rollmebacksooon

Introduce `self.desire_reshape_dims` to dynamically handle desire input reshaping using metadata. Update desire 20Hz reshaping logic for improved adaptability and maintainability.

.codespellignore

@@ -1,2 +0,0 @@
-Wen
-REGIST

.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

.github/workflows/ui_preview.yaml

@@ -86,7 +86,7 @@ jobs:
         run: >-
           sudo apt-get install -y imagemagick
 
-          scenes="homescreen settings_device settings_software settings_sunnylink settings_toggles settings_sunnypilot settings_sunnypilot_mads settings_developer offroad_alert update_available prime onroad onroad_disengaged onroad_override onroad_sidebar onroad_wide onroad_wide_sidebar onroad_alert_small onroad_alert_mid onroad_alert_full driver_camera body keyboard"
+          scenes="homescreen settings_device settings_software settings_toggles settings_developer offroad_alert update_available prime onroad onroad_disengaged onroad_override onroad_sidebar onroad_wide onroad_wide_sidebar onroad_alert_small onroad_alert_mid onroad_alert_full driver_camera body keyboard"
           A=($scenes)
 
           DIFF=""

.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

.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

SConstruct

@@ -74,12 +74,6 @@ AddOption('--minimal',
           default=os.path.exists(File('#.lfsconfig').abspath), # minimal by default on release branch (where there's no LFS)
           help='the minimum build to run openpilot. no tests, tools, etc.')
 
-AddOption('--stock-ui',
-          action='store_true',
-          dest='stock_ui',
-          default=False,
-          help='Build stock openpilot UI instead of sunnypilot UI')
-
 ## Architecture name breakdown (arch)
 ## - larch64: linux tici aarch64
 ## - aarch64: linux pc aarch64
@@ -178,10 +172,6 @@ else:
 if arch != "Darwin":
   ldflags += ["-Wl,--as-needed", "-Wl,--no-undefined"]
 
-if not GetOption('stock_ui'):
-  cflags += ["-DSUNNYPILOT"]
-  cxxflags += ["-DSUNNYPILOT"]
-
 ccflags_option = GetOption('ccflags')
 if ccflags_option:
   ccflags += ccflags_option.split(' ')
@@ -396,8 +386,6 @@ 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":

cereal/custom.capnp

@@ -8,77 +8,10 @@ $Cxx.namespace("cereal");
 # cereal, so use these if you want custom events in your fork.
 
 # you can rename the struct, but don't change the identifier
-struct SelfdriveStateSP @0x81c2f05a394cf4af {
-  mads @0 :ModularAssistiveDrivingSystem;
-
-  struct ModularAssistiveDrivingSystem {
-    state @0 :ModularAssistiveDrivingSystemState;
-    enabled @1 :Bool;
-    active @2 :Bool;
-    available @3 :Bool;
-
-    enum ModularAssistiveDrivingSystemState {
-      disabled @0;
-      paused @1;
-      enabled @2;
-      softDisabling @3;
-      overriding @4;
-    }
-  }
+struct CustomReserved0 @0x81c2f05a394cf4af {
 }
 
-struct ModelManagerSP @0xaedffd8f31e7b55d {
-  activeBundle @0 :ModelBundle;
-  selectedBundle @1 :ModelBundle;
-  availableBundles @2 :List(ModelBundle);
-
-  struct DownloadUri {
-    uri @0 :Text;
-    sha256 @1 :Text;
-  }
-
-  enum Type {
-    drive @0;
-    navigation @1;
-    metadata @2;
-  }
-
-  struct Model {
-    fullName @0 :Text;
-    fileName @1 :Text;
-    downloadUri @2 :DownloadUri;
-    downloadProgress @3 :DownloadProgress;
-    type @4 :Type;
-  }
-
-  enum DownloadStatus {
-    notDownloading @0;
-    downloading @1;
-    downloaded @2;
-    cached @3;
-    failed @4;
-  }
-
-  struct DownloadProgress {
-    status @0 :DownloadStatus;
-    progress @1 :Float32;
-    eta @2 :UInt32;
-  }
-  
-  enum Runner {
-    snpe @0;
-    tinygrad @1;
-  }
-
-  struct ModelBundle {
-    index @0 :UInt32;
-    internalName @1 :Text;
-    displayName @2 :Text;
-    models @3 :List(Model);
-    status @4 :DownloadStatus;
-    generation @5 :UInt32;
-    environment @6 :Text;
-  }
+struct CustomReserved1 @0xaedffd8f31e7b55d {
 }
 
 struct CustomReserved2 @0xf35cc4560bbf6ec2 {

cereal/log.capnp

@@ -125,79 +125,6 @@ struct OnroadEvent @0xc4fa6047f024e718 {
     espActive @90;
     personalityChanged @91;
     aeb @92;
-    eventReserved93 @93;
-    eventReserved94 @94;
-    eventReserved95 @95;
-    eventReserved96 @96;
-    eventReserved97 @97;
-    eventReserved98 @98;
-    eventReserved99 @99;
-    eventReserved100 @100;
-    eventReserved101 @101;
-    eventReserved102 @102;
-    eventReserved103 @103;
-    eventReserved104 @104;
-    eventReserved105 @105;
-    eventReserved106 @106;
-    eventReserved107 @107;
-    eventReserved108 @108;
-    eventReserved109 @109;
-    eventReserved110 @110;
-    eventReserved111 @111;
-    eventReserved112 @112;
-    eventReserved113 @113;
-    eventReserved114 @114;
-    eventReserved115 @115;
-    eventReserved116 @116;
-    eventReserved117 @117;
-    eventReserved118 @118;
-    eventReserved119 @119;
-    eventReserved120 @120;
-    eventReserved121 @121;
-    eventReserved122 @122;
-    eventReserved123 @123;
-    eventReserved124 @124;
-    eventReserved125 @125;
-    eventReserved126 @126;
-    eventReserved127 @127;
-    eventReserved128 @128;
-    eventReserved129 @129;
-    eventReserved130 @130;
-    eventReserved131 @131;
-    eventReserved132 @132;
-    eventReserved133 @133;
-    eventReserved134 @134;
-    eventReserved135 @135;
-    eventReserved136 @136;
-    eventReserved137 @137;
-    eventReserved138 @138;
-    eventReserved139 @139;
-    eventReserved140 @140;
-    eventReserved141 @141;
-    eventReserved142 @142;
-    eventReserved143 @143;
-    eventReserved144 @144;
-    eventReserved145 @145;
-    eventReserved146 @146;
-    eventReserved147 @147;
-    eventReserved148 @148;
-    eventReserved149 @149;
-    eventReserved150 @150;
-
-    # sunnypilot
-    lkasEnable @151;
-    lkasDisable @152;
-    manualSteeringRequired @153;
-    manualLongitudinalRequired @154;
-    silentLkasEnable @155;
-    silentLkasDisable @156;
-    silentBrakeHold @157;
-    silentWrongGear @158;
-    silentReverseGear @159;
-    silentDoorOpen @160;
-    silentSeatbeltNotLatched @161;
-    silentParkBrake @162;
-    controlsMismatchLateral @163;
 
     soundsUnavailableDEPRECATED @47;
   }
@@ -662,7 +589,6 @@ struct PandaState @0xa7649e2575e4591e {
 
   # safety stuff
   controlsAllowed @3 :Bool;
-  controlsAllowedLat @5 :Bool;
   safetyRxInvalid @19 :UInt32;
   safetyTxBlocked @24 :UInt32;
   safetyModel @14 :Car.CarParams.SafetyModel;
@@ -770,6 +696,7 @@ struct PandaState @0xa7649e2575e4591e {
   }
 
   gasInterceptorDetectedDEPRECATED @4 :Bool;
+  startedSignalDetectedDEPRECATED @5 :Bool;
   hasGpsDEPRECATED @6 :Bool;
   gmlanSendErrsDEPRECATED @9 :UInt32;
   fanSpeedRpmDEPRECATED @11 :UInt16;
@@ -2631,8 +2558,8 @@ struct Event {
     customReservedRawData2 @126 :Data;
 
     # *********** Custom: reserved for forks ***********
-    selfdriveStateSP @107 :Custom.SelfdriveStateSP;
-    modelManagerSP @108 :Custom.ModelManagerSP;
+    customReserved0 @107 :Custom.CustomReserved0;
+    customReserved1 @108 :Custom.CustomReserved1;
     customReserved2 @109 :Custom.CustomReserved2;
     customReserved3 @110 :Custom.CustomReserved3;
     customReserved4 @111 :Custom.CustomReserved4;

cereal/services.py

@@ -74,10 +74,6 @@ _services: dict[str, tuple] = {
   "userFlag": (True, 0., 1),
   "microphone": (True, 10., 10),
 
-  # sunnypilot
-  "modelManagerSP": (False, 1., 1),
-  "selfdriveStateSP": (True, 100., 10),
-
   # debug
   "uiDebug": (True, 0., 1),
   "testJoystick": (True, 0.),

common/api/__init__.py

@@ -1,27 +1,46 @@
-from openpilot.common.api.comma_connect import CommaConnectApi
-from sunnypilot.sunnylink.api import SunnylinkApi
+import jwt
+import os
+import requests
+from datetime import datetime, timedelta, UTC
+from openpilot.system.hardware.hw import Paths
+from openpilot.system.version import get_version
 
+API_HOST = os.getenv('API_HOST', 'https://api.commadotai.com')
 
 class Api:
-  def __init__(self, dongle_id, use_sunnylink=False):
-    if use_sunnylink:
-      self.service = SunnylinkApi(dongle_id)
-    else:
-      self.service = CommaConnectApi(dongle_id)
-
-  def request(self, method, endpoint, **params):
-    return self.service.request(method, endpoint, **params)
+  def __init__(self, dongle_id):
+    self.dongle_id = dongle_id
+    with open(Paths.persist_root()+'/comma/id_rsa') as f:
+      self.private_key = f.read()
 
   def get(self, *args, **kwargs):
-    return self.service.get(*args, **kwargs)
+    return self.request('GET', *args, **kwargs)
 
   def post(self, *args, **kwargs):
-    return self.service.post(*args, **kwargs)
+    return self.request('POST', *args, **kwargs)
+
+  def request(self, method, endpoint, timeout=None, access_token=None, **params):
+    return api_get(endpoint, method=method, timeout=timeout, access_token=access_token, **params)
 
   def get_token(self, expiry_hours=1):
-    return self.service.get_token(expiry_hours)
+    now = datetime.now(UTC).replace(tzinfo=None)
+    payload = {
+      'identity': self.dongle_id,
+      'nbf': now,
+      'iat': now,
+      'exp': now + timedelta(hours=expiry_hours)
+    }
+    token = jwt.encode(payload, self.private_key, algorithm='RS256')
+    if isinstance(token, bytes):
+      token = token.decode('utf8')
+    return token
 
