he does not like 1ms

decay one line and give full authority in curvy curves; kappa=curv
Merge branch 'master' into laneful-curves
2026-10-24 08:53:42 +08:00 · 2026-10-23 11:56:25 -07:00 · 2026-10-23 11:55:31 -07:00 · 2026-10-23 00:05:23 -07:00 · 2026-10-22 23:54:18 -07:00 · 2026-10-22 23:52:10 -07:00
54 changed files with 1460 additions and 969 deletions
@@ -115,7 +115,7 @@ jobs:
          env ${TG_FLAGS} python3 ${{ github.workspace }}/${{ env.COMPILER }}/compile_onnx.py \
            ${{ github.workspace }}/${{ env.SMALL_ONNX }} \
            ${{ github.workspace }}/${{ env.SMALL_PKL }} \
-            --device-input "*" --out-of-band --benchmark-runs 1
+            --out-of-band --benchmark-runs 1

      - name: Prepare output
        env:
@@ -440,9 +440,10 @@ jobs:
          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"

          taskset -c 7 env ${TG_FLAGS} python3 \
-            ${{ github.workspace }}/tinygrad_repo/examples/openpilot/compile3.py \
+            ${{ github.workspace }}/tinygrad_repo/examples/openpilot/compile_onnx.py \
            ${{ github.workspace }}/${{ env.DM_ONNX }} \
-            ${{ github.workspace }}/${{ env.DM_PKL }}
+            ${{ github.workspace }}/${{ env.DM_PKL }} \
+            --out-of-band --benchmark-runs 1

      - name: Compile DM warp
        run: |
@@ -58,6 +58,11 @@ jobs:

      - name: Create Pull Request
        uses: peter-evans/create-pull-request@9153d834b60caba6d51c9b9510b087acf9f33f83
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          GIT_CONFIG_COUNT: 1
+          GIT_CONFIG_KEY_0: credential.https://huggingface.co.helper
+          GIT_CONFIG_VALUE_0: '!f() { test "$1" = get && echo username=user && echo "password=$HF_TOKEN"; }; f'
        with:
          author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
          token: ${{ secrets.GITHUB_TOKEN }}
@@ -69,3 +74,7 @@ jobs:
          labels: bot
          add-paths: |
            openpilot/sunnypilot/modeld_v2/models/*.pkl
+
+      - name: Reset lfs access
+        if: always()
+        run: git config --local --unset-all "lfs.$(git config -f .lfsconfig lfs.url).access" || true
@@ -33,7 +33,7 @@ jobs:

      - name: LFS Fetch
        run: |
-          git lfs fetch
+          git lfs fetch || echo "::warning::some objects are missing on commaai/openpilot-lfs; mirroring the rest"

      - name: Set up Git
        run: |
@@ -68,6 +68,7 @@ jobs:
          git config lfs.activitytimeout 300
          git config lfs.transfer.maxretries 5
          git config lfs.concurrenttransfers 4
+          git config lfs.allowincompletepush true

