const std::string name, float *buffer, int size) { - inputs.push_back(std::unique_ptr(new ModelInput(name, buffer, size))); - } - virtual void setInputBuffer(const std::string name, float *buffer, int size) { - for (auto &input : inputs) { - if (name == input->name) { - input->setBuffer(buffer, size); - return; - } - } - LOGE("Tried to update input `%s` but no input with this name exists", name.c_str()); - assert(false); - } -}; diff --git a/sunnypilot/modeld/runners/runmodel.pxd b/sunnypilot/modeld/runners/runmodel.pxd deleted file mode 100644 index b83434473..000000000 --- a/sunnypilot/modeld/runners/runmodel.pxd +++ /dev/null @@ -1,14 +0,0 @@ -# distutils: language = c++ - -from libcpp.string cimport string - -cdef extern from "sunnypilot/modeld/runners/runmodel.h": - cdef int USE_CPU_RUNTIME - cdef int USE_GPU_RUNTIME - cdef int USE_DSP_RUNTIME - - cdef cppclass RunModel: - void addInput(string, float*, int) - void setInputBuffer(string, float*, int) - void * getCLBuffer(string) - void execute() diff --git a/sunnypilot/modeld/runners/runmodel_pyx.pxd b/sunnypilot/modeld/runners/runmodel_pyx.pxd deleted file mode 100644 index b6ede7cf3..000000000 --- a/sunnypilot/modeld/runners/runmodel_pyx.pxd +++ /dev/null @@ -1,6 +0,0 @@ -# distutils: language = c++ - -from .runmodel cimport RunModel as cppRunModel - -cdef class RunModel: - cdef cppRunModel * model diff --git a/sunnypilot/modeld/runners/runmodel_pyx.pyx b/sunnypilot/modeld/runners/runmodel_pyx.pyx deleted file mode 100644 index e224b1e4f..000000000 --- a/sunnypilot/modeld/runners/runmodel_pyx.pyx +++ /dev/null @@ -1,37 +0,0 @@ -# distutils: language = c++ -# cython: c_string_encoding=ascii, language_level=3 - -from libcpp.string cimport string - -from .runmodel cimport USE_CPU_RUNTIME, USE_GPU_RUNTIME, USE_DSP_RUNTIME -from sunnypilot.modeld.models.commonmodel_pyx cimport CLMem - -class Runtime: - CPU = USE_CPU_RUNTIME - GPU = USE_GPU_RUNTIME - DSP = USE_DSP_RUNTIME - -cdef class RunModel: - def __dealloc__(self): - del self.model - - def addInput(self, string name, float[:] buffer): - if buffer is not None: - self.model.addInput(name, &buffer[0], len(buffer)) - else: - self.model.addInput(name, NULL, 0) - - def setInputBuffer(self, string name, float[:] buffer): - if buffer is not None: - self.model.setInputBuffer(name, &buffer[0], len(buffer)) - else: - self.model.setInputBuffer(name, NULL, 0) - - def getCLBuffer(self, string name): - cdef void * cl_buf = self.model.getCLBuffer(name) - if not cl_buf: - return None - return CLMem.create(cl_buf) - - def execute(self): - self.model.execute() diff --git a/sunnypilot/modeld/runners/snpemodel.cc b/sunnypilot/modeld/runners/snpemodel.cc deleted file mode 100644 index ce06ba39f..000000000 --- a/sunnypilot/modeld/runners/snpemodel.cc +++ /dev/null @@ -1,116 +0,0 @@ -#pragma clang diagnostic ignored "-Wexceptions" - -#include "sunnypilot/modeld/runners/snpemodel.h" - -#include -#include -#include -#include -#include - -#include "common/util.h" -#include "common/timing.h" - -void PrintErrorStringAndExit() { - std::cerr << zdl::DlSystem::getLastErrorString() << std::endl; - std::exit(EXIT_FAILURE); -} - -SNPEModel::SNPEModel(const std::string path, float *_output, size_t _output_size, int runtime, bool _use_tf8, cl_context context) { - output = _output; - output_size = _output_size; - use_tf8 = _use_tf8; - -#ifdef QCOM2 - if (runtime == USE_GPU_RUNTIME) { - snpe_runtime = zdl::DlSystem::Runtime_t::GPU; - } else if (runtime == USE_DSP_RUNTIME) { - snpe_runtime = zdl::DlSystem::Runtime_t::DSP; - } else { - snpe_runtime = zdl::DlSystem::Runtime_t::CPU; - } - assert(zdl::SNPE::SNPEFactory::isRuntimeAvailable(snpe_runtime)); -#endif - model_data = util::read_file(path); - assert(model_data.size() > 0); - - // load model - std::unique_ptr container = zdl::DlContainer::IDlContainer::open((uint8_t*)model_data.data(), model_data.size()); - if (!container) { PrintErrorStringAndExit(); } - LOGW("loaded model with size: %lu", model_data.size()); - - // create model runner - zdl::SNPE::SNPEBuilder snpe_builder(container.get()); - while (!snpe) { -#ifdef QCOM2 - snpe = snpe_builder.setOutputLayers({}) - .setRuntimeProcessor(snpe_runtime) - .setUseUserSuppliedBuffers(true) - .setPerformanceProfile(zdl::DlSystem::PerformanceProfile_t::HIGH_PERFORMANCE) - .build(); -#else - snpe = snpe_builder.setOutputLayers({}) - .setUseUserSuppliedBuffers(true) - .setPerformanceProfile(zdl::DlSystem::PerformanceProfile_t::HIGH_PERFORMANCE) - .build(); -#endif - if (!snpe) std::cerr << zdl::DlSystem::getLastErrorString() << std::endl; - } - - // create output buffer - zdl::DlSystem::UserBufferEncodingFloat ub_encoding_float; - zdl::DlSystem::IUserBufferFactory &ub_factory = zdl::SNPE::SNPEFactory::getUserBufferFactory(); - - const auto &output_tensor_names_opt = snpe->getOutputTensorNames(); - if (!output_tensor_names_opt) throw std::runtime_error("Error obtaining output tensor names"); - const auto &output_tensor_names = *output_tensor_names_opt; - assert(output_tensor_names.size() == 1); - const char *output_tensor_name = output_tensor_names.at(0); - const zdl::DlSystem::TensorShape &buffer_shape = snpe->getInputOutputBufferAttributes(output_tensor_name)->getDims(); - if (output_size != 0) { - assert(output_size == buffer_shape[1]); - } else { - output_size = buffer_shape[1]; - } - std::vector output_strides = {output_size * sizeof(float), sizeof(float)}; - output_buffer = ub_factory.createUserBuffer(output, output_size * sizeof(float), output_strides, &ub_encoding_float); - output_map.add(output_tensor_name, output_buffer.get()); -} - -void SNPEModel::addInput(const std::string name, float *buffer, int size) { - const int idx = inputs.size(); - const auto &input_tensor_names_opt = snpe->getInputTensorNames(); - if (!input_tensor_names_opt) throw std::runtime_error("Error obtaining input tensor names"); - const auto &input_tensor_names = *input_tensor_names_opt; - const char *input_tensor_name = input_tensor_names.at(idx); - const bool input_tf8 = use_tf8 && strcmp(input_tensor_name, "input_img") == 0; // TODO: This is a terrible hack, get rid of this name check both here and in onnx_runner.py - LOGW("adding index %d: %s", idx, input_tensor_name); - - zdl::DlSystem::UserBufferEncodingFloat ub_encoding_float; - zdl::DlSystem::UserBufferEncodingTf8 ub_encoding_tf8(0, 1./255); // network takes 0-1 - zdl::DlSystem::IUserBufferFactory &ub_factory = zdl::SNPE::SNPEFactory::getUserBufferFactory(); - zdl::DlSystem::UserBufferEncoding *input_encoding = input_tf8 ? (zdl::DlSystem::UserBufferEncoding*)&ub_encoding_tf8 : (zdl::DlSystem::UserBufferEncoding*)&ub_encoding_float; - - const auto &buffer_shape_opt = snpe->getInputDimensions(input_tensor_name); - const zdl::DlSystem::TensorShape &buffer_shape = *buffer_shape_opt; - size_t size_of_input = input_tf8 ? sizeof(uint8_t) : sizeof(float); - std::vector strides(buffer_shape.rank()); - strides[strides.size() - 1] = size_of_input; - size_t product = 1; - for (size_t i = 0; i < buffer_shape.rank(); i++) product *= buffer_shape[i]; - size_t stride = strides[strides.size() - 1]; - for (size_t i = buffer_shape.rank() - 1; i > 0; i--) { - stride *= buffer_shape[i]; - strides[i-1] = stride; - } - - auto input_buffer = ub_factory.createUserBuffer(buffer, product*size_of_input, strides, input_encoding); - input_map.add(input_tensor_name, input_buffer.get()); - inputs.push_back(std::unique_ptr(new SNPEModelInput(name, buffer, size, std::move(input_buffer)))); -} - -void SNPEModel::execute() { - if (!snpe->execute(input_map, output_map)) { - PrintErrorStringAndExit(); - } -} diff --git a/sunnypilot/modeld/runners/snpemodel.h b/sunnypilot/modeld/runners/snpemodel.h deleted file mode 100644 index bd7662421..000000000 --- a/sunnypilot/modeld/runners/snpemodel.h +++ /dev/null @@ -1,52 +0,0 @@ -#pragma once -#pragma clang diagnostic ignored "-Wdeprecated-declarations" - -#include -#include -#include - -#include -#include -#include -#include -#include -#include -#include -#include -#include - -#include "sunnypilot/modeld/runners/runmodel.h" - -struct SNPEModelInput : public ModelInput { - std::unique_ptr snpe_buffer; - - SNPEModelInput(const std::string _name, float *_buffer, int _size, std::unique_ptr _snpe_buffer) : ModelInput(_name, _buffer, _size), snpe_buffer(std::move(_snpe_buffer)) {} - void setBuffer(float *_buffer, int _size) { - ModelInput::setBuffer(_buffer, _size); - assert(snpe_buffer->setBufferAddress(_buffer) == true); - } -}; - -class SNPEModel : public RunModel { -public: - SNPEModel(const std::string path, float *_output, size_t _output_size, int runtime, bool use_tf8 = false, cl_context context = NULL); - void addInput(const std::string name, float *buffer, int size); - void execute(); - -private: - std::string model_data; - -#ifdef QCOM2 - zdl::DlSystem::Runtime_t snpe_runtime; -#endif - - // snpe model stuff - std::unique_ptr snpe; - zdl::DlSystem::UserBufferMap input_map; - zdl::DlSystem::UserBufferMap output_map; - std::unique_ptr output_buffer; - - bool use_tf8; - float *output; - size_t output_size; -}; diff --git a/sunnypilot/modeld/runners/snpemodel.pxd b/sunnypilot/modeld/runners/snpemodel.pxd deleted file mode 100644 index f19501d37..000000000 --- a/sunnypilot/modeld/runners/snpemodel.pxd +++ /dev/null @@ -1,9 +0,0 @@ -# distutils: language = c++ - -from libcpp.string cimport string - -from msgq.visionipc.visionipc cimport cl_context - -cdef extern from "sunnypilot/modeld/runners/snpemodel.h": - cdef cppclass SNPEModel: - SNPEModel(string, float*, size_t, int, bool, cl_context) diff --git a/sunnypilot/modeld/runners/snpemodel_pyx.pyx b/sunnypilot/modeld/runners/snpemodel_pyx.pyx deleted file mode 100644 index d1f24d1ea..000000000 --- a/sunnypilot/modeld/runners/snpemodel_pyx.pyx +++ /dev/null @@ -1,17 +0,0 @@ -# distutils: language = c++ -# cython: c_string_encoding=ascii, language_level=3 - -import os -from libcpp cimport bool -from libcpp.string cimport string - -from .snpemodel cimport SNPEModel as cppSNPEModel -from sunnypilot.modeld.models.commonmodel_pyx cimport CLContext -from sunnypilot.modeld.runners.runmodel_pyx cimport RunModel -from sunnypilot.modeld.runners.runmodel cimport RunModel as cppRunModel - -os.environ['ADSP_LIBRARY_PATH'] = "/data/pythonpath/third_party/snpe/dsp/" - -cdef class SNPEModel(RunModel): - def __cinit__(self, string path, float[:] output, int runtime, bool use_tf8, CLContext context): - self.model = new cppSNPEModel(path, &output[0], len(output), runtime, use_tf8, context.context) diff --git a/sunnypilot/modeld/runners/thneedmodel.cc b/sunnypilot/modeld/runners/thneedmodel.cc deleted file mode 100644 index d83fc0a5f..000000000 --- a/sunnypilot/modeld/runners/thneedmodel.cc +++ /dev/null @@ -1,58 +0,0 @@ -#include "sunnypilot/modeld/runners/thneedmodel.h" - -#include - -#include "common/swaglog.h" - -ThneedModel::ThneedModel(const std::string path, float *_output, size_t _output_size, int runtime, bool luse_tf8, cl_context context) { - thneed = new Thneed(true, context); - thneed->load(path.c_str()); - thneed->clexec(); - - recorded = false; - output = _output; -} - -void* ThneedModel::getCLBuffer(const std::string name) { - int index = -1; - for (int i = 0; i < inputs.size(); i++) { - if (name == inputs[i]->name) { - index = i; - break; - } - } - - if (index == -1) { - LOGE("Tried to get CL buffer for input `%s` but no input with this name exists", name.c_str()); - assert(false); - } - - if (thneed->input_clmem.size() >= inputs.size()) { - return &thneed->input_clmem[inputs.size() - index - 1]; - } else { - return nullptr; - } -} - -void ThneedModel::execute() { - if (!recorded) { - thneed->record = true; - float *input_buffers[inputs.size()]; - for (int i = 0; i < inputs.size(); i++) { - input_buffers[inputs.size() - i - 1] = inputs[i]->buffer; - } - - thneed->copy_inputs(input_buffers); - thneed->clexec(); - thneed->copy_output(output); - thneed->stop(); - - recorded = true; - } else { - float *input_buffers[inputs.size()]; - for (int i = 0; i < inputs.size(); i++) { - input_buffers[inputs.size() - i - 1] = inputs[i]->buffer; - } - thneed->execute(input_buffers, output); - } -} diff --git a/sunnypilot/modeld/runners/thneedmodel.h b/sunnypilot/modeld/runners/thneedmodel.h deleted file mode 100644 index ecc7207c1..000000000 --- a/sunnypilot/modeld/runners/thneedmodel.h +++ /dev/null @@ -1,17 +0,0 @@ -#pragma once - -#include - -#include "sunnypilot/modeld/runners/runmodel.h" -#include "sunnypilot/modeld/thneed/thneed.h" - -class ThneedModel : public RunModel { -public: - ThneedModel(const std::string path, float *_output, size_t _output_size, int runtime, bool use_tf8 = false, cl_context context = NULL); - void *getCLBuffer(const std::string name); - void execute(); -private: - Thneed *thneed = NULL; - bool recorded; - float *output; -}; diff --git a/sunnypilot/modeld/runners/thneedmodel.pxd b/sunnypilot/modeld/runners/thneedmodel.pxd deleted file mode 100644 index ace7443b5..000000000 --- a/sunnypilot/modeld/runners/thneedmodel.pxd +++ /dev/null @@ -1,9 +0,0 @@ -# distutils: language = c++ - -from libcpp.string cimport string - -from msgq.visionipc.visionipc cimport cl_context - -cdef extern from "sunnypilot/modeld/runners/thneedmodel.h": - cdef cppclass ThneedModel: - ThneedModel(string, float*, size_t, int, bool, cl_context) diff --git a/sunnypilot/modeld/runners/thneedmodel_pyx.pyx b/sunnypilot/modeld/runners/thneedmodel_pyx.pyx deleted file mode 100644 index 49de8344c..000000000 --- a/sunnypilot/modeld/runners/thneedmodel_pyx.pyx +++ /dev/null @@ -1,14 +0,0 @@ -# distutils: language = c++ -# cython: c_string_encoding=ascii, language_level=3 - -from libcpp cimport bool -from libcpp.string cimport string - -from .thneedmodel cimport ThneedModel as cppThneedModel -from sunnypilot.modeld.models.commonmodel_pyx cimport CLContext -from sunnypilot.modeld.runners.runmodel_pyx cimport RunModel -from sunnypilot.modeld.runners.runmodel cimport RunModel as cppRunModel - -cdef class ThneedModel(RunModel): - def __cinit__(self, string path, float[:] output, int runtime, bool use_tf8, CLContext context): - self.model = new