 
-def api_get(endpoint, method='GET', timeout=None, access_token=None, use_sunnylink=False, **params):
-  return SunnylinkApi(None).api_get(endpoint, method, timeout, access_token, **params) if use_sunnylink \
-    else CommaConnectApi(None).api_get(endpoint, method, timeout, access_token, **params)
+def api_get(endpoint, method='GET', timeout=None, access_token=None, **params):
+  headers = {}
+  if access_token is not None:
+    headers['Authorization'] = "JWT " + access_token
+
+  headers['User-Agent'] = "openpilot-" + get_version()
+
+  return requests.request(method, API_HOST + "/" + endpoint, timeout=timeout, headers=headers, params=params)

common/api/base.py

@@ -1,56 +0,0 @@
-import jwt
-import requests
-import unicodedata
-from datetime import datetime, timedelta, UTC
-from openpilot.system.hardware.hw import Paths
-from openpilot.system.version import get_version
-
-
-class BaseApi:
-  def __init__(self, dongle_id, api_host, user_agent="openpilot-"):
-    self.dongle_id = dongle_id
-    self.api_host = api_host
-    self.user_agent = user_agent
-    with open(f'{Paths.persist_root()}/comma/id_rsa') as f:
-      self.private_key = f.read()
-
-  def get(self, *args, **kwargs):
-    return self.request('GET', *args, **kwargs)
-
-  def post(self, *args, **kwargs):
-    return self.request('POST', *args, **kwargs)
-
-  def request(self, method, endpoint, timeout=None, access_token=None, **params):
-    return self.api_get(endpoint, method=method, timeout=timeout, access_token=access_token, **params)
-
-  def _get_token(self, expiry_hours=1, **extra_payload):
-    now = datetime.now(UTC).replace(tzinfo=None)
-    payload = {
-      'identity': self.dongle_id,
-      'nbf': now,
-      'iat': now,
-      'exp': now + timedelta(hours=expiry_hours),
-      **extra_payload
-    }
-    token = jwt.encode(payload, self.private_key, algorithm='RS256')
-    if isinstance(token, bytes):
-      token = token.decode('utf8')
-    return token
-
-  def get_token(self, expiry_hours=1):
-    return self._get_token(expiry_hours)
-
-  def remove_non_ascii_chars(self, text):
-    normalized_text = unicodedata.normalize('NFD', text)
-    ascii_encoded_text = normalized_text.encode('ascii', 'ignore')
-    return ascii_encoded_text.decode()
-
-  def api_get(self, endpoint, method='GET', timeout=None, access_token=None, **params):
-    headers = {}
-    if access_token is not None:
-      headers['Authorization'] = "JWT " + access_token
-
-    version = self.remove_non_ascii_chars(get_version())
-    headers['User-Agent'] = self.user_agent + version
-
-    return requests.request(method, f"{self.api_host}/{endpoint}", timeout=timeout, headers=headers, params=params)

common/api/comma_connect.py

@@ -1,11 +0,0 @@
-import os
-
-from openpilot.common.api.base import BaseApi
-
-API_HOST = os.getenv('API_HOST', 'https://api.commadotai.com')
-
-
-class CommaConnectApi(BaseApi):
-  def __init__(self, dongle_id):
-    super().__init__(dongle_id, API_HOST)
-    self.user_agent = "openpilot-"

common/params.cc

@@ -109,36 +109,36 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"CurrentBootlog", PERSISTENT},
     {"CurrentRoute", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
     {"DisableLogging", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
-    {"DisablePowerDown", PERSISTENT | BACKUP},
-    {"DisableUpdates", PERSISTENT | BACKUP},
-    {"DisengageOnAccelerator", PERSISTENT | BACKUP},
+    {"DisablePowerDown", PERSISTENT},
+    {"DisableUpdates", PERSISTENT},
+    {"DisengageOnAccelerator", PERSISTENT},
     {"DongleId", PERSISTENT},
     {"DoReboot", CLEAR_ON_MANAGER_START},
     {"DoShutdown", CLEAR_ON_MANAGER_START},
     {"DoUninstall", CLEAR_ON_MANAGER_START},
-    {"ExperimentalLongitudinalEnabled", PERSISTENT | DEVELOPMENT_ONLY | BACKUP},
-    {"ExperimentalMode", PERSISTENT | BACKUP},
-    {"ExperimentalModeConfirmed", PERSISTENT | BACKUP},
+    {"ExperimentalLongitudinalEnabled", PERSISTENT | DEVELOPMENT_ONLY},
+    {"ExperimentalMode", PERSISTENT},
+    {"ExperimentalModeConfirmed", PERSISTENT},
     {"FirmwareQueryDone", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
     {"ForcePowerDown", PERSISTENT},
     {"GitBranch", PERSISTENT},
     {"GitCommit", PERSISTENT},
     {"GitCommitDate", PERSISTENT},
     {"GitDiff", PERSISTENT},
-    {"GithubSshKeys", PERSISTENT | BACKUP},
-    {"GithubUsername", PERSISTENT | BACKUP},
+    {"GithubSshKeys", PERSISTENT},
+    {"GithubUsername", PERSISTENT},
     {"GitRemote", PERSISTENT},
-    {"GsmApn", PERSISTENT | BACKUP},
-    {"GsmMetered", PERSISTENT | BACKUP},
-    {"GsmRoaming", PERSISTENT | BACKUP},
+    {"GsmApn", PERSISTENT},
+    {"GsmMetered", PERSISTENT},
+    {"GsmRoaming", PERSISTENT},
     {"HardwareSerial", PERSISTENT},
     {"HasAcceptedTerms", PERSISTENT},
     {"IMEI", PERSISTENT},
     {"InstallDate", PERSISTENT},
     {"IsDriverViewEnabled", CLEAR_ON_MANAGER_START},
     {"IsEngaged", PERSISTENT},
-    {"IsLdwEnabled", PERSISTENT | BACKUP},
-    {"IsMetric", PERSISTENT | BACKUP},
+    {"IsLdwEnabled", PERSISTENT},
+    {"IsMetric", PERSISTENT},
     {"IsOffroad", CLEAR_ON_MANAGER_START},
     {"IsOnroad", PERSISTENT},
     {"IsRhdDetected", PERSISTENT},
@@ -146,7 +146,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"IsTakingSnapshot", CLEAR_ON_MANAGER_START},
     {"IsTestedBranch", CLEAR_ON_MANAGER_START},
     {"JoystickDebugMode", CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION},
-    {"LanguageSetting", PERSISTENT | BACKUP},
+    {"LanguageSetting", PERSISTENT},
     {"LastAthenaPingTime", CLEAR_ON_MANAGER_START},
     {"LastGPSPosition", PERSISTENT},
     {"LastManagerExitReason", CLEAR_ON_MANAGER_START},
@@ -158,7 +158,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"LiveTorqueParameters", PERSISTENT | DONT_LOG},
     {"LocationFilterInitialState", PERSISTENT},
     {"LongitudinalManeuverMode", CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION},
-    {"LongitudinalPersonality", PERSISTENT | BACKUP},
+    {"LongitudinalPersonality", PERSISTENT},
     {"NetworkMetered", PERSISTENT},
     {"ObdMultiplexingChanged", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
     {"ObdMultiplexingEnabled", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
@@ -174,17 +174,17 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"Offroad_TemperatureTooHigh", CLEAR_ON_MANAGER_START},
     {"Offroad_UnofficialHardware", CLEAR_ON_MANAGER_START},
     {"Offroad_UpdateFailed", CLEAR_ON_MANAGER_START},
-    {"OpenpilotEnabledToggle", PERSISTENT | BACKUP},
+    {"OpenpilotEnabledToggle", PERSISTENT},
     {"PandaHeartbeatLost", CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION},
     {"PandaSomResetTriggered", CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION},
     {"PandaSignatures", CLEAR_ON_MANAGER_START},
     {"PrimeType", PERSISTENT},
-    {"RecordFront", PERSISTENT | BACKUP},
+    {"RecordFront", PERSISTENT},
     {"RecordFrontLock", PERSISTENT},  // for the internal fleet
-    {"SecOCKey", PERSISTENT | DONT_LOG},  // Candidate for | BACKUP
+    {"SecOCKey", PERSISTENT | DONT_LOG},
     {"RouteCount", PERSISTENT},
     {"SnoozeUpdate", CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION},
-    {"SshEnabled", PERSISTENT | BACKUP},
+    {"SshEnabled", PERSISTENT},
     {"TermsVersion", PERSISTENT},
     {"TrainingVersion", PERSISTENT},
     {"UbloxAvailable", PERSISTENT},
@@ -200,28 +200,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"UpdaterTargetBranch", CLEAR_ON_MANAGER_START},
     {"UpdaterLastFetchTime", PERSISTENT},
     {"Version", PERSISTENT},
-
-    // --- sunnypilot params --- //
-    {"EnableGithubRunner", PERSISTENT | BACKUP},
-
-    // MADS params
-    {"Mads", PERSISTENT | BACKUP},
-    {"MadsMainCruiseAllowed", PERSISTENT | BACKUP},
-    {"MadsPauseLateralOnBrake", PERSISTENT | BACKUP},
-    {"MadsUnifiedEngagementMode", PERSISTENT | BACKUP},
-
-    // Model Manager params
-    {"ModelManager_ActiveBundle", PERSISTENT},
-    {"ModelManager_DownloadIndex", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
-    {"ModelManager_LastSyncTime", CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION},
-    {"ModelManager_ModelsCache", PERSISTENT | BACKUP},
-
-    // sunnylink params
-    {"EnableSunnylinkUploader", PERSISTENT | BACKUP},
-    {"LastSunnylinkPingTime", CLEAR_ON_MANAGER_START},
-    {"SunnylinkDongleId", PERSISTENT},
-    {"SunnylinkdPid", PERSISTENT},
-    {"SunnylinkEnabled", PERSISTENT},
+    {"EnableGithubRunner", PERSISTENT},
 };
 
 } // namespace

common/params.h

@@ -16,7 +16,6 @@ enum ParamKeyType {
   CLEAR_ON_OFFROAD_TRANSITION = 0x10,
   DONT_LOG = 0x20,
   DEVELOPMENT_ONLY = 0x40,
-  BACKUP = 0x80,
   ALL = 0xFFFFFFFF
 };
 

pyproject.toml

@@ -42,7 +42,8 @@ dependencies = [
 
   # modeld
   "onnx >= 1.14.0",
-  "onnxruntime >=1.16.3",
+  "onnxruntime >=1.16.3; platform_system == 'Linux' and platform_machine == 'aarch64'",
+  "onnxruntime-gpu >=1.16.3; platform_system == 'Linux' and platform_machine == 'x86_64'",
 