      - name: Push LFS
        id: sync-and-commit
@@ -81,3 +82,80 @@ jobs:
          done
          echo "All push attempts failed"
          exit 1
+
+      - name: Checkout sunnypilot
+        uses: actions/checkout@v4
+        with:
+          repository: 'sunnypilot/sunnypilot'
+          path: sunnypilot
+          fetch-depth: 0
+          filter: blob:limit=1k
+          lfs: false
+
+      - name: Reference objects on sunnypilot-lfs
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: |
+          set -euo pipefail
+          GIT_LFS_SKIP_SMUDGE=1 git clone --quiet https://huggingface.co/sunnypilot/sunnypilot-lfs hf-lfs
+          mkdir -p hf-lfs/all
+          cat > scan_pointers.py <<'EOF'
+          import re, subprocess, sys, threading
+          repo = sys.argv[1]
+          chk = subprocess.run(["git", "-C", repo, "cat-file", "--batch-all-objects",
+                                "--batch-check=%(objectname) %(objecttype) %(objectsize)"],
+                               capture_output=True, text=True, check=True).stdout
+          small = [f[0] for f in (l.split() for l in chk.splitlines()) if f[1] == "blob" and int(f[2]) < 1024]
+          p = subprocess.Popen(["git", "-C", repo, "cat-file", "--batch=%(objectsize)"],
+                               stdin=subprocess.PIPE, stdout=subprocess.PIPE)
+          def feed():
+            for sha in small:
+              p.stdin.write(sha.encode() + b"\n")
+            p.stdin.close()
+          threading.Thread(target=feed, daemon=True).start()
+          rx = re.compile(rb"^version https://git-lfs\.github\.com/spec/v1\noid sha256:([0-9a-f]{64})\nsize ([0-9]+)\n")
+          seen = {}
+          for _ in small:
+            n = int(p.stdout.readline()); body = p.stdout.read(n); p.stdout.read(1)
+            m = rx.match(body)
+            if m:
+              seen.setdefault(m.group(1).decode(), m.group(2).decode())
+          for oid, size in sorted(seen.items()):
+            print(oid, size)
+          EOF
+          for repo in . sunnypilot; do
+            python3 scan_pointers.py "$repo"
+          done | sort -u | while read -r oid size; do
+            [ -e "hf-lfs/all/$oid" ] && continue
+            printf 'version https://git-lfs.github.com/spec/v1\noid sha256:%s\nsize %s\n' "$oid" "$size" > "hf-lfs/all/$oid"
+            echo "$oid"
+          done > new_oids.txt
+          echo "new pointer files: $(wc -l < new_oids.txt)"
+
+          dropped=0
+          while mapfile -t -n 100 chunk && ((${#chunk[@]})); do
+            body=$(for oid in "${chunk[@]}"; do
+                     size=$(awk '/^size /{print $2}' "hf-lfs/all/$oid")
+                     printf '{"oid":"%s","size":%s}\n' "$oid" "$size"
+                   done | jq -s '{operation:"download",transfers:["basic"],objects:.}')
+            for attempt in 1 2 3 4 5; do
+              resp=$(curl -sS -u "user:${HF_TOKEN}" -w '\n%{http_code}' \
+                       -H 'Accept: application/vnd.git-lfs+json' -H 'Content-Type: application/vnd.git-lfs+json' \
+                       --data "$body" "${LFS_URL}/objects/batch") && [ "$(tail -n1 <<<"$resp")" = 200 ] && break
+              echo "batch check attempt $attempt failed ($(tail -n1 <<<"$resp")), retrying in 60s"; sleep 60
+            done
+            [ "$(tail -n1 <<<"$resp")" = 200 ] || { echo "batch check failed"; exit 1; }
+            for oid in $(sed '$d' <<<"$resp" | jq -r '.objects[] | select(.error) | .oid'); do
+              rm -f "hf-lfs/all/$oid"; dropped=$((dropped+1))
+            done
+          done < new_oids.txt
+          echo "dropped (not on HF): $dropped"
+
+          cd hf-lfs
+          git add -A all
+          if git diff --cached --quiet; then
+            echo "nothing new to reference"
+            exit 0
+          fi
+          git commit -q -m "Reference $(git diff --cached --name-only | wc -l | tr -d ' ') new LFS objects"
+          git push origin HEAD:main
@@ -594,8 +594,14 @@ jobs:
      - name: Publish chestnut branch
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
        run: |
          CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
+          cp .lfsconfig "${{ env.OUTPUT_DIR }}/"
+          echo 'openpilot/selfdrive/modeld/models/big_*_tinygrad.pkl filter=lfs diff=lfs merge=lfs -text' > "${{ env.OUTPUT_DIR }}/.gitattributes"
+          git lfs install
+          git config --global credential.helper store
+          echo "https://user:${HF_TOKEN}@huggingface.co" > ~/.git-credentials

          ${{ env.CI_DIR }}/publish.sh \
            "${{ github.workspace }}" \
@@ -3,9 +3,62 @@ on:
  pull_request:
    paths:
      - 'tinygrad_repo'
+      - 'openpilot/sunnypilot/modeld_v2/**'
  workflow_dispatch:

