bump

.github/workflows/build-all-tinygrad-models.yaml

@@ -140,7 +140,7 @@ jobs:
         run: |
           echo '${{ needs.setup.outputs.model_matrix }}' > matrix.json
           built=(); while IFS= read -r line; do built+=("$line"); done < <(
-            find output -maxdepth 1 -name 'model-*' -printf "%f\n" | sed -E 's/^model-//' | sed -E 's/-[0-9]+$//' | sed -E 's/ \([^)]*\)//' | awk '{gsub(/^ +| +$/, ""); print}'
+            ls output | sed -E 's/^model-//' | sed -E 's/-[0-9]+$//' | sed -E 's/ \([^)]*\)//' | awk '{gsub(/^ +| +$/, ""); print}'
           )
           jq -c --argjson built "$(printf '%s\n' "${built[@]}" | jq -R . | jq -s .)" \
             'map(select(.display_name as $n | ($built | index($n | gsub("^ +| +$"; "")) | not)))' matrix.json > retry_matrix.json
@@ -168,7 +168,6 @@ jobs:
     if: ${{ !cancelled() && (needs.get_and_build.result != 'failure' || needs.retry_get_and_build.result == 'success' || (needs.retry_failed_models.outputs.retry_matrix != '[]' && needs.retry_failed_models.outputs.retry_matrix != '')) }}
     runs-on: ubuntu-latest
     strategy:
-      fail-fast: false
       max-parallel: 1
       matrix:
         model: ${{ fromJson(needs.setup.outputs.model_matrix) }}

.github/workflows/repo-maintenance.yaml

@@ -43,6 +43,7 @@ jobs:
       with:
         submodules: true
     - name: uv lock
+      if: github.repository == 'commaai/openpilot'
       run: |
         python3 -m ensurepip --upgrade
         pip3 install uv
@@ -56,9 +57,6 @@ jobs:
     - name: bump submodules
       run: |
         git config --global --add safe.directory '*'
-        git config submodule.msgq.update none
-        git config submodule.rednose_repo.update none
-        git config submodule.teleoprtc_repo.update none
         git config submodule.tinygrad.update none
         git submodule update --remote
         git add .

.gitmodules

@@ -15,7 +15,7 @@
   url = https://github.com/commaai/teleoprtc
 [submodule "tinygrad"]
   path = tinygrad_repo
-  url = https://github.com/sunnypilot/tinygrad.git
+  url = https://github.com/commaai/tinygrad.git
 [submodule "sunnypilot/neural_network_data"]
   path = sunnypilot/neural_network_data
   url = https://github.com/sunnypilot/neural-network-data.git

Dockerfile.sunnypilot

@@ -9,6 +9,4 @@ WORKDIR ${OPENPILOT_PATH}
 
 COPY . ${OPENPILOT_PATH}/
 
-ENV UV_BIN="/home/batman/.local/bin/"
-ENV PATH="$UV_BIN:$PATH"
-RUN UV_PROJECT_ENVIRONMENT=$VIRTUAL_ENV uv run scons --cache-readonly -j$(nproc)
+RUN scons --cache-readonly -j$(nproc)

selfdrive/car/cruise.py

@@ -48,14 +48,16 @@ class VCruiseHelper(VCruiseHelperSP):
 
     self.get_minimum_set_speed(is_metric)
 
+    _enabled = self.update_enabled_state(CS, enabled)
+    if not self.CP.pcmCruise or not self.CP_SP.pcmCruiseSpeed:
+      self.update_button_timers(CS, enabled)
+
     if CS.cruiseState.available:
-      _enabled = self.update_enabled_state(CS, enabled)
       if not self.CP.pcmCruise or (not self.CP_SP.pcmCruiseSpeed and _enabled):
         # if stock cruise is completely disabled, then we can use our own set speed logic
         self._update_v_cruise_non_pcm(CS, _enabled, is_metric)
         self.update_speed_limit_assist_v_cruise_non_pcm()
         self.v_cruise_cluster_kph = self.v_cruise_kph
-        self.update_button_timers(CS, enabled)
       else:
         self.v_cruise_kph = CS.cruiseState.speed * CV.MS_TO_KPH
         self.v_cruise_cluster_kph = CS.cruiseState.speedCluster * CV.MS_TO_KPH