   # logging
   "pyzmq",
@@ -137,7 +138,7 @@ 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"
@@ -163,7 +164,6 @@ testpaths = [
   "tools/replay",
   "tools/cabana",
   "cereal/messaging/tests",
-  "sunnypilot",
 ]
 
 [tool.codespell]

release/ci/squash_and_merge.py

@@ -1,361 +0,0 @@
-#!/usr/bin/env python3
-import argparse
-import subprocess
-import sys
-import shutil
-import signal
-import contextlib
-import tempfile
-import os
-
-
-def run_command(command: str) -> tuple[int, str, str]:
-  """Run a shell command and return exit code, stdout, and stderr."""
-  process = subprocess.Popen(
-    command,
-    shell=True,
-    stdout=subprocess.PIPE,
-    stderr=subprocess.PIPE,
-    text=True
-  )
-  stdout, stderr = process.communicate()
-  return process.returncode, stdout.strip(), stderr.strip()
-
-
-def is_gh_available() -> bool:
-  """Check if GitHub CLI is available."""
-  return shutil.which('gh') is not None
-
-
-def get_current_branch() -> str | None:
-  """Get the name of the current git branch."""
-  code, output, error = run_command("git rev-parse --abbrev-ref HEAD")
-  if code != 0:
-    print(f"Error getting current branch: {error}")
-    return None
-  return output
-
-
-def backup_branch(branch_name: str) -> bool:
-  """Create a backup of the current branch."""
-  backup_name = f"{branch_name}-backup-$(date +%Y%m%d_%H%M%S)"
-  code, _, error = run_command(f"git branch {backup_name}")
-  if code != 0:
-    print(f"Error creating backup branch: {error}")
-    return False
-  print(f"Created backup branch: {backup_name}")
-  return True
-
-
-def get_commit_messages(source_branch: str, target_branch: str) -> list[str] | None:
-  """Get all commit messages between source and target branches."""
-  code, output, error = run_command(f"git log {target_branch}..{source_branch} --format=%B")
-  if code != 0:
-    print(f"Error getting commit messages: {error}")
-    return None
-  return [msg.strip() for msg in output.splitlines() if msg and not msg.startswith('Merge')]
-
-
-def get_pr_info(branch_name: str) -> str | None:
-  """Get PR title using GitHub CLI."""
-  if not is_gh_available():
-    print("Warning: GitHub CLI not found. Install it to auto-fetch PR titles:")
-    print("  https://cli.github.com/")
-    return None
-
-  # Try to get PR info using gh cli
-  code, output, error = run_command(f"gh pr view --json title --jq .title {branch_name}")
-  if code != 0:
-    print(f"No open PR found for branch '{branch_name}'")
-    return None
-
-  return output
-
-
-def create_squash_message(pr_title: str | None, commit_messages: list[str], source_branch: str) -> str:
-  """Create a squash commit message from PR title and commit messages."""
-  parts = []
-
-  # Add PR title if provided
-  if pr_title:
-    parts.append(pr_title)
-  else:
-    parts.append(f"Squashed changes from {source_branch}")
-  parts.append("")  # Empty line after title
-
-  # Add original commits section
-  if commit_messages:
-    parts.append("Original commits:")
-    parts.append("")  # Empty line before list
-    parts.extend(f"* {msg}" for msg in commit_messages)
-
-  return '\n'.join(parts)
-
-
-def prompt_for_title() -> str:
-  """Prompt user for a commit title."""
-  return input("Enter commit title (or press Enter to use default): ").strip()
-
-
-@contextlib.contextmanager
-def workspace_manager(original_branch: str):
-  """Context manager to handle workspace state and cleanup."""
-  stash_created = False
-  stash_restored = False
-  temp_branch: str | None = None
-
-  def cleanup_handler(signum=None, frame=None):
-    """Clean up workspace state."""
-    nonlocal temp_branch, stash_created, stash_restored
-    try:
-      if signum and stash_restored:
-        # If we're handling Ctrl+C but stash was already restored,
-        # just clean up branches and exit
-        current = get_current_branch()
-        if current and current != original_branch:
-          run_command(f"git checkout {original_branch}")
-        if temp_branch:
-          run_command(f"git branch -D {temp_branch}")
-        print("\nOperation interrupted, but changes were already restored.")
-        sys.exit(1)
-
-      # First, switch back to original branch
-      current = get_current_branch()
-      if current and current != original_branch:
-        run_command(f"git checkout {original_branch}")
-
-      # Then clean up temp branch
-      if temp_branch:
-        run_command(f"git branch -D {temp_branch}")
-
-      # Finally, restore stash if needed - AFTER switching branches
-      if stash_created and not stash_restored:
-        print("Restoring your uncommitted changes...")
-        code, stash_list, _ = run_command("git stash list")
-        if code == 0 and "Automatic stash by squash script" in stash_list:
-          run_command("git stash pop")
-          stash_restored = True
-          stash_created = False
-
-      if signum:
-        print("\nOperation interrupted. Cleaned up and restored original state.")
-        sys.exit(1)
-
-    except Exception as e:
-      print(f"Error during cleanup: {e}")
-      if signum:
-        sys.exit(1)
-
-  try:
-    # Set up signal handlers
-    signal.signal(signal.SIGINT, cleanup_handler)
-    signal.signal(signal.SIGTERM, cleanup_handler)
-
-    # Check for changes (including untracked files)
-    code, output, _ = run_command("git status --porcelain")
-    if output:
-      print("Stashing uncommitted changes...")
-      run_command("git stash push -u -m 'Automatic stash by squash script'")
-      stash_created = True
-
-    yield lambda x: setattr(x, 'temp_branch', temp_branch)
-
-  except Exception as e:
-    print(f"\nError occurred: {str(e)}")
-    cleanup_handler()
-    raise
-  finally:
-    cleanup_handler()
-
-
-def create_commit_with_message(message: str) -> bool:
-  """Create a commit with the given message using a temporary file."""
-  try:
-    with tempfile.NamedTemporaryFile(mode='w', delete=False) as f:
-      f.write(message)
-      temp_path = f.name
-
-    # Use the temporary file for the commit message
-    code, _, error = run_command(f"git commit -F {temp_path}")
-    os.unlink(temp_path)  # Clean up the temp file
-
-    if code != 0:
-      print(f"Error creating commit: {error}")
-      return False
-    return True
-  except Exception as e:
-    print(f"Error handling commit message: {e}")
-    if os.path.exists(temp_path):
-      os.unlink(temp_path)
-    return False
-
-
-def squash_and_merge(source_branch: str, target_branch: str, manual_title: str | None, backup: bool = False, push: bool = False) -> bool:
-  """
-  Squash the source branch and merge into target branch.
-  """
-  # Get original branch right away
-  original_branch = get_current_branch()
-  if not original_branch:
-    return False
-
-  class State:
-    temp_branch: str | None = None
-
-  state = State()
-
-  with workspace_manager(original_branch) as set_temp_branch:
-    # Validate source branch exists
-    code, _, error = run_command(f"git rev-parse --verify {source_branch}")
-    if code != 0:
-      print(f"Error: Source branch {source_branch} not found")
-      return False
-
-    if source_branch == target_branch:
-      print(f"Error: Source and target branches cannot be the same ({source_branch})")
-      return False
-
-    # Ensure target branch exists
-    code, _, error = run_command(f"git rev-parse --verify {target_branch}")
-    if code != 0:
-      print(f"Error: Target branch {target_branch} not found")
-      return False
-
-    # Find merge base
-    code, merge_base, error = run_command(f"git merge-base {target_branch} {source_branch}")
-    if code != 0:
-      print(f"Error finding merge base: {error}")
-      return False
-
-    # Create backup unless explicitly skipped
-    if backup and not backup_branch(source_branch):
-      return False
-
-    # Get commit messages
-    commit_messages = get_commit_messages(source_branch, target_branch)
-    if commit_messages is None:
-      return False
-
-    # Get title (priority: manual title > PR title > prompt user)
-    title = manual_title
-    if not title:
-      title = get_pr_info(source_branch)
-    if not title:
-      title = prompt_for_title()
-
-    try:
-      # Create and switch to temporary branch
-      temp_branch = f"temp-squash-{source_branch}"
-      state.temp_branch = temp_branch
-      set_temp_branch(state)
-
-      print(f"\nCreating temporary branch {temp_branch}...")
-      code, _, error = run_command(f"git checkout -b {temp_branch} {source_branch}")
-      if code != 0:
-        print(f"Error creating temp branch: {error}")
-        return False
-
-      print("Preparing squash by resetting temporary branch to merge base...")
-      code, _, error = run_command(f"git reset --soft {merge_base}")
-      if code != 0:
-        print(f"Error resetting for squash: {error}")
-        return False
-
-      # Create commit with message
-      print("Creating squash commit...")
-      squash_message = create_squash_message(title, commit_messages, source_branch)
-      if not create_commit_with_message(squash_message):
-        return False
-
-      # Switch to target and try merge
-      print(f"\nSwitching to target branch {target_branch}...")
-      code, _, error = run_command(f"git checkout {target_branch}")
-      if code != 0:
-        print(f"Error checking out target branch: {error}")
-        return False
-
-      print(f"Attempting to merge changes from {temp_branch}...")
-      code, _, error = run_command(f"git merge {temp_branch}")
-
-      if code != 0:
-        print(f"\nMerge failed with error: {error}")
-        print("\nThe squash was successful, and your changes are preserved in the temporary branch.")
-        print("To complete the merge manually, follow these steps:")
-        print(f"\n1. Your squashed changes are in branch: '{temp_branch}'")
-        print(f"2. The target branch is: '{target_branch}'")
-        print("\nTo resolve the conflicts:")
-        print(f"   git checkout {target_branch}")
-        print(f"   git merge {temp_branch}")
-        print("   # resolve conflicts in your editor")
-        print("   git add <resolved-files>")
-        print("   git commit")
-        print(f"   git push origin {target_branch}  # when ready to push")
-        print("\nTo clean up after successful merge:")
-        print(f"   git branch -D {temp_branch}")
-
-        # Make sure to abort the merge
-        print("\nAborting current merge attempt...")
-        run_command("git merge --abort")
-
-        # Return to original branch, but keep temp branch
-        print(f"Returning to {original_branch}...")
-        run_command(f"git checkout {original_branch}")
-        return False
-
-      # Clean up temp branch on success
-      run_command(f"git branch -D {temp_branch}")
-
-      # Push if requested
-      if push:
-        code, _, error = run_command(f"git push origin {target_branch}")
-        if code != 0:
-          print(f"Error pushing to {target_branch}: {error}")
-          return False
-        print(f"Successfully pushed to {target_branch}")
-      else:
-        print(f"Changes squashed and merged into {target_branch} locally")
-        print(f"To push the changes: git push origin {target_branch}")
-
-      # Return to original branch
-      code, _, error = run_command(f"git checkout {original_branch}")
-      if code != 0:
-        print(f"Warning: Failed to return to original branch: {error}")
-        return False
-
-      return True
-
-    except Exception as e:
-      print(f"Error during squash process: {e}")
-      return False
-
-
-def main():
-  parser = argparse.ArgumentParser(
-    description='Squash branch and merge into target branch'
-  )
-  parser.add_argument('--target', '-t', required=True,
-                      help='Target branch to merge changes into')
-  parser.add_argument('--source', '-s',
-                      help='Source branch to squash (default: current branch)')
-  parser.add_argument('--title', '-m',
-                      help='Optional manual title (overrides PR title)')
-  parser.add_argument('--backup', action='store_true',
-                      help='Creates a backup branch for the source branch')
-  parser.add_argument('--push', action='store_true',
-                      help='Push changes to remote after squashing')
-
-  args = parser.parse_args()
-
-  # Determine source branch early
-  source_branch = args.source
-  if not source_branch:
-    source_branch = get_current_branch()
-    if not source_branch:
-      sys.exit(1)
-
-  if not squash_and_merge(source_branch, args.target, args.title, args.backup, args.push):
-    sys.exit(1)
-
-
-if __name__ == "__main__":
-  main()