cppThneedModel(path, &output[0], len(output), runtime, use_tf8, context.context) diff --git a/sunnypilot/modeld/thneed/README b/sunnypilot/modeld/thneed/README deleted file mode 100644 index f3bc66d8f..000000000 --- a/sunnypilot/modeld/thneed/README +++ /dev/null @@ -1,8 +0,0 @@ -thneed is an SNPE accelerator. I know SNPE is already an accelerator, but sometimes things need to go even faster.. - -It runs on the local device, and caches a single model run. Then it replays it, but fast. - -thneed slices through abstraction layers like a fish. - -You need a thneed. - diff --git a/sunnypilot/modeld/thneed/__init__.py b/sunnypilot/modeld/thneed/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/sunnypilot/modeld/thneed/serialize.cc b/sunnypilot/modeld/thneed/serialize.cc deleted file mode 100644 index f9a8b288a..000000000 --- a/sunnypilot/modeld/thneed/serialize.cc +++ /dev/null @@ -1,154 +0,0 @@ -#include -#include - -#include "third_party/json11/json11.hpp" -#include "common/util.h" -#include "common/clutil.h" -#include "common/swaglog.h" -#include "sunnypilot/modeld/thneed/thneed.h" -using namespace json11; - -extern map g_program_source; - -void Thneed::load(const char *filename) { - LOGD("Thneed::load: loading from %s\n", filename); - - string buf = util::read_file(filename); - int jsz = *(int *)buf.data(); - string jsonerr; - string jj(buf.data() + sizeof(int), jsz); - Json jdat = Json::parse(jj, jsonerr); - - map real_mem; - real_mem[NULL] = NULL; - - int ptr = sizeof(int)+jsz; - for (auto &obj : jdat["objects"].array_items()) { - auto mobj = obj.object_items(); - int sz = mobj["size"].int_value(); - cl_mem clbuf = NULL; - - if (mobj["buffer_id"].string_value().size() > 0) { - // image buffer must already be allocated - clbuf = real_mem[*(cl_mem*)(mobj["buffer_id"].string_value().data())]; - assert(mobj["needs_load"].bool_value() == false); - } else { - if (mobj["needs_load"].bool_value()) { - clbuf = clCreateBuffer(context, CL_MEM_COPY_HOST_PTR | CL_MEM_READ_WRITE, sz, &buf[ptr], NULL); - if (debug >= 1) printf("loading %p %d @ 0x%X\n", clbuf, sz, ptr); - ptr += sz; - } else { - // TODO: is there a faster way to init zeroed out buffers? - void *host_zeros = calloc(sz, 1); - clbuf = clCreateBuffer(context, CL_MEM_COPY_HOST_PTR | CL_MEM_READ_WRITE, sz, host_zeros, NULL); - free(host_zeros); - } - } - assert(clbuf != NULL); - - if (mobj["arg_type"] == "image2d_t" || mobj["arg_type"] == "image1d_t") { - cl_image_desc desc = {0}; - desc.image_type = (mobj["arg_type"] == "image2d_t") ? CL_MEM_OBJECT_IMAGE2D : CL_MEM_OBJECT_IMAGE1D_BUFFER; - desc.image_width = mobj["width"].int_value(); - desc.image_height = mobj["height"].int_value(); - desc.image_row_pitch = mobj["row_pitch"].int_value(); - assert(sz == desc.image_height*desc.image_row_pitch); -#ifdef QCOM2 - desc.buffer = clbuf; -#else - // TODO: we are creating unused buffers on PC - clReleaseMemObject(clbuf); -#endif - cl_image_format format = {0}; - format.image_channel_order = CL_RGBA; - format.image_channel_data_type = mobj["float32"].bool_value() ? CL_FLOAT : CL_HALF_FLOAT; - - cl_int errcode; - -#ifndef QCOM2 - if (mobj["needs_load"].bool_value()) { - clbuf = clCreateImage(context, CL_MEM_COPY_HOST_PTR | CL_MEM_READ_WRITE, &format, &desc, &buf[ptr-sz], &errcode); - } else { - clbuf = clCreateImage(context, CL_MEM_READ_WRITE, &format, &desc, NULL, &errcode); - } -#else - clbuf = clCreateImage(context, CL_MEM_READ_WRITE, &format, &desc, NULL, &errcode); -#endif - if (clbuf == NULL) { - LOGE("clError: %s create image %zux%zu rp %zu with buffer %p\n", cl_get_error_string(errcode), - desc.image_width, desc.image_height, desc.image_row_pitch, desc.buffer); - } - assert(clbuf != NULL); - } - - real_mem[*(cl_mem*)(mobj["id"].string_value().data())] = clbuf; - } - - map g_programs; - for (const auto &[name, source] : jdat["programs"].object_items()) { - if (debug >= 1) printf("building %s with size %zu\n", name.c_str(), source.string_value().size()); - g_programs[name] = cl_program_from_source(context, device_id, source.string_value()); - } - - for (auto &obj : jdat["inputs"].array_items()) { - auto mobj = obj.object_items(); - int sz = mobj["size"].int_value(); - cl_mem aa = real_mem[*(cl_mem*)(mobj["buffer_id"].string_value().data())]; - input_clmem.push_back(aa); - input_sizes.push_back(sz); - LOGD("Thneed::load: adding input %s with size %d\n", mobj["name"].string_value().data(), sz); - - cl_int cl_err; - void *ret = clEnqueueMapBuffer(command_queue, aa, CL_TRUE, CL_MAP_WRITE, 0, sz, 0, NULL, NULL, &cl_err); - if (cl_err != CL_SUCCESS) LOGE("clError: %s map %p %d\n", cl_get_error_string(cl_err), aa, sz); - assert(cl_err == CL_SUCCESS); - inputs.push_back(ret); - } - - for (auto &obj : jdat["outputs"].array_items()) { - auto mobj = obj.object_items(); - int sz = mobj["size"].int_value(); - LOGD("Thneed::save: adding output with size %d\n", sz); - // TODO: support multiple outputs - output = real_mem[*(cl_mem*)(mobj["buffer_id"].string_value().data())]; - assert(output != NULL); - } - - for (auto &obj : jdat["binaries"].array_items()) { - string name = obj["name"].string_value(); - size_t length = obj["length"].int_value(); - if (debug >= 1) printf("binary %s with size %zu\n", name.c_str(), length); - g_programs[name] = cl_program_from_binary(context, device_id, (const uint8_t*)&buf[ptr], length); - ptr += length; - } - - for (auto &obj : jdat["kernels"].array_items()) { - auto gws = obj["global_work_size"]; - auto lws = obj["local_work_size"]; - auto kk = shared_ptr(new CLQueuedKernel(this)); - - kk->name = obj["name"].string_value(); - kk->program = g_programs[kk->name]; - kk->work_dim = obj["work_dim"].int_value(); - for (int i = 0; i < kk->work_dim; i++) { - kk->global_work_size[i] = gws[i].int_value(); - kk->local_work_size[i] = lws[i].int_value(); - } - kk->num_args = obj["num_args"].int_value(); - for (int i = 0; i < kk->num_args; i++) { - string arg = obj["args"].array_items()[i].string_value(); - int arg_size = obj["args_size"].array_items()[i].int_value(); - kk->args_size.push_back(arg_size); - if (arg_size == 8) { - cl_mem val = *(cl_mem*)(arg.data()); - val = real_mem[val]; - kk->args.push_back(string((char*)&val, sizeof(val))); - } else { - kk->args.push_back(arg); - } - } - kq.push_back(kk); - } - - clFinish(command_queue); -} diff --git a/sunnypilot/modeld/thneed/thneed.h b/sunnypilot/modeld/thneed/thneed.h deleted file mode 100644 index 47e18e0be..000000000 --- a/sunnypilot/modeld/thneed/thneed.h +++ /dev/null @@ -1,133 +0,0 @@ -#pragma once - -#ifndef __user -#define __user __attribute__(()) -#endif - -#include -#include -#include -#include -#include - -#include - -#include "third_party/linux/include/msm_kgsl.h" - -using namespace std; - -cl_int thneed_clSetKernelArg(cl_kernel kernel, cl_uint arg_index, size_t arg_size, const void *arg_value); - -namespace json11 { - class Json; -} -class Thneed; - -class GPUMalloc { - public: - GPUMalloc(int size, int fd); - ~GPUMalloc(); - void *alloc(int size); - private: - uint64_t base; - int remaining; -}; - -class CLQueuedKernel { - public: - CLQueuedKernel(Thneed *lthneed) { thneed = lthneed; } - CLQueuedKernel(Thneed *lthneed, - cl_kernel _kernel, - cl_uint _work_dim, - const size_t *_global_work_size, - const size_t *_local_work_size); - cl_int exec(); - void debug_print(bool verbose); - int get_arg_num(const char *search_arg_name); - cl_program program; - string name; - cl_uint num_args; - vector arg_names; - vector arg_types; - vector args; - vector args_size; - cl_kernel kernel = NULL; - json11::Json to_json() const; - - cl_uint work_dim; - size_t global_work_size[3] = {0}; - size_t local_work_size[3] = {0}; - private: - Thneed *thneed; -}; - -class CachedIoctl { - public: - virtual void exec() {} -}; - -class CachedSync: public CachedIoctl { - public: - CachedSync(Thneed *lthneed, string ldata) { thneed = lthneed; data = ldata; } - void exec(); - private: - Thneed *thneed; - string data; -}; - -class CachedCommand: public CachedIoctl { - public: - CachedCommand(Thneed *lthneed, struct kgsl_gpu_command *cmd); - void exec(); - private: - void disassemble(int cmd_index); - struct kgsl_gpu_command cache; - unique_ptr cmds; - unique_ptr objs; - Thneed *thneed; - vector > kq; -}; - -class Thneed { - public: - Thneed(bool do_clinit=false, cl_context _context = NULL); - void stop(); - void execute(float **finputs, float *foutput, bool slow=false); - void wait(); - - vector input_clmem; - vector inputs; - vector input_sizes; - cl_mem output = NULL; - - cl_context context = NULL; - cl_command_queue command_queue; - cl_device_id device_id; - int context_id; - - // protected? - bool record = false; - int debug; - int timestamp; - -#ifdef QCOM2 - unique_ptr ram; - vector > cmds; - int fd; -#endif - - // all CL kernels - void copy_inputs(float **finputs, bool internal=false); - void copy_output(float *foutput); - cl_int clexec(); - vector > kq; - - // pending CL kernels - vector > ckq; - - // loading - void load(const char *filename); - private: - void clinit(); -}; - diff --git a/sunnypilot/modeld/thneed/thneed_common.cc b/sunnypilot/modeld/thneed/thneed_common.cc deleted file mode 100644 index 56fbe70d8..000000000 --- a/sunnypilot/modeld/thneed/thneed_common.cc +++ /dev/null @@ -1,216 +0,0 @@ -#include "sunnypilot/modeld/thneed/thneed.h" - -#include -#include -#include - -#include "common/clutil.h" -#include "common/timing.h" - -map, string> g_args; -map, int> g_args_size; -map g_program_source; - -void Thneed::stop() { - //printf("Thneed::stop: recorded %lu commands\n", cmds.size()); - record = false; -} - -void Thneed::clinit() { - device_id = cl_get_device_id(CL_DEVICE_TYPE_DEFAULT); - if (context == NULL) context = CL_CHECK_ERR(clCreateContext(NULL, 1, &device_id, NULL, NULL, &err)); - //cl_command_queue_properties props[3] = {CL_QUEUE_PROPERTIES, CL_QUEUE_PROFILING_ENABLE, 0}; - cl_command_queue_properties props[3] = {CL_QUEUE_PROPERTIES, 0, 0}; - command_queue = CL_CHECK_ERR(clCreateCommandQueueWithProperties(context, device_id, props, &err)); - printf("Thneed::clinit done\n"); -} - -cl_int Thneed::clexec() { - if (debug >= 1) printf("Thneed::clexec: running %lu queued kernels\n", kq.size()); - for (auto &k : kq) { - if (record) ckq.push_back(k); - cl_int ret = k->exec(); - assert(ret == CL_SUCCESS); - } - return clFinish(command_queue); -} - -void Thneed::copy_inputs(float **finputs, bool internal) { - for (int idx = 0; idx < inputs.size(); ++idx) { - if (debug >= 1) printf("copying %lu -- %p -> %p (cl %p)\n", input_sizes[idx], finputs[idx], inputs[idx], input_clmem[idx]); - - if (internal) { - // if it's internal, using memcpy is fine since the buffer sync is cached in the ioctl layer - if (finputs[idx] != NULL) memcpy(inputs[idx], finputs[idx], input_sizes[idx]); - } else { - if (finputs[idx] != NULL) CL_CHECK(clEnqueueWriteBuffer(command_queue, input_clmem[idx], CL_TRUE, 0, input_sizes[idx], finputs[idx], 0, NULL, NULL)); - } - } -} - -void Thneed::copy_output(float *foutput) { - if (output != NULL) { - size_t sz; - clGetMemObjectInfo(output, CL_MEM_SIZE, sizeof(sz), &sz, NULL); - if (debug >= 1) printf("copying %lu for output %p -> %p\n", sz, output, foutput); - CL_CHECK(clEnqueueReadBuffer(command_queue, output, CL_TRUE, 0, sz, foutput, 0, NULL, NULL)); - } else { - printf("CAUTION: model output is NULL, does it have no outputs?\n"); - } -} - -// *********** CLQueuedKernel *********** - -CLQueuedKernel::CLQueuedKernel(Thneed *lthneed, - cl_kernel _kernel, - cl_uint _work_dim, - const size_t *_global_work_size, - const size_t *_local_work_size) { - thneed = lthneed; - kernel = _kernel; - work_dim = _work_dim; - assert(work_dim <= 3); - for (int i = 0; i < work_dim; i++) { - global_work_size[i] = _global_work_size[i]; - local_work_size[i] = _local_work_size[i]; - } - - char _name[0x100]; - clGetKernelInfo(kernel, CL_KERNEL_FUNCTION_NAME, sizeof(_name), _name, NULL); - name = string(_name); - clGetKernelInfo(kernel, CL_KERNEL_NUM_ARGS, sizeof(num_args), &num_args, NULL); - - // get args - for (int i = 0; i < num_args; i++) { - char arg_name[0x100] = {0}; - clGetKernelArgInfo(kernel, i, CL_KERNEL_ARG_NAME, sizeof(arg_name), arg_name, NULL); - arg_names.push_back(string(arg_name)); - clGetKernelArgInfo(kernel, i, CL_KERNEL_ARG_TYPE_NAME, sizeof(arg_name), arg_name, NULL); - arg_types.push_back(string(arg_name)); - - args.push_back(g_args[make_pair(kernel, i)]); - args_size.push_back(g_args_size[make_pair(kernel, i)]); - } - - // get program - clGetKernelInfo(kernel, CL_KERNEL_PROGRAM, sizeof(program), &program, NULL); -} - -int CLQueuedKernel::get_arg_num(const char *search_arg_name) { - for (int i = 0; i < num_args; i++) { - if (arg_names[i] == search_arg_name) return i; - } - printf("failed to find %s in %s\n", search_arg_name, name.c_str()); - assert(false); -} - -cl_int CLQueuedKernel::exec() { - if (kernel == NULL) { - kernel = clCreateKernel(program, name.c_str(), NULL); - arg_names.clear(); - arg_types.clear(); - - for (int j = 0; j < num_args; j++) { - char arg_name[0x100] = {0}; - clGetKernelArgInfo(kernel, j, CL_KERNEL_ARG_NAME, sizeof(arg_name), arg_name, NULL); - arg_names.push_back(string(arg_name)); - clGetKernelArgInfo(kernel, j, CL_KERNEL_ARG_TYPE_NAME, sizeof(arg_name), arg_name, NULL); - arg_types.push_back(string(arg_name)); - - cl_int ret; - if (args[j].size() != 0) { - assert(args[j].size() == args_size[j]); - ret = thneed_clSetKernelArg(kernel, j, args[j].size(), args[j].data()); - } else { - ret = thneed_clSetKernelArg(kernel, j, args_size[j], NULL); - } - assert(ret == CL_SUCCESS); - } - } - - if (thneed->debug >= 1) { - debug_print(thneed->debug >= 2); - } - - return clEnqueueNDRangeKernel(thneed->command_queue, - kernel, work_dim, NULL, global_work_size, local_work_size, 0, NULL, NULL); -} - -void CLQueuedKernel::debug_print(bool verbose) { - printf("%p %56s -- ", kernel, name.c_str()); - for (int i = 0; i < work_dim; i++) { - printf("%4zu ", global_work_size[i]); - } - printf(" -- "); - for (int i = 0; i < work_dim; i++) { - printf("%4zu ", local_work_size[i]); - } - printf("\n"); - - if (verbose) { - for (int i = 0; i < num_args; i++) { - string arg = args[i]; - printf(" %s %s", arg_types[i].c_str(), arg_names[i].c_str()); - void *arg_value = (void*)arg.data(); - int arg_size = arg.size(); - if (arg_size == 0) { - printf(" (size) %d", args_size[i]); - } else if (arg_size == 1) { - printf(" = %d", *((char*)arg_value)); - } else if (arg_size == 2) { - printf(" = %d", *((short*)arg_value)); - } else if (arg_size == 4) { - if (arg_types[i] == "float") { - printf(" = %f", *((float*)arg_value)); - } else { - printf(" = %d", *((int*)arg_value)); - } - } else if (arg_size == 8) { - cl_mem val = (cl_mem)(*((uintptr_t*)arg_value)); - printf(" = %p", val); - if (val != NULL) { - cl_mem_object_type obj_type; - clGetMemObjectInfo(val, CL_MEM_TYPE, sizeof(obj_type), &obj_type, NULL); - if (arg_types[i] == "image2d_t" || arg_types[i] == "image1d_t" || obj_type == CL_MEM_OBJECT_IMAGE2D) { - cl_image_format format; - size_t width, height, depth, array_size, row_pitch, slice_pitch; - cl_mem buf; - clGetImageInfo(val, CL_IMAGE_FORMAT, sizeof(format), &format, NULL); - assert(format.image_channel_order == CL_RGBA); - assert(format.image_channel_data_type == CL_HALF_FLOAT || format.image_channel_data_type == CL_FLOAT); - clGetImageInfo(val, CL_IMAGE_WIDTH, sizeof(width), &width, NULL); - clGetImageInfo(val, CL_IMAGE_HEIGHT, sizeof(height), &height, NULL); - clGetImageInfo(val, CL_IMAGE_ROW_PITCH, sizeof(row_pitch), &row_pitch, NULL); - clGetImageInfo(val, CL_IMAGE_DEPTH, sizeof(depth), &depth, NULL); - clGetImageInfo(val, CL_IMAGE_ARRAY_SIZE, sizeof(array_size), &array_size, NULL); - clGetImageInfo(val, CL_IMAGE_SLICE_PITCH, sizeof(slice_pitch), &slice_pitch, NULL); - assert(depth == 0); - assert(array_size == 0); - assert(slice_pitch == 0); - - clGetImageInfo(val, CL_IMAGE_BUFFER, sizeof(buf), &buf, NULL); - size_t sz = 0; - if (buf != NULL) clGetMemObjectInfo(buf, CL_MEM_SIZE, sizeof(sz), &sz, NULL); - printf(" image %zu x %zu rp %zu @ %p buffer %zu", width, height, row_pitch, buf, sz); - } else { - size_t sz; - clGetMemObjectInfo(val, CL_MEM_SIZE, sizeof(sz), &sz, NULL); - printf(" buffer %zu", sz); - } - } - } - printf("\n"); - } - } -} - -cl_int thneed_clSetKernelArg(cl_kernel kernel, cl_uint arg_index, size_t arg_size, const void *arg_value) { - g_args_size[make_pair(kernel, arg_index)] = arg_size; - if (arg_value != NULL) { - g_args[make_pair(kernel, arg_index)] = string((char*)arg_value, arg_size); - } else { - g_args[make_pair(kernel, arg_index)] = string(""); - } - cl_int ret = clSetKernelArg(kernel, arg_index, arg_size, arg_value); - return ret; -} diff --git a/sunnypilot/modeld/thneed/thneed_pc.cc b/sunnypilot/modeld/thneed/thneed_pc.cc deleted file mode 100644 index 629d0ee35..000000000 --- a/sunnypilot/modeld/thneed/thneed_pc.cc +++ /dev/null @@ -1,32 +0,0 @@ -#include "sunnypilot/modeld/thneed/thneed.h" - -#include - -#include "common/clutil.h" -#include "common/timing.h" - -Thneed::Thneed(bool do_clinit, cl_context _context) { - context = _context; - if (do_clinit) clinit(); - char *thneed_debug_env = getenv("THNEED_DEBUG"); - debug = (thneed_debug_env != NULL) ? atoi(thneed_debug_env) : 0; -} - -void Thneed::execute(float **finputs, float *foutput, bool slow) { - uint64_t tb, te; - if (debug >= 1) tb = nanos_since_boot(); - - // ****** copy inputs - copy_inputs(finputs); - - // ****** run commands - clexec(); - - // ****** copy outputs - copy_output(foutput); - - if (debug >= 1) { - te = nanos_since_boot(); - printf("model exec in %lu us\n", (te-tb)/1000); - } -} diff --git a/sunnypilot/modeld/thneed/thneed_qcom2.cc b/sunnypilot/modeld/thneed/thneed_qcom2.cc deleted file mode 100644 index b940da1ce..000000000 --- a/sunnypilot/modeld/thneed/thneed_qcom2.cc +++ /dev/null @@ -1,258 +0,0 @@ -#include "sunnypilot/modeld/thneed/thneed.h" - -#include -#include - -#include -#include -#include -#include -#include - -#include "common/clutil.h" -#include "common/timing.h" - -Thneed *g_thneed = NULL; -int g_fd = -1; - -void hexdump(uint8_t *d, int len) { - assert((len%4) == 0); - printf(" dumping %p len 0x%x\n", d, len); - for (int i = 0; i < len/4; i++) { - if (i != 0 && (i%0x10) == 0) printf("\n"); - printf("%8x ", d[i]); - } - printf("\n"); -} - -// *********** ioctl interceptor *********** - -extern "C" { - -int (*my_ioctl)(int filedes, unsigned long request, void *argp) = NULL; -#undef ioctl -int ioctl(int filedes, unsigned long request, void *argp) { - request &= 0xFFFFFFFF; // needed on QCOM2 - if (my_ioctl == NULL) my_ioctl = reinterpret_cast(dlsym(RTLD_NEXT, "ioctl")); - Thneed *thneed = g_thneed; - - // save the fd - if (request == IOCTL_KGSL_GPUOBJ_ALLOC) g_fd = filedes; - - // note that this runs always, even without a thneed object - if (request == IOCTL_KGSL_DRAWCTXT_CREATE) { - struct kgsl_drawctxt_create *create = (struct kgsl_drawctxt_create *)argp; - create->flags &= ~KGSL_CONTEXT_PRIORITY_MASK; - create->flags |= 6 << KGSL_CONTEXT_PRIORITY_SHIFT; // priority from 1-15, 1 is max priority - printf("IOCTL_KGSL_DRAWCTXT_CREATE: creating context with flags 0x%x\n", create->flags); - } - - if (thneed != NULL) { - if (request == IOCTL_KGSL_GPU_COMMAND) { - struct kgsl_gpu_command *cmd = (struct kgsl_gpu_command *)argp; - if (thneed->record) { - thneed->timestamp = cmd->timestamp; - thneed->context_id = cmd->context_id; - thneed->cmds.push_back(unique_ptr(new CachedCommand(thneed, cmd))); - } - if (thneed->debug >= 1) { - printf("IOCTL_KGSL_GPU_COMMAND(%2zu): flags: 0x%lx context_id: %u timestamp: %u numcmds: %d numobjs: %d\n", - thneed->cmds.size(), - cmd->flags, - cmd->context_id, cmd->timestamp, cmd->numcmds, cmd->numobjs); - } - } else if (request == IOCTL_KGSL_GPUOBJ_SYNC) { - struct kgsl_gpuobj_sync *cmd = (struct kgsl_gpuobj_sync *)argp; - struct kgsl_gpuobj_sync_obj *objs = (struct kgsl_gpuobj_sync_obj *)(cmd->objs); - - if (thneed->debug >= 2) { - printf("IOCTL_KGSL_GPUOBJ_SYNC count:%d ", cmd->count); - for (int i = 0; i < cmd->count; i++) { - printf(" -- offset:0x%lx len:0x%lx id:%d op:%d ", objs[i].offset, objs[i].length, objs[i].id, objs[i].op); - } - printf("\n"); - } - - if (thneed->record) { - thneed->cmds.push_back(unique_ptr(new - CachedSync(thneed, string((char *)objs, sizeof(struct kgsl_gpuobj_sync_obj)*cmd->count)))); - } - } else if (request == IOCTL_KGSL_DEVICE_WAITTIMESTAMP_CTXTID) { - struct kgsl_device_waittimestamp_ctxtid *cmd = (struct kgsl_device_waittimestamp_ctxtid *)argp; - if (thneed->debug >= 1) { - printf("IOCTL_KGSL_DEVICE_WAITTIMESTAMP_CTXTID: context_id: %d timestamp: %d timeout: %d\n", - cmd->context_id, cmd->timestamp, cmd->timeout); - } - } else if (request == IOCTL_KGSL_SETPROPERTY) { - if (thneed->debug >= 1) { - struct kgsl_device_getproperty *prop = (struct kgsl_device_getproperty *)argp; - printf("IOCTL_KGSL_SETPROPERTY: 0x%x sizebytes:%zu\n", prop->type, prop->sizebytes); - if (thneed->debug >= 2) { - hexdump((uint8_t *)prop->value, prop->sizebytes); - if (prop->type == KGSL_PROP_PWR_CONSTRAINT) { - struct kgsl_device_constraint *constraint = (struct kgsl_device_constraint *)prop->value; - hexdump((uint8_t *)constraint->data, constraint->size); - } - } - } - } else if (request == IOCTL_KGSL_DRAWCTXT_CREATE || request == IOCTL_KGSL_DRAWCTXT_DESTROY) { - // this happens - } else if (request == IOCTL_KGSL_GPUOBJ_ALLOC || request == IOCTL_KGSL_GPUOBJ_FREE) { - // this happens - } else { - if (thneed->debug >= 1) { - printf("other ioctl %lx\n", request); - } - } - } - - int ret = my_ioctl(filedes, request, argp); - // NOTE: This error message goes into stdout and messes up pyenv - // if (ret != 0) printf("ioctl returned %d with errno %d\n", ret, errno); - return ret; -} - -} - -// *********** GPUMalloc *********** - -GPUMalloc::GPUMalloc(int size, int fd) { - struct kgsl_gpuobj_alloc alloc; - memset(&alloc, 0, sizeof(alloc)); - alloc.size = size; - alloc.flags = 0x10000a00; - ioctl(fd, IOCTL_KGSL_GPUOBJ_ALLOC, &alloc); - void *addr = mmap64(NULL, alloc.mmapsize, 0x3, 0x1, fd, alloc.id*0x1000); - assert(addr != MAP_FAILED); - - base = (uint64_t)addr; - remaining = size; -} - -GPUMalloc::~GPUMalloc() { - // TODO: free the GPU malloced area -} - -void *GPUMalloc::alloc(int size) { - void *ret = (void*)base; - size = (size+0xff) & (~0xFF); - assert(size <= remaining); - remaining -= size; - base += size; - return ret; -} - -// *********** CachedSync, at the ioctl layer *********** - -void CachedSync::exec() { - struct kgsl_gpuobj_sync cmd; - - cmd.objs = (uint64_t)data.data(); - cmd.obj_len = data.length(); - cmd.count = data.length() / sizeof(struct kgsl_gpuobj_sync_obj); - - int ret = ioctl(thneed->fd, IOCTL_KGSL_GPUOBJ_SYNC, &cmd); - assert(ret == 0); -} - -// *********** CachedCommand, at the ioctl layer *********** - -CachedCommand::CachedCommand(Thneed *lthneed, struct kgsl_gpu_command *cmd) { - thneed = lthneed; - assert(cmd->numsyncs == 0); - - memcpy(&cache, cmd, sizeof(cache)); - - if (cmd->numcmds > 0) { - cmds = make_unique(cmd->numcmds); - memcpy(cmds.get(), (void *)cmd->cmdlist, sizeof(struct kgsl_command_object)*cmd->numcmds); - cache.cmdlist = (uint64_t)cmds.get(); - for (int i = 0; i < cmd->numcmds; i++) { - void *nn = thneed->ram->alloc(cmds[i].size); - memcpy(nn, (void*)cmds[i].gpuaddr, cmds[i].size); - cmds[i].gpuaddr = (uint64_t)nn; - } - } - - if (cmd->numobjs > 0) { - objs = make_unique(cmd->numobjs); - memcpy(objs.get(), (void *)cmd->objlist, sizeof(struct kgsl_command_object)*cmd->numobjs); - cache.objlist = (uint64_t)objs.get(); - for (int i = 0; i < cmd->numobjs; i++) { - void *nn = thneed->ram->alloc(objs[i].size); - memset(nn, 0, objs[i].size); - objs[i].gpuaddr = (uint64_t)nn; - } - } - - kq = thneed->ckq; - thneed->ckq.clear(); -} - -void CachedCommand::exec() { - cache.timestamp = ++thneed->timestamp; - int ret = ioctl(thneed->fd, IOCTL_KGSL_GPU_COMMAND, &cache); - - if (thneed->debug >= 1) printf("CachedCommand::exec got %d\n", ret); - - if (thneed->debug >= 2) { - for (auto &it : kq) { - it->debug_print(false); - } - } - - assert(ret == 0); -} - -// *********** Thneed *********** - -Thneed::Thneed(bool do_clinit, cl_context _context) { - // TODO: QCOM2 actually requires a different context - //context = _context; - if (do_clinit) clinit(); - assert(g_fd != -1); - fd = g_fd; - ram = make_unique(0x80000, fd); - timestamp = -1; - g_thneed = this; - char *thneed_debug_env = getenv("THNEED_DEBUG"); - debug = (thneed_debug_env != NULL) ? atoi(thneed_debug_env) : 0; -} - -void Thneed::wait() { - struct kgsl_device_waittimestamp_ctxtid wait; - wait.context_id = context_id; - wait.timestamp = timestamp; - wait.timeout = -1; - - uint64_t tb = nanos_since_boot(); - int wret = ioctl(fd, IOCTL_KGSL_DEVICE_WAITTIMESTAMP_CTXTID, &wait); - uint64_t te = nanos_since_boot(); - - if (debug >= 1) printf("wait %d after %lu us\n", wret, (te-tb)/1000); -} - -void Thneed::execute(float **finputs, float *foutput, bool slow) { - uint64_t tb, te; - if (debug >= 1) tb = nanos_since_boot(); - - // ****** copy inputs - copy_inputs(finputs, true); - - // ****** run commands - int i = 0; - for (auto &it : cmds) { - ++i; - if (debug >= 1) printf("run %2d @ %7lu us: ", i, (nanos_since_boot()-tb)/1000); - it->exec(); - if ((i == cmds.size()) || slow) wait(); - } - - // ****** copy outputs - copy_output(foutput); - - if (debug >= 1) { - te = nanos_since_boot(); - printf("model exec in %lu us\n", (te-tb)/1000); - } -} diff --git a/sunnypilot/modeld/transforms/loadyuv.cc b/sunnypilot/modeld/transforms/loadyuv.cc deleted file mode 100644 index c93f5cd03..000000000 --- a/sunnypilot/modeld/transforms/loadyuv.cc +++ /dev/null @@ -1,76 +0,0 @@ -#include "selfdrive/modeld/transforms/loadyuv.h" - -#include -#include -#include - -void loadyuv_init(LoadYUVState* s, cl_context ctx, cl_device_id device_id, int width, int height) { - memset(s, 0, sizeof(*s)); - - s->width = width; - s->height = height; - - char args[1024]; - snprintf(args, sizeof(args), - "-cl-fast-relaxed-math -cl-denorms-are-zero " - "-DTRANSFORMED_WIDTH=%d -DTRANSFORMED_HEIGHT=%d", - width, height); - cl_program prg = cl_program_from_file(ctx, device_id, LOADYUV_PATH, args); - - s->loadys_krnl = CL_CHECK_ERR(clCreateKernel(prg, "loadys", &err)); - s->loaduv_krnl = CL_CHECK_ERR(clCreateKernel(prg, "loaduv", &err)); - s->copy_krnl = CL_CHECK_ERR(clCreateKernel(prg, "copy", &err)); - - // done with this - CL_CHECK(clReleaseProgram(prg)); -} - -void loadyuv_destroy(LoadYUVState* s) { - CL_CHECK(clReleaseKernel(s->loadys_krnl)); - CL_CHECK(clReleaseKernel(s->loaduv_krnl)); - CL_CHECK(clReleaseKernel(s->copy_krnl)); -} - -void loadyuv_queue(LoadYUVState* s, cl_command_queue q, - cl_mem y_cl, cl_mem u_cl, cl_mem v_cl, - cl_mem out_cl) { - cl_int global_out_off = 0; - - CL_CHECK(clSetKernelArg(s->loadys_krnl, 0, sizeof(cl_mem), &y_cl)); - CL_CHECK(clSetKernelArg(s->loadys_krnl, 1, sizeof(cl_mem), &out_cl)); - CL_CHECK(clSetKernelArg(s->loadys_krnl, 2, sizeof(cl_int), &global_out_off)); - - const size_t loadys_work_size = (s->width*s->height)/8; - CL_CHECK(clEnqueueNDRangeKernel(q, s->loadys_krnl, 1, NULL, - &loadys_work_size, NULL, 0, 0, NULL)); - - const size_t loaduv_work_size = ((s->width/2)*(s->height/2))/8; - global_out_off += (s->width*s->height); - - CL_CHECK(clSetKernelArg(s->loaduv_krnl, 0, sizeof(cl_mem), &u_cl)); - CL_CHECK(clSetKernelArg(s->loaduv_krnl, 1, sizeof(cl_mem), &out_cl)); - CL_CHECK(clSetKernelArg(s->loaduv_krnl, 2, sizeof(cl_int), &global_out_off)); - - CL_CHECK(clEnqueueNDRangeKernel(q, s->loaduv_krnl, 1, NULL, - &loaduv_work_size, NULL, 0, 0, NULL)); - - global_out_off += (s->width/2)*(s->height/2); - - CL_CHECK(clSetKernelArg(s->loaduv_krnl, 0, sizeof(cl_mem), &v_cl)); - CL_CHECK(clSetKernelArg(s->loaduv_krnl, 1, sizeof(cl_mem), &out_cl)); - CL_CHECK(clSetKernelArg(s->loaduv_krnl, 2, sizeof(cl_int), &global_out_off)); - - CL_CHECK(clEnqueueNDRangeKernel(q, s->loaduv_krnl, 1, NULL, - &loaduv_work_size, NULL, 0, 0, NULL)); -} - -void copy_queue(LoadYUVState* s, cl_command_queue q, cl_mem src, cl_mem dst, - size_t src_offset, size_t dst_offset, size_t size) { - CL_CHECK(clSetKernelArg(s->copy_krnl, 0, sizeof(cl_mem), &src)); - CL_CHECK(clSetKernelArg(s->copy_krnl, 1, sizeof(cl_mem), &dst)); - CL_CHECK(clSetKernelArg(s->copy_krnl, 2, sizeof(cl_int), &src_offset)); - CL_CHECK(clSetKernelArg(s->copy_krnl, 