selfdrive/modeld/SConscript

@@ -50,7 +50,7 @@ def tg_compile(flags, model_name):
 # Compile small models
 for model_name in ['driving_vision', 'driving_policy', 'dmonitoring_model']:
   flags = {
-    'larch64': 'DEV=QCOM FLOAT16=1 NOLOCALS=1 IMAGE=2 JIT_BATCH_SIZE=0',
+    'larch64': 'DEV=QCOM',
     'Darwin': f'DEV=CPU HOME={os.path.expanduser("~")} IMAGE=0', # tinygrad calls brew which needs a $HOME in the env
   }.get(arch, 'DEV=CPU CPU_LLVM=1 IMAGE=0')
   tg_compile(flags, model_name)

selfdrive/ui/mici/onroad/model_renderer.py

@@ -12,7 +12,7 @@ from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.lib.shader_polygon import draw_polygon, Gradient
 from openpilot.system.ui.widgets import Widget
 
-from openpilot.selfdrive.ui.sunnypilot.mici.onroad.model_renderer import LANE_LINE_COLORS_SP, ModelRendererSP
+from openpilot.selfdrive.ui.sunnypilot.mici.onroad.model_renderer import LANE_LINE_COLORS_SP
 
 CLIP_MARGIN = 500
 MIN_DRAW_DISTANCE = 10.0
@@ -51,10 +51,9 @@ class LeadVehicle:
   fill_alpha: int = 0
 
 
-class ModelRenderer(Widget, ModelRendererSP):
+class ModelRenderer(Widget):
   def __init__(self):
-    Widget.__init__(self)
-    ModelRendererSP.__init__(self)
+    super().__init__()
     self._longitudinal_control = False
     self._experimental_mode = False
     self._blend_filter = FirstOrderFilter(1.0, 0.25, 1 / gui_app.target_fps)
@@ -341,10 +340,6 @@ class ModelRenderer(Widget, ModelRendererSP):
     allow_throttle = sm['longitudinalPlan'].allowThrottle or not self._longitudinal_control
     self._blend_filter.update(int(allow_throttle))
 
-    if ui_state.rainbow_path:
-      self.rainbow_path.draw_rainbow_path(self._rect, self._path)
-      return
-
     if self._experimental_mode:
       # Draw with acceleration coloring
       if ui_state.status == UIStatus.DISENGAGED:

selfdrive/ui/sunnypilot/layouts/settings/sunnylink.py

@@ -355,10 +355,5 @@ class SunnylinkLayout(Widget):
 
   def show_event(self):
     super().show_event()
-    ui_state.sunnylink_state.set_settings_open(True)
     self._scroller.show_event()
     self._sunnylink_description.set_visible(False)
-
-  def hide_event(self):
-    super().hide_event()
-    ui_state.sunnylink_state.set_settings_open(False)

selfdrive/ui/sunnypilot/mici/onroad/model_renderer.py

@@ -6,14 +6,8 @@ See the LICENSE.md file in the root directory for more details.
 """
 import pyray as rl
 from openpilot.selfdrive.ui.ui_state import UIStatus
-from openpilot.selfdrive.ui.sunnypilot.onroad.rainbow_path import RainbowPath
 
 LANE_LINE_COLORS_SP = {
   UIStatus.LAT_ONLY: rl.Color(0, 255, 64, 255),
   UIStatus.LONG_ONLY: rl.Color(0, 255, 64, 255),
 }
-
-
-class ModelRendererSP:
-  def __init__(self):
-    self.rainbow_path = RainbowPath()

selfdrive/ui/sunnypilot/onroad/turn_signal.py

@@ -72,28 +72,72 @@ class TurnSignalWidget(Widget):
 