release/release_files.py

@@ -91,7 +91,7 @@ whitelist = [
   "tools/joystick/",
   "tools/longitudinal_maneuvers/",
 
-  "tinygrad_repo/examples/openpilot/compile3.py",
+  "tinygrad_repo/openpilot/compile2.py",
   "tinygrad_repo/extra/onnx.py",
   "tinygrad_repo/extra/onnx_ops.py",
   "tinygrad_repo/extra/thneed.py",

scripts/lint/lint.sh

@@ -57,7 +57,7 @@ function run_tests() {
 
   if [[ -z "$FAST" ]]; then
     run "mypy" mypy $PYTHON_FILES
-    run "codespell" codespell $ALL_FILES --ignore-words=$ROOT/.codespellignore
+    run "codespell" codespell $ALL_FILES
   fi
 
   return $FAILED

selfdrive/car/card.py

@@ -22,8 +22,6 @@ from openpilot.selfdrive.pandad import can_capnp_to_list, can_list_to_can_capnp
 from openpilot.selfdrive.car.cruise import VCruiseHelper
 from openpilot.selfdrive.car.car_specific import MockCarState
 
-from openpilot.sunnypilot.mads.mads import MadsParams
-
 REPLAY = "REPLAY" in os.environ
 
 EventName = log.OnroadEvent.EventName
@@ -115,10 +113,6 @@ class Car:
     if not disengage_on_accelerator:
       self.CP.alternativeExperience |= ALTERNATIVE_EXPERIENCE.DISABLE_DISENGAGE_ON_GAS
 
-    # mads
-    MadsParams().set_alternative_experience(self.CP)
-    MadsParams().set_car_specific_params(self.CP)
-
     openpilot_enabled_toggle = self.params.get_bool("OpenpilotEnabledToggle")
 
     controller_available = self.CI.CC is not None and openpilot_enabled_toggle and not self.CP.dashcamOnly

selfdrive/controls/controlsd.py

@@ -19,7 +19,6 @@ from openpilot.selfdrive.controls.lib.longcontrol import LongControl
 from openpilot.selfdrive.controls.lib.vehicle_model import VehicleModel
 from openpilot.selfdrive.locationd.helpers import PoseCalibrator, Pose
 
-from opendbc.sunnypilot import SunnypilotParamFlags
 
 State = log.SelfdriveState.OpenpilotState
 LaneChangeState = log.LaneChangeState
@@ -57,9 +56,6 @@ class Controls:
     elif self.CP.lateralTuning.which() == 'torque':
       self.LaC = LatControlTorque(self.CP, self.CI)
 
-    data_services = list(self.sm.data.keys()) + ['selfdriveStateSP']
-    self.sm = messaging.SubMaster(data_services, poll='selfdriveState')
-
   def update(self):
     self.sm.update(15)
     if self.sm.updated["liveCalibration"]:
@@ -92,16 +88,7 @@ class Controls:
 
     # Check which actuators can be enabled
     standstill = abs(CS.vEgo) <= max(self.CP.minSteerSpeed, MIN_LATERAL_CONTROL_SPEED) or CS.standstill
-
-    ss_sp = self.sm['selfdriveStateSP']
-    CC.madsEnabled = ss_sp.mads.enabled
-    if ss_sp.mads.available:
-      CC.sunnypilotParams |= SunnypilotParamFlags.ENABLE_MADS.value
-      _lat_active = ss_sp.mads.active
-    else:
-      _lat_active = self.sm['selfdriveState'].active
-
-    CC.latActive = _lat_active and not CS.steerFaultTemporary and not CS.steerFaultPermanent and not standstill
+    CC.latActive = self.sm['selfdriveState'].active and not CS.steerFaultTemporary and not CS.steerFaultPermanent and not standstill
     CC.longActive = CC.enabled and not any(e.overrideLongitudinal for e in self.sm['onroadEvents']) and self.CP.openpilotLongitudinalControl
 
     actuators = CC.actuators

selfdrive/modeld/SConscript

@@ -13,6 +13,20 @@ common_src = [
   "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":
@@ -31,24 +45,34 @@ 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)
-tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=env.Dir("#").abspath) if 'pycache' not in x]
+
+tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=env.Dir("#").abspath)]
 
 # Get model metadata
 fn = File("models/supercombo").abspath
 cmd = f'python3 {Dir("#selfdrive/modeld").abspath}/get_model_metadata.py {fn}.onnx'
 lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files, cmd)
 
-# Compile tinygrad model
-pythonpath_string = 'PYTHONPATH="${PYTHONPATH}:' + env.Dir("#tinygrad_repo").abspath + '"'
-if arch == 'larch64':
-  device_string = 'QCOM=1'
-else:
-  device_string = 'CLANG=1 IMAGE=0'
+# Build thneed model
+if arch == "larch64" or GetOption('pc_thneed'):
+  tinygrad_opts = []
+  if not GetOption('pc_thneed'):
+    # use FLOAT16 on device for speed + don't cache the CL kernels for space
+    tinygrad_opts += ["FLOAT16=1", "PYOPENCL_NO_CACHE=1"]
+  cmd = f"cd {Dir('#').abspath}/tinygrad_repo && " + ' '.join(tinygrad_opts) + f" python3 openpilot/compile2.py {fn}.onnx {fn}.thneed"
 
-for model_name in ['supercombo', 'dmonitoring_model']:
-  fn = File(f"models/{model_name}").abspath
-  cmd = f'{pythonpath_string} {device_string} python3 {Dir("#tinygrad_repo").abspath}/examples/openpilot/compile3.py {fn}.onnx {fn}_tinygrad.pkl'
-  lenv.Command(fn + "_tinygrad.pkl", [fn + ".onnx"] + tinygrad_files, cmd)
+  lenv.Command(fn + ".thneed", [fn + ".onnx"] + tinygrad_files, cmd)
 
+  fn_dm = File("models/dmonitoring_model").abspath
+  cmd = f"cd {Dir('#').abspath}/tinygrad_repo && " + ' '.join(tinygrad_opts) + f" python3 openpilot/compile2.py {fn_dm}.onnx {fn_dm}.thneed"
+  lenv.Command(fn_dm + ".thneed", [fn_dm + ".onnx"] + tinygrad_files, cmd)
+
+  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'])

selfdrive/modeld/dmonitoringmodeld

@@ -1,4 +1,10 @@
 #!/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 "$DIR/dmonitoringmodeld.py" "$@"

selfdrive/modeld/dmonitoringmodeld.py

@@ -1,17 +1,8 @@
 #!/usr/bin/env python3
 import os
-from openpilot.system.hardware import TICI
-if TICI:
-  from tinygrad.tensor import Tensor
-  from tinygrad.dtype import dtypes
-  from openpilot.selfdrive.modeld.runners.tinygrad_helpers import qcom_tensor_from_opencl_address
-  os.environ['QCOM'] = '1'
-else:
-  from openpilot.selfdrive.modeld.runners.ort_helpers import make_onnx_cpu_runner
 import gc
 import math
 import time
-import pickle
 import ctypes
 import numpy as np
 from pathlib import Path
@@ -22,20 +13,21 @@ from cereal.messaging import PubMaster, SubMaster
 from msgq.visionipc import VisionIpcClient, VisionStreamType, VisionBuf
 from openpilot.common.swaglog import cloudlog
 from openpilot.common.realtime import set_realtime_priority
-from openpilot.common.transformations.model import dmonitoringmodel_intrinsics, DM_INPUT_SIZE
+from openpilot.common.transformations.model import dmonitoringmodel_intrinsics
 from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
 from openpilot.selfdrive.modeld.models.commonmodel_pyx import CLContext, MonitoringModelFrame
+from openpilot.selfdrive.modeld.runners import ModelRunner, Runtime
 from openpilot.selfdrive.modeld.parse_model_outputs import sigmoid
 
-MODEL_WIDTH, MODEL_HEIGHT = DM_INPUT_SIZE
 CALIB_LEN = 3
 FEATURE_LEN = 512
 OUTPUT_SIZE = 84 + FEATURE_LEN
 
 PROCESS_NAME = "selfdrive.modeld.dmonitoringmodeld"
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
-MODEL_PATH = Path(__file__).parent / 'models/dmonitoring_model.onnx'
-MODEL_PKL_PATH = Path(__file__).parent / 'models/dmonitoring_model_tinygrad.pkl'
+MODEL_PATHS = {
+  ModelRunner.THNEED: Path(__file__).parent / 'models/dmonitoring_model.thneed',
+  ModelRunner.ONNX: Path(__file__).parent / 'models/dmonitoring_model.onnx'}
 
 class DriverStateResult(ctypes.Structure):
   _fields_ = [
@@ -66,42 +58,29 @@ class DMonitoringModelResult(ctypes.Structure):
 class ModelState:
   inputs: dict[str, np.ndarray]
   output: np.ndarray
+  model: ModelRunner
 
   def __init__(self, cl_ctx):
     assert ctypes.sizeof(DMonitoringModelResult) == OUTPUT_SIZE * ctypes.sizeof(ctypes.c_float)
 
     self.frame = MonitoringModelFrame(cl_ctx)
-    self.numpy_inputs = {
-      'calib': np.zeros((1, CALIB_LEN), dtype=np.float32),
-    }
+    self.output = np.zeros(OUTPUT_SIZE, dtype=np.float32)
+    self.inputs = {
+      'calib': np.zeros(CALIB_LEN, dtype=np.float32)}
 