+env:
+  CI: 1
+  GIT_CONFIG_COUNT: 1
+  GIT_CONFIG_KEY_0: lfs.fetchexclude
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
+
 jobs:
+  plain-artifact:
+    name: Plain artifact round trip and pickle converter
+    runs-on: ubuntu-24.04
+    env:
+      PYTHONPATH: ${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}
+      TINYGRAD_TESTS: 1
+    steps:
+      - uses: actions/checkout@v7
+      - run: ./tools/op.sh setup
+      - name: Build openpilot
+        run: scons -j$(nproc)
+      - name: Compile, load, cache and fuse a model with the pinned tinygrad
+        env:
+          DEV: CPU
+        run: tools/op.sh test -v openpilot/sunnypilot/modeld_v2/tests/test_plain_artifact.py
+      - name: Install LLVM 20 and ROCm comgr for the amd mock, as tinygrad_repo/.github/actions/setup-tinygrad does
+        run: |
+          . /etc/os-release
+          curl -fsSL https://apt.llvm.org/llvm-snapshot.gpg.key | sudo tee /etc/apt/trusted.gpg.d/apt.llvm.org.asc > /dev/null
+          echo "deb http://apt.llvm.org/$VERSION_CODENAME/ llvm-toolchain-$VERSION_CODENAME-20 main" | sudo tee /etc/apt/sources.list.d/llvm.list
+          sudo mkdir -p /etc/apt/keyrings
+          curl -fsSL https://repo.radeon.com/rocm/rocm.gpg.key | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
+          echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/7.1 $VERSION_CODENAME main" | sudo tee /etc/apt/sources.list.d/rocm.list
+          printf 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600\n' | sudo tee /etc/apt/preferences.d/rocm-pin-600
+          sudo apt-get -qq update && sudo apt-get -qq install -y --no-install-recommends libllvm20 clang-20 lld-20 comgr
+          printf '/opt/rocm/lib\n/opt/rocm/lib64\n' | sudo tee /etc/ld.so.conf.d/rocm.conf && sudo ldconfig
+          echo "/usr/lib/llvm-20/bin" >> "$GITHUB_PATH"
+      - name: Convert a pickled USB+AMD jit and replay it under tinygrad's amd mock
+        env:
+          DEV: MOCKUSB+AMD
+          CHECK_OOB: 0
+          GMMU: 0
+        run: tools/op.sh test -v openpilot/sunnypilot/modeld_v2/tests/test_convert_upstream_pkl.py
+      - name: Where tinygrad moved, for the helper or failure point named above
+        if: failure() && github.event_name == 'pull_request'
+        run: |
+          git fetch -q --depth=1 origin "${{ github.base_ref }}"
+          old=$(git rev-parse "origin/${{ github.base_ref }}:tinygrad_repo") new=$(git rev-parse HEAD:tinygrad_repo)
+          git -C tinygrad_repo fetch -q origin "$old" || true
+          echo "tinygrad_repo $old -> $new, in what helpers.py and plain_artifact_compiler.py read:"
+          git -C tinygrad_repo diff "$old" "$new" -- tinygrad/uop/ops.py tinygrad/engine/jit.py tinygrad/engine/realize.py tinygrad/device.py \
+            tinygrad/helpers.py tinygrad/dtype.py tinygrad/renderer/__init__.py
+          echo "and in what convert_upstream_pkl.py decodes:"
+          git -C tinygrad_repo diff --stat "$old" "$new" -- tinygrad/runtime/autogen/am/pm4_nv.py tinygrad/runtime/autogen/amd_gpu.py
+          git -C tinygrad_repo diff "$old" "$new" -- tinygrad/runtime/support/hcq2.py tinygrad/runtime/support/usb.py tinygrad/runtime/ops_amd.py
+
  generate-matrix:
    runs-on: ubuntu-latest
    outputs:
@@ -138,6 +138,9 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
    status @0 :DownloadStatus;
    progress @1 :Float32;
    eta @2 :UInt32;
+    speed @3 :Float32;
+    canceling @4 :Bool;
+    resuming @5 :Bool;
  }