 
 class TurnSignalController:
-  def __init__(self):
-    self._config = TurnSignalConfig()
+  def __init__(self, config: TurnSignalConfig | None = None):
+    self._config = config or TurnSignalConfig()
     self._left_signal = TurnSignalWidget(direction=IconSide.left)
     self._right_signal = TurnSignalWidget(direction=IconSide.right)
-
-  @staticmethod
-  def _update_signal(signal, blindspot, blinker):
-    if ui_state.blindspot and blindspot:
-      signal.activate('blind_spot')
-    elif ui_state.turn_signals and blinker:
-      signal.activate('signal')
-    else:
-      signal.deactivate()
+    self._last_icon_side = None
 
   def update(self):
-    CS = ui_state.sm['carState']
+    sm = ui_state.sm
+    ss = sm['selfdriveState']
 
-    self._update_signal(self._left_signal, CS.leftBlindspot, CS.leftBlinker)
-    self._update_signal(self._right_signal, CS.rightBlindspot, CS.rightBlinker)
+    event_name = ss.alertType.split('/')[0] if ss.alertType else ''
+
+    if event_name == 'preLaneChangeLeft':
+      self._last_icon_side = IconSide.left
+      self._left_signal.activate('signal')
+      self._right_signal.deactivate()
+
+    elif event_name == 'preLaneChangeRight':
+      self._last_icon_side = IconSide.right
+      self._right_signal.activate('signal')
+      self._left_signal.deactivate()
+
+    elif event_name == 'laneChange':
+      if self._last_icon_side == IconSide.left:
+        self._left_signal.activate('signal')
+        self._right_signal.deactivate()
+      elif self._last_icon_side == IconSide.right:
+        self._right_signal.activate('signal')
+        self._left_signal.deactivate()
+
+    elif event_name == 'laneChangeBlocked':
+      CS = sm['carState']
+      if CS.leftBlinker:
+        icon_side = IconSide.left
+      elif CS.rightBlinker:
+        icon_side = IconSide.right
+      else:
+        icon_side = self._last_icon_side
+
+      if icon_side == IconSide.left:
+        self._left_signal.activate('blind_spot')
+        self._right_signal.deactivate()
+      elif icon_side == IconSide.right:
+        self._right_signal.activate('blind_spot')
+        self._left_signal.deactivate()
+
+    else:
+      self._last_icon_side = None
+      CS = sm['carState']
+
+      if CS.leftBlindspot:
+        self._left_signal.activate('blind_spot')
+      elif CS.leftBlinker:
+        self._left_signal.activate('signal')
+      else:
+        self._left_signal.deactivate()
+
+      if CS.rightBlindspot:
+        self._right_signal.activate('blind_spot')
+      elif CS.rightBlinker:
+        self._right_signal.activate('signal')
+      else:
+        self._right_signal.deactivate()
 
   def render(self, rect: rl.Rectangle):
-    if not ui_state.turn_signals and not ui_state.blindspot:
+    if not ui_state.turn_signals:
       return
 
     x = rect.x + rect.width / 2

sunnypilot/modeld_v2/SConscript

@@ -60,7 +60,7 @@ def tg_compile(flags, model_name):
 for model_name in ['supercombo', 'driving_vision', 'driving_off_policy', 'driving_policy']:
   if File(f"models/{model_name}.onnx").exists():
     flags = {
-      'larch64': 'DEV=QCOM FLOAT16=1 NOLOCALS=1 IMAGE=2 JIT_BATCH_SIZE=0',
+      'larch64': 'DEV=QCOM',
       'Darwin': f'DEV=CPU HOME={os.path.expanduser("~")} IMAGE=0', # tinygrad calls brew which needs a $HOME in the env
     }.get(arch, 'DEV=CPU CPU_LLVM=1 IMAGE=0')
     tg_compile(flags, model_name)

sunnypilot/modeld_v2/modeld.py

@@ -1,11 +1,4 @@
 #!/usr/bin/env python3
-import os
-from openpilot.system.hardware import TICI
-os.environ['DEV'] = 'QCOM' if TICI else 'CPU'
-USBGPU = "USBGPU" in os.environ
-if USBGPU:
-  os.environ['DEV'] = 'AMD'
-  os.environ['AMD_IFACE'] = 'USB'
 import time
 import numpy as np
 import cereal.messaging as messaging

sunnypilot/models/fetcher.py

@@ -116,7 +116,7 @@ class ModelCache:
 
 class ModelFetcher:
   """Handles fetching and caching of model data from remote source"""
-  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-docs/refs/heads/gh-pages/docs/driving_models_v14.json"
+  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-docs/refs/heads/gh-pages/docs/driving_models_v11.json"
 
   def __init__(self, params: Params):
     self.params = params

sunnypilot/models/helpers.py

@@ -19,8 +19,8 @@ from openpilot.system.hardware.hw import Paths
 from pathlib import Path
 