-    if TICI:
-      self.tensor_inputs = {k: Tensor(v, device='NPY').realize() for k,v in self.numpy_inputs.items()}
-      with open(MODEL_PKL_PATH, "rb") as f:
-        self.model_run = pickle.load(f)
-    else:
-      self.onnx_cpu_runner = make_onnx_cpu_runner(MODEL_PATH)
+    self.model = ModelRunner(MODEL_PATHS, self.output, Runtime.GPU, False, cl_ctx)
+    self.model.addInput("input_img", None)
+    self.model.addInput("calib", self.inputs['calib'])
 
   def run(self, buf:VisionBuf, calib:np.ndarray, transform:np.ndarray) -> tuple[np.ndarray, float]:
-    self.numpy_inputs['calib'][0,:] = calib
+    self.inputs['calib'][:] = calib
+
+    self.model.setInputBuffer("input_img", self.frame.prepare(buf, transform.flatten(), None).view(np.float32))
 
     t1 = time.perf_counter()
-
-    input_img_cl = self.frame.prepare(buf, transform.flatten())
-    if TICI:
-      # The imgs tensors are backed by opencl memory, only need init once
-      if 'input_img' not in self.tensor_inputs:
-        self.tensor_inputs['input_img'] = qcom_tensor_from_opencl_address(input_img_cl.mem_address, (1, MODEL_WIDTH*MODEL_HEIGHT), dtype=dtypes.uint8)
-    else:
-      self.numpy_inputs['input_img'] = self.frame.buffer_from_cl(input_img_cl).reshape((1, MODEL_WIDTH*MODEL_HEIGHT))
-
-    if TICI:
-      output = self.model_run(**self.tensor_inputs).numpy().flatten()
-    else:
-      output = self.onnx_cpu_runner.run(None, self.numpy_inputs)[0].flatten()
-
+    self.model.execute()
     t2 = time.perf_counter()
-    return output, t2 - t1
+    return self.output, t2 - t1
 
 
 def fill_driver_state(msg, ds_result: DriverStateResult):

selfdrive/modeld/modeld

@@ -1,4 +1,10 @@
 #!/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 "$DIR/modeld.py" "$@"

selfdrive/modeld/modeld.py

@@ -1,31 +1,39 @@
 #!/usr/bin/env python3
-from openpilot.system.hardware import TICI
-
-from openpilot.selfdrive.modeld.runners.model_runner import ONNXRunner, TinygradRunner
-
-#
+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.realtime import DT_MDL
+from openpilot.common.numpy_fast import interp
 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.selfdrive.modeld.runners import ModelRunner, Runtime
 from openpilot.selfdrive.modeld.parse_model_outputs import Parser
 from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState
 from openpilot.selfdrive.modeld.constants import ModelConstants
 from openpilot.selfdrive.modeld.models.commonmodel_pyx import DrivingModelFrame, CLContext
 
 PROCESS_NAME = "selfdrive.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:
@@ -38,35 +46,54 @@ class FrameMeta:
       self.frame_id, self.timestamp_sof, self.timestamp_eof = vipc.frame_id, vipc.timestamp_sof, vipc.timestamp_eof
 
 class ModelState:
-  frames: dict[str, DrivingModelFrame]
+  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.frames = {'input_imgs': DrivingModelFrame(context), 'big_input_imgs': DrivingModelFrame(context)}
+    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)
-    # Initialize model runner
-    self.model_runner = TinygradRunner(self.frames) if TICI else ONNXRunner(self.frames)
 
     # img buffers are managed in openCL transform code
-    self.numpy_inputs = {}
+    self.inputs = {}
 
-    for key, shape in self.model_runner.input_shapes.items():
-      if key not in self.frames: # Managed by opencl
-        self.numpy_inputs[key] = np.zeros(shape, dtype=np.float32)
+    with open(METADATA_PATH, 'rb') as f:
+      model_metadata = pickle.load(f)
 
+    for key, shape in model_metadata['input_shapes'].items():
+      if key not in ["input_imgs", "big_input_imgs"]:
+        self.inputs[key] = np.zeros(shape, dtype=np.float32).flatten()
+
+    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()
 
-    net_output_size = self.model_runner.model_metadata['output_shapes']['outputs'][1]
-    self.output = np.zeros(net_output_size, dtype=np.float32)
+    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)
 
-    num_elements = self.numpy_inputs['features_buffer'].shape[1]
+    num_elements = model_metadata['input_shapes']['features_buffer'][1]
     step_size = int(-100 / num_elements)
     self.full_features_20Hz_idxs = np.arange(step_size, step_size * (num_elements + 1), step_size)[::-1]
-    self.desire_reshape_dims = (self.numpy_inputs['desire'].shape[0], self.numpy_inputs['desire'].shape[1], -1, self.numpy_inputs['desire'].shape[2])
+
+    desired_shape = int(self.inputs['desire'].shape[0] / self.desire_20Hz.shape[1])
+    middle_dim = int(self.desire_20Hz.shape[0] / desired_shape)
+    self.desire_reshape_dims = (desired_shape, middle_dim, -1)
+
+  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:
@@ -77,42 +104,41 @@ class ModelState:
 
     self.desire_20Hz[:-1] = self.desire_20Hz[1:]
     self.desire_20Hz[-1] = new_desire
-    self.numpy_inputs['desire'][:] = self.desire_20Hz.reshape(self.desire_reshape_dims).max(axis=2)
+    self.inputs['desire'][:] = self.desire_20Hz.reshape(self.desire_reshape_dims).max(axis=1).flatten()
 
-    for key in self.numpy_inputs:
-      if key in inputs and key not in ['desire']:
-        self.numpy_inputs[key][:] = inputs[key]
+    self.inputs['traffic_convention'][:] = inputs['traffic_convention']
 
-    imgs_cl = {'input_imgs': self.frames['input_imgs'].prepare(buf, transform.flatten()),
-               'big_input_imgs': self.frames['big_input_imgs'].prepare(wbuf, transform_wide.flatten())}
-
-    # Prepare inputs using the model runner
-    self.model_runner.prepare_inputs(imgs_cl, self.numpy_inputs)
+    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
 
-    # Run model inference
-    self.output = self.model_runner.run_model()
-    outputs = self.parser.parse_outputs(self.model_runner.slice_outputs(self.output), self.numpy_inputs.keys())
+    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, :]
 
-    self.numpy_inputs['features_buffer'][:] = self.full_features_20Hz[self.full_features_20Hz_idxs]
+    # idxs = np.arange(-4,-100,-4)[::-1]
+    self.inputs['features_buffer'][:] = self.full_features_20Hz[self.full_features_20Hz_idxs].flatten()
+
+    if "lat_planner_solution" in outputs:
+      if "lat_planner_state" in self.inputs.keys():
+        self.inputs['lat_planner_state'][2] = interp(DT_MDL, ModelConstants.T_IDXS, outputs['lat_planner_solution'][0, :, 2])
+        self.inputs['lat_planner_state'][3] = interp(DT_MDL, ModelConstants.T_IDXS, outputs['lat_planner_solution'][0, :, 3])
 
     if "desired_curvature" in outputs:
       input_name_prev = None
-
-      if "prev_desired_curvs" in self.numpy_inputs.keys():
+      if "prev_desired_curvs" in self.inputs.keys():
         input_name_prev = 'prev_desired_curvs'
-      elif "prev_desired_curv" in self.numpy_inputs.keys():
+      elif "prev_desired_curv" in self.inputs.keys():
         input_name_prev = 'prev_desired_curv'
 
       if input_name_prev is not None:
         len = outputs['desired_curvature'][0].size
-        self.numpy_inputs[input_name_prev][0, :-len, 0] = self.numpy_inputs[input_name_prev][0, len:, 0]
-        self.numpy_inputs[input_name_prev][0, -len:, 0] = outputs['desired_curvature'][0]
+        self.inputs[input_name_prev][:-len] = self.inputs[input_name_prev][len:]
+        self.inputs[input_name_prev][-len:] = outputs['desired_curvature'][0, :len]
     return outputs
 
 
@@ -173,6 +199,7 @@ def main(demo=False):
   meta_main = FrameMeta()
   meta_extra = FrameMeta()
 
+
   if demo:
     CP = get_demo_car_params()
   else:
@@ -254,8 +281,17 @@ def main(demo=False):
       'traffic_convention': traffic_convention,
       }
 
-    if "lateral_control_params" in model.numpy_inputs.keys():
-      inputs['lateral_control_params'] = np.array([sm["carState"].vEgo, steer_delay], dtype=np.float32)
+    if "lateral_control_params" in model.inputs.keys():
+      inputs['lateral_control_params'] = np.array([v_ego, steer_delay], dtype=np.float32)
+
+    if "driving_style" in model.inputs.keys():
+      inputs['driving_style'] = np.array([1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0], dtype=np.float32)
+
+    if "nav_features" in model.inputs.keys():
+      inputs['nav_features'] = np.zeros(ModelConstants.NAV_FEATURE_LEN, dtype=np.float32)  # Get size from shape
+
+    if "nav_instructions" in model.inputs.keys():
+      inputs['nav_instructions'] = np.zeros(ModelConstants.NAV_INSTRUCTION_LEN, dtype=np.float32)  # Get size from shape
 
     mt1 = time.perf_counter()
     model_output = model.run(buf_main, buf_extra, model_transform_main, model_transform_extra, inputs, prepare_only)
@@ -284,6 +320,7 @@ def main(demo=False):
       pm.send('modelV2', modelv2_send)
       pm.send('drivingModelData', drivingdata_send)
       pm.send('cameraOdometry', posenet_send)
+
     last_vipc_frame_id = meta_main.frame_id
 
 

selfdrive/modeld/models/commonmodel.cc

@@ -6,8 +6,8 @@
 #include "common/clutil.h"
 