  struct Chunk {
@@ -465,6 +468,13 @@ struct ModelDataV2SP @0xa1680744031fdb2d {
  laneTurnDirection @0 :TurnDirection;
  leftLaneChangeEdgeBlock @1 :Bool;
  rightLaneChangeEdgeBlock @2 :Bool;
+  blendfulCurvature @3 :Float32;
+  blendfulTrust @4 :Float32;
+  modelCurvature @5 :Float32;
+  blendfulGoingAround @6 :Bool;
+  blendfulLeftProb @7 :Float32;
+  blendfulRightProb @8 :Float32;
+  blendfulLaneWidth @9 :Float32;

  enum TurnDirection {
    none @0;
@@ -94,7 +94,7 @@ _services: dict[str, tuple] = {
  "carControlSP": (True, 100., 10),
  "carStateSP": (True, 100., 10),
  "liveMapDataSP": (True, 1., 1),
-  "modelDataV2SP": (True, 20., None, QueueSize.BIG),
+  "modelDataV2SP": (True, 20., 10, QueueSize.BIG),
  "liveLocationKalman": (True, 20.),

  # debug
@@ -256,7 +256,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
    {"LagdValueCache", {PERSISTENT, FLOAT, "0.2"}},
    {"LaneTurnDesire", {PERSISTENT | BACKUP, BOOL, "0"}},
    {"LaneTurnValue", {PERSISTENT | BACKUP, FLOAT, "19.0"}},
-    {"LanefulStrength", {PERSISTENT | BACKUP, FLOAT, "0.0"}},
+    {"Blendful", {PERSISTENT | BACKUP, BOOL, "0"}},
    {"PlanplusControl", {PERSISTENT | BACKUP, FLOAT, "1.0"}},

    // mapd
@@ -48,8 +48,9 @@ def compile_model(onnx_path, pkl_path):
    Action(cmd, "  [ONNX] $TARGET"),
  )

-compile_model('models/dmonitoring_model.onnx', 'models/dmonitoring_model_tinygrad.pkl')
-compile_model('models/driving_supercombo.onnx', 'models/driving_tinygrad.pkl')
+if not os.getenv('SKIP_TINYGRAD_COMPILE'):
+  compile_model('models/dmonitoring_model.onnx', 'models/dmonitoring_model_tinygrad.pkl')
+  compile_model('models/driving_supercombo.onnx', 'models/driving_tinygrad.pkl')

 model_w, model_h = MEDMODEL_INPUT_SIZE
 for cam_w, cam_h in camera_configs:
@@ -62,7 +63,7 @@ for cam_w, cam_h in camera_configs:
  lenv.Command(warp_pkl_path, tinygrad_files + warp_deps + [Value(cmd)], cmd)

 dm_w, dm_h = DM_INPUT_SIZE
-for cam_w, cam_h in camera_configs:
+for cam_w, cam_h in [] if os.getenv('SKIP_TINYGRAD_COMPILE') else camera_configs:
  dm_pkl_path = File(f"models/dm_warp_{cam_w}x{cam_h}_tinygrad.pkl").abspath
  stride, y_height, uv_height, frame_size = get_nv12_info(cam_w, cam_h)
  cmd = (f'{tg_flags} {mac_brew_string} python3 "{compiler}/compile_warp.py" '
@@ -7,6 +7,7 @@ from functools import cached_property
 import os
 os.environ['GMMU'] = '0' # for chestnut fast loading, noop for qcom
 os.environ.setdefault('AM_POWER_LIMIT', '100')
+os.environ.setdefault('AM_PERF_LEVEL', 'high')
 from tinygrad.device import Buffer, Device
 from tinygrad.dtype import DType, dtypes
 from tinygrad.engine.realize import lower_and_compile
@@ -206,8 +206,6 @@ class AugmentedRoadView(CameraView):
  def _handle_mouse_release(self, mouse_pos: MousePos):
    # Don't trigger click callback if bookmark was triggered
    if not self._bookmark_icon.interacting():
-      if self._model_renderer.laneful.handle_tap(mouse_pos):
-        return
      super()._handle_mouse_release(mouse_pos)