3, sizeof(cl_int), &dst_offset)); - const size_t copy_work_size = size/8; - CL_CHECK(clEnqueueNDRangeKernel(q, s->copy_krnl, 1, NULL, - ©_work_size, NULL, 0, 0, NULL)); -} \ No newline at end of file diff --git a/sunnypilot/modeld/transforms/loadyuv.cl b/sunnypilot/modeld/transforms/loadyuv.cl deleted file mode 100644 index 970187a6d..000000000 --- a/sunnypilot/modeld/transforms/loadyuv.cl +++ /dev/null @@ -1,47 +0,0 @@ -#define UV_SIZE ((TRANSFORMED_WIDTH/2)*(TRANSFORMED_HEIGHT/2)) - -__kernel void loadys(__global uchar8 const * const Y, - __global uchar * out, - int out_offset) -{ - const int gid = get_global_id(0); - const int ois = gid * 8; - const int oy = ois / TRANSFORMED_WIDTH; - const int ox = ois % TRANSFORMED_WIDTH; - - const uchar8 ys = Y[gid]; - - // 02 - // 13 - - __global uchar* outy0; - __global uchar* outy1; - if ((oy & 1) == 0) { - outy0 = out + out_offset; //y0 - outy1 = out + out_offset + UV_SIZE*2; //y2 - } else { - outy0 = out + out_offset + UV_SIZE; //y1 - outy1 = out + out_offset + UV_SIZE*3; //y3 - } - - vstore4(ys.s0246, 0, outy0 + (oy/2) * (TRANSFORMED_WIDTH/2) + ox/2); - vstore4(ys.s1357, 0, outy1 + (oy/2) * (TRANSFORMED_WIDTH/2) + ox/2); -} - -__kernel void loaduv(__global uchar8 const * const in, - __global uchar8 * out, - int out_offset) -{ - const int gid = get_global_id(0); - const uchar8 inv = in[gid]; - out[gid + out_offset / 8] = inv; -} - -__kernel void copy(__global uchar8 * in, - __global uchar8 * out, - int in_offset, - int out_offset) -{ - const int gid = get_global_id(0); - out[gid + out_offset / 8] = in[gid + in_offset / 8]; -} diff --git a/sunnypilot/modeld/transforms/loadyuv.h b/sunnypilot/modeld/transforms/loadyuv.h deleted file mode 100644 index 659059cd2..000000000 --- a/sunnypilot/modeld/transforms/loadyuv.h +++ /dev/null @@ -1,20 +0,0 @@ -#pragma once - -#include "common/clutil.h" - -typedef struct { - int width, height; - cl_kernel loadys_krnl, loaduv_krnl, copy_krnl; -} LoadYUVState; - -void loadyuv_init(LoadYUVState* s, cl_context ctx, cl_device_id device_id, int width, int height); - -void loadyuv_destroy(LoadYUVState* s); - -void loadyuv_queue(LoadYUVState* s, cl_command_queue q, - cl_mem y_cl, cl_mem u_cl, cl_mem v_cl, - cl_mem out_cl); - - -void copy_queue(LoadYUVState* s, cl_command_queue q, cl_mem src, cl_mem dst, - size_t src_offset, size_t dst_offset, size_t size); \ No newline at end of file diff --git a/sunnypilot/modeld/transforms/transform.cc b/sunnypilot/modeld/transforms/transform.cc deleted file mode 100644 index 305643cf4..000000000 --- a/sunnypilot/modeld/transforms/transform.cc +++ /dev/null @@ -1,97 +0,0 @@ -#include "selfdrive/modeld/transforms/transform.h" - -#include -#include - -#include "common/clutil.h" - -void transform_init(Transform* s, cl_context ctx, cl_device_id device_id) { - memset(s, 0, sizeof(*s)); - - cl_program prg = cl_program_from_file(ctx, device_id, TRANSFORM_PATH, ""); - s->krnl = CL_CHECK_ERR(clCreateKernel(prg, "warpPerspective", &err)); - // done with this - CL_CHECK(clReleaseProgram(prg)); - - s->m_y_cl = CL_CHECK_ERR(clCreateBuffer(ctx, CL_MEM_READ_WRITE, 3*3*sizeof(float), NULL, &err)); - s->m_uv_cl = CL_CHECK_ERR(clCreateBuffer(ctx, CL_MEM_READ_WRITE, 3*3*sizeof(float), NULL, &err)); -} - -void transform_destroy(Transform* s) { - CL_CHECK(clReleaseMemObject(s->m_y_cl)); - CL_CHECK(clReleaseMemObject(s->m_uv_cl)); - CL_CHECK(clReleaseKernel(s->krnl)); -} - -void transform_queue(Transform* s, - cl_command_queue q, - cl_mem in_yuv, int in_width, int in_height, int in_stride, int in_uv_offset, - cl_mem out_y, cl_mem out_u, cl_mem out_v, - int out_width, int out_height, - const mat3& projection) { - const int zero = 0; - - // sampled using pixel center origin - // (because that's how fastcv and opencv does it) - - mat3 projection_y = projection; - - // in and out uv is half the size of y. - mat3 projection_uv = transform_scale_buffer(projection, 0.5); - - CL_CHECK(clEnqueueWriteBuffer(q, s->m_y_cl, CL_TRUE, 0, 3*3*sizeof(float), (void*)projection_y.v, 0, NULL, NULL)); - CL_CHECK(clEnqueueWriteBuffer(q, s->m_uv_cl, CL_TRUE, 0, 3*3*sizeof(float), (void*)projection_uv.v, 0, NULL, NULL)); - - const int in_y_width = in_width; - const int in_y_height = in_height; - const int in_y_px_stride = 1; - const int in_uv_width = in_width/2; - const int in_uv_height = in_height/2; - const int in_uv_px_stride = 2; - const int in_u_offset = in_uv_offset; - const int in_v_offset = in_uv_offset + 1; - - const int out_y_width = out_width; - const int out_y_height = out_height; - const int out_uv_width = out_width/2; - const int out_uv_height = out_height/2; - - CL_CHECK(clSetKernelArg(s->krnl, 0, sizeof(cl_mem), &in_yuv)); // src - CL_CHECK(clSetKernelArg(s->krnl, 1, sizeof(cl_int), &in_stride)); // src_row_stride - CL_CHECK(clSetKernelArg(s->krnl, 2, sizeof(cl_int), &in_y_px_stride)); // src_px_stride - CL_CHECK(clSetKernelArg(s->krnl, 3, sizeof(cl_int), &zero)); // src_offset - CL_CHECK(clSetKernelArg(s->krnl, 4, sizeof(cl_int), &in_y_height)); // src_rows - CL_CHECK(clSetKernelArg(s->krnl, 5, sizeof(cl_int), &in_y_width)); // src_cols - CL_CHECK(clSetKernelArg(s->krnl, 6, sizeof(cl_mem), &out_y)); // dst - CL_CHECK(clSetKernelArg(s->krnl, 7, sizeof(cl_int), &out_y_width)); // dst_row_stride - CL_CHECK(clSetKernelArg(s->krnl, 8, sizeof(cl_int), &zero)); // dst_offset - CL_CHECK(clSetKernelArg(s->krnl, 9, sizeof(cl_int), &out_y_height)); // dst_rows - CL_CHECK(clSetKernelArg(s->krnl, 10, sizeof(cl_int), &out_y_width)); // dst_cols - CL_CHECK(clSetKernelArg(s->krnl, 11, sizeof(cl_mem), &s->m_y_cl)); // M - - const size_t work_size_y[2] = {(size_t)out_y_width, (size_t)out_y_height}; - - CL_CHECK(clEnqueueNDRangeKernel(q, s->krnl, 2, NULL, - (const size_t*)&work_size_y, NULL, 0, 0, NULL)); - - const size_t work_size_uv[2] = {(size_t)out_uv_width, (size_t)out_uv_height}; - - CL_CHECK(clSetKernelArg(s->krnl, 2, sizeof(cl_int), &in_uv_px_stride)); // src_px_stride - CL_CHECK(clSetKernelArg(s->krnl, 3, sizeof(cl_int), &in_u_offset)); // src_offset - CL_CHECK(clSetKernelArg(s->krnl, 4, sizeof(cl_int), &in_uv_height)); // src_rows - CL_CHECK(clSetKernelArg(s->krnl, 5, sizeof(cl_int), &in_uv_width)); // src_cols - CL_CHECK(clSetKernelArg(s->krnl, 6, sizeof(cl_mem), &out_u)); // dst - CL_CHECK(clSetKernelArg(s->krnl, 7, sizeof(cl_int), &out_uv_width)); // dst_row_stride - CL_CHECK(clSetKernelArg(s->krnl, 8, sizeof(cl_int), &zero)); // dst_offset - CL_CHECK(clSetKernelArg(s->krnl, 9, sizeof(cl_int), &out_uv_height)); // dst_rows - CL_CHECK(clSetKernelArg(s->krnl, 10, sizeof(cl_int), &out_uv_width)); // dst_cols - CL_CHECK(clSetKernelArg(s->krnl, 11, sizeof(cl_mem), &s->m_uv_cl)); // M - - CL_CHECK(clEnqueueNDRangeKernel(q, s->krnl, 2, NULL, - (const size_t*)&work_size_uv, NULL, 0, 0, NULL)); - CL_CHECK(clSetKernelArg(s->krnl, 3, sizeof(cl_int), &in_v_offset)); // src_ofset - CL_CHECK(clSetKernelArg(s->krnl, 6, sizeof(cl_mem), &out_v)); // dst - - CL_CHECK(clEnqueueNDRangeKernel(q, s->krnl, 2, NULL, - (const size_t*)&work_size_uv, NULL, 0, 0, NULL)); -} diff --git