 DrivingModelFrame::DrivingModelFrame(cl_device_id device_id, cl_context context) : ModelFrame(device_id, context) {
-  input_frames = std::make_unique<uint8_t[]>(buf_size);
-  input_frames_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, buf_size, NULL, &err));
+  input_frames = std::make_unique<float[]>(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;
@@ -17,7 +17,7 @@ DrivingModelFrame::DrivingModelFrame(cl_device_id device_id, cl_context context)
   init_transform(device_id, context, MODEL_WIDTH, MODEL_HEIGHT);
 }
 
-cl_mem* DrivingModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) {
+float* 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++) {
@@ -25,12 +25,19 @@ cl_mem* DrivingModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_hei
   }
   loadyuv_queue(&loadyuv, q, y_cl, u_cl, v_cl, last_img_cl);
 
-  copy_queue(&loadyuv, q, img_buffer_20hz_cl, input_frames_cl, 0, 0, frame_size_bytes);
-  copy_queue(&loadyuv, q, last_img_cl, input_frames_cl, 0, frame_size_bytes, frame_size_bytes);
+  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 &input_frames_cl;
+    // 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() {
@@ -43,16 +50,17 @@ DrivingModelFrame::~DrivingModelFrame() {
 
 
 MonitoringModelFrame::MonitoringModelFrame(cl_device_id device_id, cl_context context) : ModelFrame(device_id, context) {
-  input_frames = std::make_unique<uint8_t[]>(buf_size);
-  input_frame_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, buf_size, NULL, &err));
+  input_frames = std::make_unique<float[]>(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);
 }
-
-cl_mem* MonitoringModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) {
+float* 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(float), input_frames.get(), 0, nullptr, nullptr));
   clFinish(q);
-  return &y_cl;
+  //return &y_cl;
+  return input_frames.get();
 }
 
 MonitoringModelFrame::~MonitoringModelFrame() {

selfdrive/modeld/models/commonmodel.h

@@ -23,12 +23,14 @@ public:
     q = CL_CHECK_ERR(clCreateCommandQueue(context, device_id, 0, &err));
   }
   virtual ~ModelFrame() {}
-  virtual cl_mem* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) { return NULL; }
+  virtual float* 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;
@@ -39,7 +41,7 @@ protected:
   cl_mem y_cl, u_cl, v_cl;
   Transform transform;
   cl_command_queue q;
-  std::unique_ptr<uint8_t[]> input_frames;
+  std::unique_ptr<float[]> 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));
@@ -66,17 +68,17 @@ class DrivingModelFrame : public ModelFrame {
 public:
   DrivingModelFrame(cl_device_id device_id, cl_context context);
   ~DrivingModelFrame();
-  cl_mem* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection);
+  float* 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);
+  const size_t frame_size_bytes = MODEL_FRAME_SIZE * sizeof(float);
 
 private:
   LoadYUVState loadyuv;
-  cl_mem img_buffer_20hz_cl, last_img_cl, input_frames_cl;
+  cl_mem img_buffer_20hz_cl, last_img_cl;//, input_frames_cl;
   cl_buffer_region region;
 };
 
@@ -84,7 +86,7 @@ class MonitoringModelFrame : public ModelFrame {
 public:
   MonitoringModelFrame(cl_device_id device_id, cl_context context);
   ~MonitoringModelFrame();
-  cl_mem* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection);
+  float* 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;
@@ -92,5 +94,5 @@ public:
   const int buf_size = MODEL_FRAME_SIZE;
 
 private:
-  cl_mem input_frame_cl;
+  // cl_mem input_frame_cl;
 };

selfdrive/modeld/models/commonmodel.pxd

@@ -14,8 +14,8 @@ cdef extern from "common/clutil.h":
 cdef extern from "selfdrive/modeld/models/commonmodel.h":
   cppclass ModelFrame:
     int buf_size
-    unsigned char * buffer_from_cl(cl_mem*, int);
-    cl_mem * prepare(cl_mem, int, int, int, int, mat3)
+    # unsigned char * buffer_from_cl(cl_mem*, int);
+    float * prepare(cl_mem, int, int, int, int, mat3, cl_mem*)
 
   cppclass DrivingModelFrame:
     int buf_size

selfdrive/modeld/models/commonmodel_pyx.pyx

@@ -39,17 +39,24 @@ cdef class ModelFrame:
   def __dealloc__(self):
     del self.frame
 
-  def prepare(self, VisionBuf buf, float[:] projection):
+  def prepare(self, VisionBuf buf, float[:] projection, CLMem output):
     cdef mat3 cprojection
     memcpy(cprojection.v, &projection[0], 9*sizeof(float))
-    cdef cl_mem * data
-    data = self.frame.prepare(buf.buf.buf_cl, buf.width, buf.height, buf.stride, buf.uv_offset, cprojection)
-    return CLMem.create(data)
+    cdef float * 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
 
-  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(<cnp.uint8_t[:self.buf_size]> data2)
+    return np.asarray(<cnp.float32_t[:self.buf_size]> 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(<cnp.uint8_t[:self.buf_size]> data2)
 
 
 cdef class DrivingModelFrame(ModelFrame):
@@ -67,4 +74,3 @@ cdef class MonitoringModelFrame(ModelFrame):
     self._frame = new cppMonitoringModelFrame(context.device_id, context.context)
     self.frame = <cppModelFrame*>(self._frame)
     self.buf_size = self._frame.buf_size
-

selfdrive/modeld/parse_model_outputs.py

@@ -84,8 +84,7 @@ class Parser:
     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], input_keys: [str]) -> dict[str, np.ndarray]:
-    """ Parse the model outputs into a dictionary of numpy arrays. The input_keys are used to determine how the output should be parsed. """
+  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))
@@ -97,8 +96,6 @@ class Parser:
                    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))
-    if 'desired_curvature' in outs and "prev_desired_curv" in input_keys:
-      self.parse_mdn('desired_curvature', outs, in_N=0, out_N=0, out_shape=(ModelConstants.DESIRED_CURV_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,))

selfdrive/modeld/runners/__init__.py

@@ -0,0 +1,27 @@
+import os
+from openpilot.system.hardware import TICI
+from openpilot.selfdrive.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.selfdrive.modeld.runners.thneedmodel_pyx import ThneedModel as Runner
+      runner_type = ModelRunner.THNEED
+    elif ModelRunner.SNPE in paths and USE_SNPE:
+      from openpilot.selfdrive.modeld.runners.snpemodel_pyx import SNPEModel as Runner
+      runner_type = ModelRunner.SNPE
+    elif ModelRunner.ONNX in paths:
+      from openpilot.selfdrive.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)

selfdrive/modeld/runners/model_runner.py

@@ -1,114 +0,0 @@
-import os
-from openpilot.system.hardware import TICI
-
-#
-from tinygrad.tensor import Tensor, dtypes
-from openpilot.selfdrive.modeld.runners.tinygrad_helpers import qcom_tensor_from_opencl_address
-from openpilot.selfdrive.modeld.runners.ort_helpers import make_onnx_cpu_runner, ORT_TYPES_TO_NP_TYPES
-import pickle
-import numpy as np
-from pathlib import Path
-from abc import ABC, abstractmethod
-from openpilot.selfdrive.modeld.models.commonmodel_pyx import DrivingModelFrame, CLMem
-
-if TICI:
-  os.environ['QCOM'] = '1'
-
-SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
-MODEL_PATH = Path(__file__).parent / '../models/supercombo.onnx'
-MODEL_PKL_PATH = Path(__file__).parent / '../models/supercombo_tinygrad.pkl'
-METADATA_PATH = Path(__file__).parent / '../models/supercombo_metadata.pkl'
-
-
-class ModelRunner(ABC):
-  """Abstract base class for model runners that defines the interface for running ML models."""
-
-  def __init__(self):
-    """Initialize the model runner with paths to model and metadata files."""
-    with open(METADATA_PATH, 'rb') as f:
-      self.model_metadata = pickle.load(f)
-    self.input_shapes = self.model_metadata['input_shapes']
-    self.output_slices = self.model_metadata['output_slices']
-    self.inputs: dict = {}
-
-  @abstractmethod
-  def prepare_inputs(self, imgs_cl: dict[str, CLMem], numpy_inputs: dict[str, np.ndarray])-> dict:
-    """Prepare inputs for model inference."""
-
-  @abstractmethod
-  def run_model(self):
-    """Run model inference with prepared inputs."""
-
-  def slice_outputs(self, model_outputs: np.ndarray) -> dict:
-    """Slice model outputs according to metadata configuration."""
-    parsed_outputs = {k: model_outputs[np.newaxis, v] for k, v in self.output_slices.items()}
-    if SEND_RAW_PRED:
-      parsed_outputs['raw_pred'] = model_outputs.copy()
-    return parsed_outputs
-
-
-class TinygradRunner(ModelRunner):
-  """Tinygrad implementation of model runner for TICI hardware."""
-
-  def __init__(self, frames: dict[str, DrivingModelFrame] | None = None):
-    super().__init__()
-    # Load Tinygrad model
-    with open(MODEL_PKL_PATH, "rb") as f:
-      self.model_run = pickle.load(f)
-
-    self.input_to_dtype = {}
-    self.input_to_device = {}
-
-    for idx, name in enumerate(self.model_run.captured.expected_names):
-      self.input_to_dtype[name] = self.model_run.captured.expected_st_vars_dtype_device[idx][2]  # 2 is the dtype
-      self.input_to_device[name] = self.model_run.captured.expected_st_vars_dtype_device[idx][3]  # 3 is the device
-
-    assert TICI or frames is not None, "TinygradRunner requires frames for non-TICI hardware"
-    self.frames = frames
-    self.is_memory_model = None  # Use None to indicate that it hasn't been determined yet
-
-  def prepare_inputs(self, imgs_cl: dict[str, CLMem], numpy_inputs: dict[str, np.ndarray]) -> dict:
-    if self.is_memory_model is None:
-      self.is_memory_model = any(self.input_to_dtype[key] == dtypes.uint8 for key in imgs_cl)
-      print(f"Memory model: {self.is_memory_model}")
-
-    # Initialize image tensors if not already done
-    for key in imgs_cl:
-      if TICI and self.is_memory_model and key not in self.inputs:
-        self.inputs[key] = qcom_tensor_from_opencl_address(imgs_cl[key].mem_address, self.input_shapes[key], dtype=dtypes.uint8)
-      elif not TICI or not self.is_memory_model:
-        shape = self.frames[key].buffer_from_cl(imgs_cl[key]).reshape(self.input_shapes[key])
-        self.inputs[key] = Tensor(shape, device=self.input_to_device[key], dtype=self.input_to_dtype[key]).realize()
-
-    # Update numpy inputs
-    for key, value in numpy_inputs.items():
-      if key not in imgs_cl:
-        self.inputs[key] = Tensor(value, device=self.input_to_device[key], dtype=self.input_to_dtype[key]).realize()
-
-    return self.inputs
-
-  def run_model(self):
-    return self.model_run(**self.inputs).numpy().flatten()
-
-
-class ONNXRunner(ModelRunner):
-  """ONNX implementation of model runner for non-TICI hardware."""
-
-  def __init__(self, frames: dict[str, DrivingModelFrame]):
-    super().__init__()
-    self.runner = make_onnx_cpu_runner(MODEL_PATH)
-    self.frames = frames
-
-    self.input_to_nptype = {
-      model_input.name: ORT_TYPES_TO_NP_TYPES[model_input.type]
-      for model_input in self.runner.get_inputs()
-    }
-
-  def prepare_inputs(self, imgs_cl: dict[str, CLMem], numpy_inputs: dict[str, np.ndarray]) -> dict:
-    self.inputs = numpy_inputs.copy()
-    for key in imgs_cl:
-      self.inputs[key] = self.frames[key].buffer_from_cl(imgs_cl[key]).astype(self.input_to_nptype[key]).reshape(self.input_shapes[key])
-    return self.inputs
-
-  def run_model(self):
-    return self.runner.run(None, self.inputs)[0].flatten()