  def _render(self, _):
@@ -141,7 +141,7 @@ class ModelRenderer(Widget, ModelRendererSP):
    if ui_state.status != UIStatus.DISENGAGED:
      self._draw_lane_lines()
      self._draw_path()
-      self.laneful.draw(self._rect)
+      self.blendful.draw(self._rect)

    if render_lead_indicator:
      self._update_leads(sm)
@@ -220,7 +220,7 @@ class ModelRenderer(Widget, ModelRendererSP):
    # Update road edges using raw points
    for road_edge in self._road_edges:
      road_edge.projected_points = self._map_line_to_polygon(road_edge.raw_points, line_width_factor, 0.0, max_idx)
-    self.laneful.update(self, max_idx)
+    self.blendful.update(self, max_idx)

    # Update path using raw points
    if lead and lead.present:
@@ -123,6 +123,8 @@ class ModelRenderer(Widget, ChevronMetrics, ModelRendererSP):
    # Draw elements
    self._draw_lane_lines()
    self._draw_path()
+    if self._lateral_active:
+      self.blendful.draw(self._rect)

    if render_lead_indicator and radar_state:
      self._draw_lead_indicator()
@@ -172,6 +174,7 @@ class ModelRenderer(Widget, ChevronMetrics, ModelRendererSP):
    # Update road edges using raw points
    for road_edge in self._road_edges:
      road_edge.projected_points = self._map_line_to_polygon(road_edge.raw_points, 0.025, 0.0, max_idx, max_distance)
+    self.blendful.update(self, max_idx, max_distance)

    # Update path using raw points
    if lead and lead.present:
@@ -8,7 +8,6 @@ from enum import IntEnum

 from openpilot.selfdrive.ui.sunnypilot.layouts.settings.cruise_sub_layouts.speed_limit_settings import SpeedLimitSettingsLayout
 from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.sunnypilot.mapd import MAPD_AVAILABLE
 from openpilot.system.ui.lib.multilang import tr, tr_noop
 from openpilot.system.ui.sunnypilot.widgets.list_view import toggle_item_sp, option_item_sp, simple_button_item_sp
 from openpilot.system.ui.widgets import Widget
@@ -30,7 +29,6 @@ ACC_ENABLED_DESCRIPTION = tr_noop("Enable custom Short & Long press increments f
 ACC_NOLONG_DESCRIPTION = tr_noop("This feature can only be used with sunnypilot longitudinal control enabled.")
 ACC_PCMCRUISE_DISABLED_DESCRIPTION = tr_noop("This feature is not supported on this platform due to vehicle limitations.")
 ONROAD_ONLY_DESCRIPTION = tr_noop("Start the vehicle to check vehicle compatibility.")
-MAP_UNAVAILABLE_DESCRIPTION = tr_noop("Map data is temporarily unavailable.")


 class CruiseLayout(Widget):
@@ -56,8 +54,7 @@ class CruiseLayout(Widget):

    self.scc_m_toggle = toggle_item_sp(
      title=tr("Smart Cruise Control - Map"),
-      description=(f"<b>{tr(MAP_UNAVAILABLE_DESCRIPTION)}</b>\n\n" if not MAPD_AVAILABLE else "") +
-                  tr("Use map data to estimate the appropriate speed to drive through turns ahead."),
+      description=tr("Use map data to estimate the appropriate speed to drive through turns ahead."),
      param="SmartCruiseControlMap")