 # see the README.md for more details on the model selector versioning
-CURRENT_SELECTOR_VERSION = 14
-REQUIRED_MIN_SELECTOR_VERSION = 14
+CURRENT_SELECTOR_VERSION = 13
+REQUIRED_MIN_SELECTOR_VERSION = 12
 
 USE_ONNX = os.getenv('USE_ONNX', PC)
 

sunnypilot/models/runners/model_runner.py

@@ -1,7 +1,9 @@
+import os
 from abc import abstractmethod, ABC
 
 import numpy as np
 from openpilot.sunnypilot.models.helpers import get_active_bundle
+from openpilot.system.hardware import TICI
 from openpilot.sunnypilot.models.runners.constants import NumpyDict, ShapeDict, CLMemDict, FrameDict, Model, SliceDict, SEND_RAW_PRED
 from openpilot.system.hardware.hw import Paths
 import pickle
@@ -9,6 +11,15 @@ import pickle
 CUSTOM_MODEL_PATH = Paths.model_root()
 
 
+# Set QCOM environment variable for TICI devices, potentially enabling hardware acceleration
+USBGPU = "USBGPU" in os.environ
+if USBGPU:
+  os.environ['DEV'] = 'AMD'
+  os.environ['AMD_IFACE'] = 'USB'
+else:
+  os.environ['DEV'] = 'QCOM' if TICI else 'CPU'
+
+
 class ModelData:
   """
   Stores metadata and configuration for a specific machine learning model.

sunnypilot/models/runners/tinygrad/tinygrad_runner.py

@@ -51,7 +51,7 @@ class TinygradRunner(ModelRunner, SupercomboTinygrad, PolicyTinygrad, VisionTiny
     self.input_to_dtype = {}
     self.input_to_device = {}
     for idx, name in enumerate(self.model_run.captured.expected_names):
-      info = self.model_run.captured.expected_input_info[idx]
+      info = self.model_run.captured.expected_st_vars_dtype_device[idx]
       self.input_to_dtype[name] = info[2]  # dtype
       self.input_to_device[name] = info[3]  # device
 
@@ -84,7 +84,7 @@ class TinygradRunner(ModelRunner, SupercomboTinygrad, PolicyTinygrad, VisionTiny
 
   def _run_model(self) -> NumpyDict:
     """Runs the Tinygrad model inference and parses the outputs."""
-    outputs = self.model_run(**self.inputs).numpy().flatten()
+    outputs = self.model_run(**self.inputs).contiguous().realize().uop.base.buffer.numpy()
     return self._parse_outputs(outputs)
 
   def _parse_outputs(self, model_outputs: np.ndarray) -> NumpyDict:

sunnypilot/selfdrive/controls/lib/smart_cruise_control/tests/test_vision_controller.py

@@ -5,7 +5,6 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
 import numpy as np
-import pytest
 
 import cereal.messaging as messaging
 from cereal import custom, log
@@ -13,52 +12,11 @@ from openpilot.common.params import Params
 from openpilot.common.realtime import DT_MDL
 from openpilot.selfdrive.car.cruise import V_CRUISE_UNSET
 from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control import MIN_V
-from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import SmartCruiseControlVision, _ENTERING_PRED_LAT_ACC_TH
+from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import SmartCruiseControlVision
 