selfdrive/modeld/runners/onnxmodel.py

@@ -4,8 +4,8 @@ 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
+from openpilot.selfdrive.modeld.runners.runmodel_pyx import RunModel
+from openpilot.selfdrive.modeld.runners.ort_helpers import convert_fp16_to_fp32, ORT_TYPES_TO_NP_TYPES
 
 
 def create_ort_session(path, fp16_to_fp32):

selfdrive/modeld/runners/run.h

@@ -0,0 +1,4 @@
+#pragma once
+
+#include "selfdrive/modeld/runners/runmodel.h"
+#include "selfdrive/modeld/runners/snpemodel.h"

selfdrive/modeld/runners/runmodel.pxd

@@ -2,7 +2,7 @@
 
 from libcpp.string cimport string
 
-cdef extern from "sunnypilot/modeld/runners/runmodel.h":
+cdef extern from "selfdrive/modeld/runners/runmodel.h":
   cdef int USE_CPU_RUNTIME
   cdef int USE_GPU_RUNTIME
   cdef int USE_DSP_RUNTIME

selfdrive/modeld/runners/runmodel_pyx.pyx

@@ -4,7 +4,7 @@
 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
+from selfdrive.modeld.models.commonmodel_pyx cimport CLMem
 
 class Runtime:
   CPU = USE_CPU_RUNTIME

selfdrive/modeld/runners/snpemodel.cc

@@ -1,6 +1,6 @@
 #pragma clang diagnostic ignored "-Wexceptions"
 
-#include "sunnypilot/modeld/runners/snpemodel.h"
+#include "selfdrive/modeld/runners/snpemodel.h"
 
 #include <cstring>
 #include <memory>

selfdrive/modeld/runners/snpemodel.h

@@ -15,7 +15,7 @@
 #include <SNPE/SNPEBuilder.hpp>
 #include <SNPE/SNPEFactory.hpp>
 
-#include "sunnypilot/modeld/runners/runmodel.h"
+#include "selfdrive/modeld/runners/runmodel.h"
 
 struct SNPEModelInput : public ModelInput {
   std::unique_ptr<zdl::DlSystem::IUserBuffer> snpe_buffer;

selfdrive/modeld/runners/snpemodel.pxd

@@ -4,6 +4,6 @@ from libcpp.string cimport string
 
 from msgq.visionipc.visionipc cimport cl_context
 
-cdef extern from "sunnypilot/modeld/runners/snpemodel.h":
+cdef extern from "selfdrive/modeld/runners/snpemodel.h":
   cdef cppclass SNPEModel:
     SNPEModel(string, float*, size_t, int, bool, cl_context)

selfdrive/modeld/runners/snpemodel_pyx.pyx

@@ -6,9 +6,9 @@ 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
+from selfdrive.modeld.models.commonmodel_pyx cimport CLContext
+from selfdrive.modeld.runners.runmodel_pyx cimport RunModel
+from selfdrive.modeld.runners.runmodel cimport RunModel as cppRunModel
 
 os.environ['ADSP_LIBRARY_PATH'] = "/data/pythonpath/third_party/snpe/dsp/"
 

selfdrive/modeld/runners/thneedmodel.cc

@@ -1,4 +1,4 @@
-#include "sunnypilot/modeld/runners/thneedmodel.h"
+#include "selfdrive/modeld/runners/thneedmodel.h"
 
 #include <string>
 

selfdrive/modeld/runners/thneedmodel.h

@@ -2,8 +2,8 @@
 
 #include <string>
 
-#include "sunnypilot/modeld/runners/runmodel.h"
-#include "sunnypilot/modeld/thneed/thneed.h"
+#include "selfdrive/modeld/runners/runmodel.h"
+#include "selfdrive/modeld/thneed/thneed.h"
 
 class ThneedModel : public RunModel {
 public:

selfdrive/modeld/runners/thneedmodel.pxd

@@ -4,6 +4,6 @@ from libcpp.string cimport string
 
 from msgq.visionipc.visionipc cimport cl_context
 
-cdef extern from "sunnypilot/modeld/runners/thneedmodel.h":
+cdef extern from "selfdrive/modeld/runners/thneedmodel.h":
   cdef cppclass ThneedModel:
     ThneedModel(string, float*, size_t, int, bool, cl_context)

selfdrive/modeld/runners/thneedmodel_pyx.pyx

@@ -5,9 +5,9 @@ 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
+from selfdrive.modeld.models.commonmodel_pyx cimport CLContext
+from selfdrive.modeld.runners.runmodel_pyx cimport RunModel
+from selfdrive.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):

selfdrive/modeld/runners/tinygrad_helpers.py

@@ -1,8 +0,0 @@
-
-from tinygrad.tensor import Tensor
-from tinygrad.helpers import to_mv
-
-def qcom_tensor_from_opencl_address(opencl_address, shape, dtype):
-  cl_buf_desc_ptr = to_mv(opencl_address, 8).cast('Q')[0]
-  rawbuf_ptr = to_mv(cl_buf_desc_ptr, 0x100).cast('Q')[20] # offset 0xA0 is a raw gpu pointer.
-  return Tensor.from_blob(rawbuf_ptr, shape, dtype=dtype, device='QCOM')

selfdrive/modeld/thneed/serialize.cc

@@ -5,7 +5,7 @@
 #include "common/util.h"
 #include "common/clutil.h"
 #include "common/swaglog.h"
-#include "sunnypilot/modeld/thneed/thneed.h"
+#include "selfdrive/modeld/thneed/thneed.h"
 using namespace json11;
 
 extern map<cl_program, string> g_program_source;

selfdrive/modeld/thneed/thneed_common.cc

@@ -1,4 +1,4 @@
-#include "sunnypilot/modeld/thneed/thneed.h"
+#include "selfdrive/modeld/thneed/thneed.h"
 
 #include <cassert>
 #include <cstring>

selfdrive/modeld/thneed/thneed_pc.cc

@@ -1,4 +1,4 @@
-#include "sunnypilot/modeld/thneed/thneed.h"
+#include "selfdrive/modeld/thneed/thneed.h"
 
 #include <cassert>
 

selfdrive/modeld/thneed/thneed_qcom2.cc

@@ -1,4 +1,4 @@
-#include "sunnypilot/modeld/thneed/thneed.h"
+#include "selfdrive/modeld/thneed/thneed.h"
 
 #include <dlfcn.h>
 #include <sys/mman.h>

selfdrive/modeld/transforms/loadyuv.cl

@@ -1,7 +1,7 @@
 #define UV_SIZE ((TRANSFORMED_WIDTH/2)*(TRANSFORMED_HEIGHT/2))
 
 __kernel void loadys(__global uchar8 const * const Y,
-                     __global uchar * out,
+                     __global float * out,
                      int out_offset)
 {
     const int gid = get_global_id(0);
@@ -10,12 +10,13 @@ __kernel void loadys(__global uchar8 const * const Y,
     const int ox = ois % TRANSFORMED_WIDTH;
 
     const uchar8 ys = Y[gid];
+    const float8 ysf = convert_float8(ys);
 
     // 02
     // 13
 
-    __global uchar* outy0;
-    __global uchar* outy1;
+    __global float* outy0;
+    __global float* outy1;
     if ((oy & 1) == 0) {
       outy0 = out + out_offset; //y0
       outy1 = out + out_offset + UV_SIZE*2; //y2
@@ -24,24 +25,23 @@ __kernel void loadys(__global uchar8 const * const Y,
       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);
+    vstore4(ysf.s0246, 0, outy0 + (oy/2) * (TRANSFORMED_WIDTH/2) + ox/2);
+    vstore4(ysf.s1357, 0, outy1 + (oy/2) * (TRANSFORMED_WIDTH/2) + ox/2);
 }
 
 __kernel void loaduv(__global uchar8 const * const in,
-                     __global uchar8 * out,
+                     __global float8 * out,
                      int out_offset)
 {
   const int gid = get_global_id(0);
   const uchar8 inv = in[gid];
-  out[gid + out_offset / 8] = inv;
+  const float8 outv  = convert_float8(inv);
+  out[gid + out_offset / 8] = outv;
 }
 
-__kernel void copy(__global uchar8 * in,
-                   __global uchar8 * out,
-                   int in_offset,
-                   int out_offset)
+__kernel void copy(__global float8 * inout,
+                   int in_offset)
 {
   const int gid = get_global_id(0);
-  out[gid + out_offset / 8] = in[gid + in_offset / 8];
-}
+  inout[gid] = inout[gid + in_offset / 8];
+}

selfdrive/pandad/panda.cc

@@ -137,8 +137,8 @@ void Panda::enable_deepsleep() {
   handle->control_write(0xfb, 0, 0);
 }
 
-void Panda::send_heartbeat(bool engaged, bool engaged_mads) {
-  handle->control_write(0xf3, engaged, engaged_mads);
+void Panda::send_heartbeat(bool engaged) {
+  handle->control_write(0xf3, engaged, 0);
 }
 
 void Panda::set_can_speed_kbps(uint16_t bus, uint16_t speed) {

selfdrive/pandad/panda.h

@@ -75,7 +75,7 @@ public:
   std::optional<std::string> get_serial();
   void set_power_saving(bool power_saving);
   void enable_deepsleep();
-  void send_heartbeat(bool engaged, bool engaged_mads);
+  void send_heartbeat(bool engaged);
   void set_can_speed_kbps(uint16_t bus, uint16_t speed);
   void set_can_fd_auto(uint16_t bus, bool enabled);
   void set_data_speed_kbps(uint16_t bus, uint16_t speed);

selfdrive/pandad/pandad.cc

@@ -41,8 +41,6 @@
 #define CUTOFF_IL 400
 #define SATURATE_IL 1000
 
-#define ALT_EXP_DISENGAGE_LATERAL_ON_BRAKE 2048
-
 ExitHandler do_exit;
 
 bool check_all_connected(const std::vector<Panda *> &pandas) {
@@ -55,18 +53,6 @@ bool check_all_connected(const std::vector<Panda *> &pandas) {
   return true;
 }
 