    self.custom_acc_toggle = toggle_item_sp(
@@ -142,7 +139,7 @@ class CruiseLayout(Widget):
      if has_long or has_icbm:
        self.custom_acc_toggle.action_item.set_enabled(((has_long and not ui_state.CP.pcmCruise) or has_icbm) and ui_state.is_offroad())
        self.scc_v_toggle.action_item.set_enabled(True)
-        self.scc_m_toggle.action_item.set_enabled(MAPD_AVAILABLE)
+        self.scc_m_toggle.action_item.set_enabled(True)
      else:
        ui_state.params.remove("CustomAccIncrementsEnabled")
        ui_state.params.remove("SmartCruiseControlVision")
@@ -8,8 +8,6 @@ from collections.abc import Callable

 import pyray as rl
 from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.sunnypilot.mapd import MAPD_AVAILABLE
-from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit.common import Policy
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.sunnypilot.widgets.list_view import multiple_button_item_sp
 from openpilot.system.ui.widgets.network import NavButton
@@ -45,8 +43,6 @@ class SpeedLimitPolicyLayout(Widget):
      param="SpeedLimitPolicy",
      button_width=250,
    )
-    if not MAPD_AVAILABLE:
-      self._speed_limit_policy.action_item.set_enabled_buttons({Policy.car_state_only})

    items = [
      self._speed_limit_policy
@@ -55,8 +51,6 @@ class SpeedLimitPolicyLayout(Widget):

  @staticmethod
  def _get_policy_description():
-    if not MAPD_AVAILABLE:
-      return f"<b>{tr('Map data is temporarily unavailable. Using Speed Limit data only from Car.')}</b>"
    return get_highlighted_description(ui_state.params, "SpeedLimitPolicy", SPEED_LIMIT_POLICY_DESCRIPTIONS)

  def _render(self, rect):
@@ -102,13 +102,18 @@ class ModelsLayout(Widget):

    self.lagd_toggle = toggle_item_sp(tr("Live Learning Steer Delay"), "", param="LagdToggle")

+    self.blendful_toggle = toggle_item_sp(tr("Blendful"),
+                                          tr("Nudges the car toward the lane center when the lane lines are clear. Drives laneless when they are not."),
+                                          param="Blendful")
+
    self.camera_offset = option_item_sp(tr("Adjust Camera Offset"), "CameraOffset", -35, 35,
                                        tr("Virtually shift camera's perspective to move model's center to Left(+ values) or Right (- values)"),
                                        1, None, True, "", style.BUTTON_ACTION_WIDTH, None, True,
                                        lambda v: f"{v / 100:.2f} m")

    self.items = [self.small_model_item, self.big_model_item, self.cancel_download_item, self.download_item, self.refresh_item, self.clear_cache_item,
-                  self.lane_turn_desire_toggle, self.lane_turn_value_control, self.lagd_toggle, self.delay_control, self.camera_offset]
+                  self.blendful_toggle, self.lane_turn_desire_toggle, self.lane_turn_value_control, self.lagd_toggle, self.delay_control,
+                  self.camera_offset]

  def _update_lagd_description(self, lagd_toggle: bool):
    desc = tr("Enable this for the car to learn and adapt its steering response time. Disable to use a fixed steering response time. " +
@@ -235,13 +240,17 @@ class ModelsLayout(Widget):
    progress = sum(p.progress for p in progresses) / len(progresses)
    ds = custom.ModelManagerSP.DownloadStatus