a/sunnypilot/modeld/transforms/transform.cl b/sunnypilot/modeld/transforms/transform.cl deleted file mode 100644 index 2ca25920c..000000000 --- a/sunnypilot/modeld/transforms/transform.cl +++ /dev/null @@ -1,54 +0,0 @@ -#define INTER_BITS 5 -#define INTER_TAB_SIZE (1 << INTER_BITS) -#define INTER_SCALE 1.f / INTER_TAB_SIZE - -#define INTER_REMAP_COEF_BITS 15 -#define INTER_REMAP_COEF_SCALE (1 << INTER_REMAP_COEF_BITS) - -__kernel void warpPerspective(__global const uchar * src, - int src_row_stride, int src_px_stride, int src_offset, int src_rows, int src_cols, - __global uchar * dst, - int dst_row_stride, int dst_offset, int dst_rows, int dst_cols, - __constant float * M) -{ - int dx = get_global_id(0); - int dy = get_global_id(1); - - if (dx < dst_cols && dy < dst_rows) - { - float X0 = M[0] * dx + M[1] * dy + M[2]; - float Y0 = M[3] * dx + M[4] * dy + M[5]; - float W = M[6] * dx + M[7] * dy + M[8]; - W = W != 0.0f ? INTER_TAB_SIZE / W : 0.0f; - int X = rint(X0 * W), Y = rint(Y0 * W); - - int sx = convert_short_sat(X >> INTER_BITS); - int sy = convert_short_sat(Y >> INTER_BITS); - - short sx_clamp = clamp(sx, 0, src_cols - 1); - short sx_p1_clamp = clamp(sx + 1, 0, src_cols - 1); - short sy_clamp = clamp(sy, 0, src_rows - 1); - short sy_p1_clamp = clamp(sy + 1, 0, src_rows - 1); - int v0 = convert_int(src[mad24(sy_clamp, src_row_stride, src_offset + sx_clamp*src_px_stride)]); - int v1 = convert_int(src[mad24(sy_clamp, src_row_stride, src_offset + sx_p1_clamp*src_px_stride)]); - int v2 = convert_int(src[mad24(sy_p1_clamp, src_row_stride, src_offset + sx_clamp*src_px_stride)]); - int v3 = convert_int(src[mad24(sy_p1_clamp, src_row_stride, src_offset + sx_p1_clamp*src_px_stride)]); - - short ay = (short)(Y & (INTER_TAB_SIZE - 1)); - short ax = (short)(X & (INTER_TAB_SIZE - 1)); - float taby = 1.f/INTER_TAB_SIZE*ay; - float tabx = 1.f/INTER_TAB_SIZE*ax; - - int dst_index = mad24(dy, dst_row_stride, dst_offset + dx); - - int itab0 = convert_short_sat_rte( (1.0f-taby)*(1.0f-tabx) * INTER_REMAP_COEF_SCALE ); - int itab1 = convert_short_sat_rte( (1.0f-taby)*tabx * INTER_REMAP_COEF_SCALE ); - int itab2 = convert_short_sat_rte( taby*(1.0f-tabx) * INTER_REMAP_COEF_SCALE ); - int itab3 = convert_short_sat_rte( taby*tabx * INTER_REMAP_COEF_SCALE ); - - int val = v0 * itab0 + v1 * itab1 + v2 * itab2 + v3 * itab3; - - uchar pix = convert_uchar_sat((val + (1 << (INTER_REMAP_COEF_BITS-1))) >> INTER_REMAP_COEF_BITS); - dst[dst_index] = pix; - } -} diff --git a/sunnypilot/modeld/transforms/transform.h b/sunnypilot/modeld/transforms/transform.h deleted file mode 100644 index 771a7054b..000000000 --- a/sunnypilot/modeld/transforms/transform.h +++ /dev/null @@ -1,25 +0,0 @@ -#pragma once - -#define CL_USE_DEPRECATED_OPENCL_1_2_APIS -#ifdef __APPLE__ -#include -#else -#include -#endif - -#include "common/mat.h" - -typedef struct { - cl_kernel krnl; - cl_mem m_y_cl, m_uv_cl; -} Transform; - -void transform_init(Transform* s, cl_context ctx, cl_device_id device_id); - -void transform_destroy(Transform* transform); - -void transform_queue(Transform* s, cl_command_queue q, - cl_mem yuv, int in_width, int in_height, int in_stride, int in_uv_offset, - cl_mem out_y, cl_mem out_u, cl_mem out_v, - int out_width, int out_height, - const mat3& projection); diff --git a/sunnypilot/models/helpers.py b/sunnypilot/models/helpers.py index a53551b4e..fe6ac2133 100644 --- a/sunnypilot/models/helpers.py +++ b/sunnypilot/models/helpers.py @@ -21,7 +21,6 @@ async def verify_file(file_path: str, expected_hash: str) -> bool: return sha256_hash.hexdigest().lower() == expected_hash.lower() - def get_active_bundle(params: Params) -> custom.ModelManagerSP.ModelBundle: """Gets the active model bundle from cache""" if params is None: @@ -31,23 +30,3 @@ def get_active_bundle(params: Params) -> custom.ModelManagerSP.ModelBundle: return messaging.log_from_bytes(active_bundle, custom.ModelManagerSP.ModelBundle) return None - - -def get_model_runner_by_filename(filename: str) -> custom.ModelManagerSP.Runner: - if filename.endswith(".thneed"): - return custom.ModelManagerSP.Runner.snpe - - if filename.endswith("_tinygrad.pkl"): - return custom.ModelManagerSP.Runner.tinygrad - - -def get_active_model_runner(params: Params) -> custom.ModelManagerSP.Runner: - """Gets the model runner from the active model bundle. If no active bundle, returns tinygrad""" - if params is None: - params = Params() - - if active_bundle := get_active_bundle(params): - drive_model = next(model for model in active_bundle.models if model.type == custom.ModelManagerSP.Type.drive) - return get_model_runner_by_filename(drive_model.fileName) - - return custom.ModelManagerSP.Runner.tinygrad diff --git a/system/manager/process_config.py b/system/manager/process_config.py index 5483f2d9c..9712b63e0 100644 --- a/system/manager/process_config.py +++ b/system/manager/process_config.py @@ -1,12 +1,10 @@ import os import operator -from cereal import car, custom +from cereal import car from openpilot.common.params import Params from openpilot.system.hardware import PC, TICI from openpilot.system.manager.process import PythonProcess, NativeProcess, DaemonProcess - -from sunnypilot.models.helpers import get_active_model_runner from sunnypilot.sunnylink.utils import sunnylink_need_register, sunnylink_ready, use_sunnylink_uploader WEBCAM = os.getenv("USE_WEBCAM") is not None @@ -72,15 +70,6 @@ def use_sunnylink_uploader_shim(started, params, CP: car.CarParams) -> bool: """Shim for use_sunnylink_uploader to match the process manager signature.""" return use_sunnylink_uploader(params) -def is_snpe_model(started, params, CP: car.CarParams) -> bool: - """Check if the active model runner is SNPE.""" - # TODO-SP: I want to do a little more optimization here to only check this once when we've transitioned from offroad to onroad. - return bool(get_active_model_runner(params) == custom.ModelManagerSP.Runner.snpe) - -def is_stock_model(started, params, CP: car.CarParams) -> bool: - """Check if the active model runner is stock.""" - return not is_snpe_model(started, params, CP) - def or_(*fns): return lambda *args: operator.or_(*(fn(*args) for fn in fns)) @@ -103,7 +92,7 @@ procs = [ NativeProcess("stream_encoderd", "system/loggerd", ["./encoderd", "--stream"], notcar), NativeProcess("loggerd", "system/loggerd", ["./loggerd"], logging), # TODO Make python process once TG allows opening QCOM from child proc - NativeProcess("modeld", "selfdrive/modeld", ["./modeld"], and_(only_onroad, is_stock_model)), + NativeProcess("modeld", "selfdrive/modeld", ["./modeld"], only_onroad), NativeProcess("sensord", "system/sensord", ["./sensord"], only_onroad, enabled=not PC), NativeProcess("ui", "selfdrive/ui", ["./ui"], always_run, watchdog_max_dt=(5 if not PC else None)), PythonProcess("soundd", "selfdrive.ui.soundd", only_onroad), @@ -145,7 +134,6 @@ procs = [ # sunnypilot procs += [ PythonProcess("models_manager", "sunnypilot.models.manager", only_offroad), - NativeProcess("modeld_snpe", "sunnypilot/modeld", ["./modeld"], and_(only_onroad, is_snpe_model)), ] if os.path.exists("./github_runner.sh"):