-bool process_mads_heartbeat(SubMaster *sm) {
-  const int &alt_exp = (*sm)["carParams"].getCarParams().getAlternativeExperience();
-  const bool disengage_lateral_on_brake = (alt_exp & ALT_EXP_DISENGAGE_LATERAL_ON_BRAKE) != 0;
-
-  const auto &mads = (*sm)["selfdriveStateSP"].getSelfdriveStateSP().getMads();
-  const bool heartbeat_type = disengage_lateral_on_brake ? mads.getActive() : mads.getEnabled();
-
-  const bool engaged = sm->allAliveAndValid({"selfdriveStateSP"}) && heartbeat_type;
-
-  return engaged;
-}
-
 Panda *connect(std::string serial="", uint32_t index=0) {
   std::unique_ptr<Panda> panda;
   try {
@@ -158,7 +144,6 @@ void fill_panda_state(cereal::PandaState::Builder &ps, cereal::PandaState::Panda
   ps.setIgnitionLine(health.ignition_line_pkt);
   ps.setIgnitionCan(health.ignition_can_pkt);
   ps.setControlsAllowed(health.controls_allowed_pkt);
-  ps.setControlsAllowedLat(health.controls_allowed_lat_pkt);
   ps.setTxBufferOverflow(health.tx_buffer_overflow_pkt);
   ps.setRxBufferOverflow(health.rx_buffer_overflow_pkt);
   ps.setPandaType(hw_type);
@@ -342,7 +327,7 @@ void send_peripheral_state(Panda *panda, PubMaster *pm) {
 }
 
 void process_panda_state(std::vector<Panda *> &pandas, PubMaster *pm, bool spoofing_started) {
-  static SubMaster sm({"selfdriveState", "selfdriveStateSP", "carParams"});
+  static SubMaster sm({"selfdriveState"});
 
   std::vector<std::string> connected_serials;
   for (Panda *p : pandas) {
@@ -381,9 +366,8 @@ void process_panda_state(std::vector<Panda *> &pandas, PubMaster *pm, bool spoof
 
     sm.update(0);
     const bool engaged = sm.allAliveAndValid({"selfdriveState"}) && sm["selfdriveState"].getSelfdriveState().getEnabled();
-    const bool engaged_mads = process_mads_heartbeat(&sm);
     for (const auto &panda : pandas) {
-      panda->send_heartbeat(engaged, engaged_mads);
+      panda->send_heartbeat(engaged);
     }
   }
 }

selfdrive/selfdrived/events.py

@@ -105,24 +105,6 @@ class Events:
       ret.append(event)
     return ret
 
-  def has(self, event_name: int) -> bool:
-    return event_name in self.events
-
-  def contains_in_list(self, events_list: list[int]) -> bool:
-    return any(event_name in self.events for event_name in events_list)
-
-  def remove(self, event_name: int, static: bool = False) -> None:
-    if static and event_name in self.static_events:
-      self.static_events.remove(event_name)
-
-    if event_name in self.events:
-      self.event_counters[event_name] = self.event_counters[event_name] + 1
-      self.events.remove(event_name)
-
-  def replace(self, prev_event_name: int, cur_event_name: int, static: bool = False) -> None:
-    self.remove(prev_event_name, static)
-    self.add(cur_event_name, static)
-
 
 class Alert:
   def __init__(self,
@@ -969,99 +951,6 @@ EVENTS: dict[int, dict[str, Alert | AlertCallbackType]] = {
     ET.WARNING: personality_changed_alert,
   },
 
-  # sunnypilot
-  EventName.lkasEnable: {
-    ET.ENABLE: EngagementAlert(AudibleAlert.engage),
-  },
-
-  EventName.lkasDisable: {
-    ET.USER_DISABLE: EngagementAlert(AudibleAlert.disengage),
-  },
-
-  EventName.manualSteeringRequired: {
-    ET.USER_DISABLE: Alert(
-      "Automatic Lane Centering is OFF",
-      "Manual Steering Required",
-      AlertStatus.normal, AlertSize.mid,
-      Priority.LOW, VisualAlert.none, AudibleAlert.disengage, 1.),
-  },
-
-  EventName.manualLongitudinalRequired: {
-    ET.WARNING: Alert(
-      "Smart/Adaptive Cruise Control: OFF",
-      "Manual Speed Control Required",
-      AlertStatus.normal, AlertSize.mid,
-      Priority.LOW, VisualAlert.none, AudibleAlert.none, 1.),
-  },
-
-  EventName.silentLkasEnable: {
-    ET.ENABLE: EngagementAlert(AudibleAlert.none),
-  },
-
-  EventName.silentLkasDisable: {
-    ET.USER_DISABLE: EngagementAlert(AudibleAlert.none),
-  },
-
-  EventName.silentBrakeHold: {
-    ET.USER_DISABLE: EngagementAlert(AudibleAlert.none),
-    ET.NO_ENTRY: NoEntryAlert("Brake Hold Active"),
-  },
-
-  EventName.silentWrongGear: {
-    ET.WARNING: Alert(
-      "",
-      "",
-      AlertStatus.normal, AlertSize.none,
-      Priority.LOWEST, VisualAlert.none, AudibleAlert.none, 0.),
-    ET.NO_ENTRY: Alert(
-      "Gear not D",
-      "openpilot Unavailable",
-      AlertStatus.normal, AlertSize.mid,
-      Priority.LOW, VisualAlert.none, AudibleAlert.none, 0.),
-  },
-
-  EventName.silentReverseGear: {
-    ET.PERMANENT: Alert(
-      "Reverse\nGear",
-      "",
-      AlertStatus.normal, AlertSize.full,
-      Priority.LOWEST, VisualAlert.none, AudibleAlert.none, .2, creation_delay=0.5),
-    ET.NO_ENTRY: NoEntryAlert("Reverse Gear"),
-  },
-
-  EventName.silentDoorOpen: {
-    ET.WARNING: Alert(
-      "",
-      "",
-      AlertStatus.normal, AlertSize.none,
-      Priority.LOWEST, VisualAlert.none, AudibleAlert.none, 0.),
-    ET.NO_ENTRY: NoEntryAlert("Door Open"),
-  },
-
-  EventName.silentSeatbeltNotLatched: {
-    ET.WARNING: Alert(
-      "",
-      "",
-      AlertStatus.normal, AlertSize.none,
-      Priority.LOWEST, VisualAlert.none, AudibleAlert.none, 0.),
-    ET.NO_ENTRY: NoEntryAlert("Seatbelt Unlatched"),
-  },
-
-  EventName.silentParkBrake: {
-    ET.WARNING: Alert(
-      "",
-      "",
-      AlertStatus.normal, AlertSize.none,
-      Priority.LOWEST, VisualAlert.none, AudibleAlert.none, 0.),
-    ET.NO_ENTRY: NoEntryAlert("Parking Brake Engaged"),
-  },
-
-  EventName.controlsMismatchLateral: {
-    ET.IMMEDIATE_DISABLE: ImmediateDisableAlert("Controls Mismatch: Lateral"),
-    ET.NO_ENTRY: NoEntryAlert("Controls Mismatch: Lateral"),
-  },
-
-
 }
 
 

selfdrive/selfdrived/selfdrived.py

@@ -23,8 +23,6 @@ from openpilot.selfdrive.controls.lib.latcontrol import MIN_LATERAL_CONTROL_SPEE
 
 from openpilot.system.version import get_build_metadata
 
-from openpilot.sunnypilot.mads.mads import ModularAssistiveDrivingSystem
-
 REPLAY = "REPLAY" in os.environ
 SIMULATION = "SIMULATION" in os.environ
 TESTING_CLOSET = "TESTING_CLOSET" in os.environ
@@ -133,10 +131,6 @@ class SelfdriveD:
     elif self.CP.passive:
       self.events.add(EventName.dashcamMode, static=True)
 
-    self.mads = ModularAssistiveDrivingSystem(self)
-    sock_services = list(self.pm.sock.keys()) + ['selfdriveStateSP']
-    self.pm = messaging.PubMaster(sock_services)
-
   def update_events(self, CS):
     """Compute onroadEvents from carState"""
 
@@ -457,25 +451,11 @@ class SelfdriveD:
       self.pm.send('onroadEvents', ce_send)
     self.events_prev = self.events.names.copy()
 
-    # selfdriveStateSP
-    ss_sp_msg = messaging.new_message('selfdriveStateSP')
-    ss_sp_msg.valid = True
-    ss_sp = ss_sp_msg.selfdriveStateSP
-    mads = ss_sp.mads
-    mads.state = self.mads.state_machine.state
-    mads.enabled = self.mads.enabled
-    mads.active = self.mads.active
-    mads.available = self.mads.enabled_toggle
-
-    self.pm.send('selfdriveStateSP', ss_sp_msg)
-
   def step(self):
     CS = self.data_sample()
     self.update_events(CS)
     if not self.CP.passive and self.initialized:
       self.enabled, self.active = self.state_machine.update(self.events)
-    if not self.CP.notCar:
-      self.mads.update(CS, self.sm)
     self.update_alerts(CS)
 
     self.publish_selfdriveState(CS)
@@ -493,8 +473,6 @@ class SelfdriveD:
       self.is_metric = self.params.get_bool("IsMetric")
       self.experimental_mode = self.params.get_bool("ExperimentalMode") and self.CP.openpilotLongitudinalControl
       self.personality = self.read_personality_param()
-
-      self.mads.read_params()
       time.sleep(0.1)
 
   def run(self):

selfdrive/selfdrived/tests/test_alerts.py

@@ -41,7 +41,7 @@ class TestAlerts:
     events = log.OnroadEvent.EventName.schema.enumerants
 
     for name, e in events.items():
-      if not name.endswith("DEPRECATED") and not name.startswith("eventReserved"):
+      if not name.endswith("DEPRECATED"):
         fail_msg = f"{name} @{e} not in EVENTS"
         assert e in EVENTS.keys(), fail_msg
 

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