 VisionState = custom.LongitudinalPlanSP.SmartCruiseControl.VisionState
 
 
-def _th_above_f32(th: float) -> float:
-  """
-  Return the next representable float32 *above* `th`.
-  This avoids flaky comparisons around thresholds due to float32 rounding.
-  """
-  th32 = np.float32(th)
-  above32 = np.nextafter(th32, np.float32(np.inf), dtype=np.float32)
-  return float(above32)
-
-
-def _build_single_spike_filtered(n: int, base: float = 1.0) -> np.ndarray:
-  """
-  Create an array where max() is >= threshold but p97 is < threshold.
-  This demonstrates the behavior difference vs np.amax().
-
-  Note: We intentionally construct using float32-representable values to match
-  the data path through cereal/capnp.
-  """
-  th = float(_ENTERING_PRED_LAT_ACC_TH)
-  th32 = float(np.float32(th))
-
-  # numpy percentile default is linear interpolation: idx=(n-1)*p/100
-  idx = (n - 1) * 0.97
-  w = float(idx - np.floor(idx))
-
-  base32 = float(np.float32(base))
-
-  # Choose spike so that p97 = base + w*(spike-base) < th
-  # -> spike < base + (th-base)/w. Use a margin (0.9) and ensure spike >= th.
-  if w == 0.0:
-    spike = th32 + 1.0
-  else:
-    spike = base32 + (th32 - base32) / w * 0.9
-    spike = max(spike, th32 + 0.01)
-
-  arr = np.full(n, base32, dtype=np.float32)
-  arr[-1] = np.float32(spike)
-  return arr
-
-
 def generate_modelV2():
   model = messaging.new_message('modelV2')
   position = log.XYZTData.new_message()
@@ -143,72 +101,4 @@ class TestSmartCruiseControlVision:
       self.scc_v.update(self.sm, True, False, 0., 0., 0.)
     assert self.scc_v.state == VisionState.enabled
 
-  @pytest.mark.parametrize(
-    "case, should_enter",
-    [
-      ("p97_just_above_threshold", True),
-      ("single_spike_filtered", False),
-      ("persistent_high_values", True),
-    ],
-    ids=[
-      "p97>threshold_enters",
-      "single_spike_max_large_but_p97_below_threshold",
-      "high_values_persist_trigger_entering",
-    ],
-  )
-  def test_max_pred_lat_acc_uses_p97_and_threshold(self, case, should_enter):
-    n = len(ModelConstants.T_IDXS)
-    th = float(_ENTERING_PRED_LAT_ACC_TH)
-
-    if case == "p97_just_above_threshold":
-      # Use the next representable float32 above threshold to avoid float32 rounding flakiness.
-      val = _th_above_f32(th)
-      pred_lat_accels = np.full(n, np.float32(val), dtype=np.float32)
-
-    elif case == "single_spike_filtered":
-      pred_lat_accels = _build_single_spike_filtered(n, base=1.0)
-
-    elif case == "persistent_high_values":
-      # Make enough "high" samples so p97 is driven by the persistent trend, not a single outlier.
-      high_count = max(2, int(np.ceil(n * 0.03)) + 1)
-      pred_lat_accels = np.full(n, np.float32(1.0), dtype=np.float32)
-      pred_lat_accels[-high_count:] = np.float32(2.0)
-      pred_lat_accels[-1] = np.float32(8.0)  # keep one big outlier too
-
-    else:
-      raise AssertionError(f"Unknown case: {case}")
-
-    # Override model predictions so:
-    # predicted_lat_accels = abs(orientationRate.z) * velocity.x == pred_lat_accels
-    mdl = generate_modelV2()
-    mdl.modelV2.velocity.x = [1.0 for _ in range(n)]
-    mdl.modelV2.orientationRate.z = [float(x) for x in pred_lat_accels]
-    self.sm["modelV2"] = mdl.modelV2
-
-    v_ego = float(MIN_V + 5.0)
-
-    # 1st update: disabled -> enabled
-    self.scc_v.update(self.sm, True, False, v_ego, 0.0, 0.0)
-    # 2nd update: evaluate entering condition from enabled state
-    self.scc_v.update(self.sm, True, False, v_ego, 0.0, 0.0)
-
-    # Controller does percentile on numpy float64 arrays (values already quantized by capnp),
-    # so compute expected in float64 to match behavior and avoid interpolation/rounding deltas.
-    expected_p97 = float(np.percentile(pred_lat_accels.astype(np.float64), 97))
-
-    # allow tiny numeric differences due to float conversions/interpolation
-    assert np.isclose(self.scc_v.max_pred_lat_acc, expected_p97, rtol=1e-6, atol=1e-5)
-
-    if should_enter:
-      # We assert entering primarily by state (this is the actual intended behavior).
-      assert self.scc_v.state == VisionState.entering
-      # Optional sanity: should be >= threshold with some margin (since we used nextafter above threshold).
-      assert self.scc_v.max_pred_lat_acc > th
-
-    else:
-      # Difference vs np.amax(): max can be above threshold, but p97 stays below it.
-      assert float(np.max(pred_lat_accels)) >= th
-      assert self.scc_v.max_pred_lat_acc < th
-      assert self.scc_v.state == VisionState.enabled
-
   # TODO-SP: mock modelV2 data to test other states