+    if any(p.canceling for p in progresses):
+      return {"name": name, "downloading": True, "progress": progress, "status_text": tr("canceling...")}
    if ds.failed in statuses:
      # close.png is authored black and a tint cannot lift it, hence close2
      return {"name": name, "status_text": tr("download failed"), "text_color": rl.RED, "icon": "icons/close2.png"}
    if ds.verifying in statuses:
      return {"name": name, "downloading": True, "progress": progress, "status_text": tr("verifying")}
    if ds.downloading in statuses:
-      return {"name": name, "downloading": True, "progress": progress}
+      speed = max((p.speed for p in progresses), default=0.0)
+      status_text = f"{speed / 1024 ** 2:.1f} MB/s" if speed > 0 else "--.- MB/s"
+      return {"name": name, "downloading": True, "progress": progress, "status_text": status_text}
    if statuses <= {ds.downloaded, ds.cached}:
      return {"name": name, "text_color": ON_COLOR, "icon": "icons/checkmark.png"}
    # circled_slash is authored grey; tinting it again only darkens it
@@ -318,6 +327,7 @@ class ModelsLayout(Widget):
    self.lane_turn_desire_toggle.action_item.set_state(turn_desire)
    self.lane_turn_value_control.set_visible(turn_desire and advanced_controls)
    self.lagd_toggle.action_item.set_state(live_delay)
+    self.blendful_toggle.action_item.set_state(ui_state.params.get_bool("Blendful"))
    self.delay_control.set_visible(not live_delay and advanced_controls)
    new_step = int(round(100 / CV.MPH_TO_KPH)) if ui_state.is_metric else 100
    if self.lane_turn_value_control.action_item is not None and self.lane_turn_value_control.action_item.value_change_step != new_step:
@@ -1,39 +0,0 @@
-"""
-Copyright (c) 2021-, sunnypilot, and a number of other contributors.
-
-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.
-"""
-from openpilot.selfdrive.ui.mici.widgets.button import BigMultiToggle
-from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.widgets.scroller import NavScroller
-
-# above 1.0 the pull overshoots lane center and ping-pongs
-STRENGTHS = {"off": 0.0, "gentle": 0.5, "firm": 1.0}
-
-
-class LanefulStrengthToggle(BigMultiToggle):
-  """Tap to cycle LanefulStrength, like the driving personality toggle."""
-  def __init__(self):
-    super().__init__("laneful strength", list(STRENGTHS), select_callback=self._on_select,
-                     description="Nudges the car toward lane center.\n" +
-                                 "Firm centers faster than gentle.")
-    self.refresh()
-
-  def refresh(self):
-    strength = ui_state.params.get("LanefulStrength", return_default=True)
-    self.set_value(min(STRENGTHS, key=lambda k: abs(STRENGTHS[k] - strength)))
-
-  def _on_select(self, value: str):
-    ui_state.params.put("LanefulStrength", STRENGTHS[value])
-
-
-class LanefulLayoutMici(NavScroller):
-  def __init__(self):
-    super().__init__()
-    self._strength = LanefulStrengthToggle()
-    self._scroller.add_widget(self._strength)
-
-  def show_event(self):
-    super().show_event()
-    self._strength.refresh()
@@ -11,7 +11,7 @@ import pyray as rl
 from openpilot.cereal import custom
 from openpilot.selfdrive.ui.mici.widgets.dialog import BigConfirmationDialog, BigDialog
 from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS, get_selected_bundle
-from openpilot.selfdrive.ui.mici.widgets.button import BigButton
+from openpilot.selfdrive.ui.mici.widgets.button import BigButton, BigParamControl
 from openpilot.selfdrive.ui.ui_state import ui_state, device
 from openpilot.selfdrive.ui.sunnypilot.model_info import (active_source, big_model_state, bundles_for_source, carrying_model,
                                                           default_model_name, model_cache_size_mb, model_info, queued_name,
@@ -95,7 +95,12 @@ class ModelsLayoutMici(NavScroller):
    self.clear_cache_btn.set_click_callback(self._confirm_clear_cache)
    self._cache_size_time = 0.0

-    self.main_items = [self.current_model_info, self.select_model_btn, self.cancel_download_btn, self.refresh_btn, self.clear_cache_btn]
+    self.blendful_toggle = BigParamControl("blendful", "Blendful",
+                                           description="Nudges the car toward the lane center when the lane lines are clear.\n" +
+                                                       "Drives laneless when they are not.")
+
+    self.main_items = [self.current_model_info, self.select_model_btn, self.cancel_download_btn, self.refresh_btn, self.clear_cache_btn,
+                       self.blendful_toggle]
    self._scroller.add_widgets(self.main_items)

  @property
@@ -205,6 +210,10 @@ class ModelsLayoutMici(NavScroller):
      device.set_override_interactive_timeout(None)
      self._was_downloading = False