sunnypilot/selfdrive/controls/lib/smart_cruise_control/vision_controller.py

@@ -90,7 +90,7 @@ class SmartCruiseControlVision:
 
       # get the maximum lat accel from the model
       predicted_lat_accels = rate_plan * vel_plan
-      self.max_pred_lat_acc = np.percentile(predicted_lat_accels, 97)
+      self.max_pred_lat_acc = np.amax(predicted_lat_accels)
 
       # get the maximum curve based on the current velocity
       v_ego = max(self.v_ego, 0.1)  # ensure a value greater than 0 for calculations

sunnypilot/sunnylink/sunnylink_state.py

@@ -109,8 +109,6 @@ class SunnylinkState:
     self.sunnylink_dongle_id = self._params.get("SunnylinkDongleId")
     self._api = SunnylinkApi(self.sunnylink_dongle_id)
 
-    self._panel_open = False
-
     self._load_initial_state()
 
   def _load_initial_state(self) -> None:
@@ -168,14 +166,9 @@ class SunnylinkState:
 
   def _worker_thread(self) -> None:
     while self._running:
-      with self._lock:
-        panel_open = self._panel_open
-
-      if panel_open:
-        self._sm.update()
-        if self.is_connected():
-          self._fetch_roles()
-          self._fetch_users()
+      if self.is_connected():
+        self._fetch_roles()
+        self._fetch_users()
 
       for _ in range(int(self.FETCH_INTERVAL / self.SLEEP_INTERVAL)):
         if not self._running:
@@ -227,9 +220,5 @@ class SunnylinkState:
     else:
       return style.ITEM_TEXT_VALUE_COLOR
 
-  def set_settings_open(self, _open: bool) -> None:
-    with self._lock:
-      self._panel_open = _open
-
   def __del__(self):
     self.stop()

uv.lock

@@ -415,11 +415,11 @@ wheels = [
 
 [[package]]
 name = "filelock"
-version = "3.24.2"
+version = "3.20.3"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/02/a8/dae62680be63cbb3ff87cfa2f51cf766269514ea5488479d42fec5aa6f3a/filelock-3.24.2.tar.gz", hash = "sha256:c22803117490f156e59fafce621f0550a7a853e2bbf4f87f112b11d469b6c81b", size = 37601, upload-time = "2026-02-16T02:50:45.614Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/1d/65/ce7f1b70157833bf3cb851b556a37d4547ceafc158aa9b34b36782f23696/filelock-3.20.3.tar.gz", hash = "sha256:18c57ee915c7ec61cff0ecf7f0f869936c7c30191bb0cf406f1341778d0834e1", size = 19485, upload-time = "2026-01-09T17:55:05.421Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/e7/04/a94ebfb4eaaa08db56725a40de2887e95de4e8641b9e902c311bfa00aa39/filelock-3.24.2-py3-none-any.whl", hash = "sha256:667d7dc0b7d1e1064dd5f8f8e80bdac157a6482e8d2e02cd16fd3b6b33bd6556", size = 24152, upload-time = "2026-02-16T02:50:44Z" },
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