+  def show_event(self):
+    super().show_event()
+    self.blendful_toggle.refresh()
+
  def _update_state(self):
    super()._update_state()

@@ -251,11 +260,13 @@ class ModelsLayoutMici(NavScroller):
      self.current_model_info.info_text.set_text(tr("download failed"))

    elif manager.selectedBundle and manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.downloading:
-      self.cancel_download_btn.set_visible(True)
+      self.cancel_download_btn.set_visible(ui_state.params.get("ModelManager_DownloadRef") is not None)
      device.set_override_interactive_timeout(5)
      progress = 0.0
      count = 0
      verifying = False
+      canceling = False
+      speed = 0.0
      for model in manager.selectedBundle.models:
        count += 1
        p = model.artifact.downloadProgress
@@ -263,11 +274,14 @@ class ModelsLayoutMici(NavScroller):
                        custom.ModelManagerSP.DownloadStatus.verifying):
          progress += p.progress
          verifying = verifying or p.status == custom.ModelManagerSP.DownloadStatus.verifying
+          canceling = canceling or p.canceling
+          speed = max(speed, p.speed)  # only one file downloads at a time, so the non-zero speed is the live one
        elif p.status in (custom.ModelManagerSP.DownloadStatus.downloaded,
                          custom.ModelManagerSP.DownloadStatus.cached):
          progress += 100.0

-      self.current_model_info.current_model_header.set_text(tr("verifying") if verifying else tr("downloading"))
+      header = tr("canceling...") if canceling else tr("verifying") if verifying else tr("downloading")
+      self.current_model_info.current_model_header.set_text(header)
      self.cancel_download_btn.set_text(tr("cancel verification") if verifying else tr("cancel download"))
      self.current_model_info.current_model_header._shimmer = True
      name_text = manager.selectedBundle.internalName.lower()
@@ -276,7 +290,10 @@ class ModelsLayoutMici(NavScroller):
      self.current_model_info.current_model_text.set_text(name_text)
      self.current_model_info.info_header.set_text(tr("progress") + self._download_progress)
      self.current_model_info.info_header._shimmer = True
-      self.current_model_info.info_text.set_text(f"{progress/count:.2f}%")
+      progress_text = f"{progress/count:.2f}%"
+      if not verifying and not canceling:
+        progress_text += f"  |  {speed / 1024 ** 2:.1f} MB/s" if speed > 0 else "  |  --.- MB/s"
+      self.current_model_info.info_text.set_text(progress_text)

    elif manager.selectedBundle and manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.downloaded:
      self.current_model_info.info_header.set_text(tr("downloaded"))
@@ -11,7 +11,6 @@ from openpilot.selfdrive.ui.mici.widgets.button import BigCircleButton
 from openpilot.selfdrive.ui.mici.widgets.dialog import BigConfirmationDialog, BigDialog
 from openpilot.selfdrive.ui.sunnypilot.mici.layouts.sunnylink import SunnylinkLayoutMici
 from openpilot.selfdrive.ui.sunnypilot.mici.layouts.models import ModelsLayoutMici
-from openpilot.selfdrive.ui.sunnypilot.mici.layouts.laneful import LanefulLayoutMici
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.lib.multilang import tr
@@ -51,10 +50,6 @@ class SettingsLayoutSP(OP.SettingsLayout):
    models_btn = SettingsBigButton(tr("models"), "", gui_app.texture("../../sunnypilot/selfdrive/assets/offroad/icon_models.png", ICON_SIZE, ICON_SIZE))
    models_btn.set_click_callback(lambda: gui_app.push_widget(models_panel))

-    laneful_panel = LanefulLayoutMici()
-    laneful_btn = SettingsBigButton(tr("laneful"), "", gui_app.texture("icons_mici/settings/device/lkas.png", ICON_SIZE, ICON_SIZE))
-    laneful_btn.set_click_callback(lambda: gui_app.push_widget(laneful_panel))
-
    # onroad: enable button sits at the front (left of toggles)
    self._enable_offroad_btn_onroad = BigCircleButton(self.icon_offroad_enable, red=True)
    self._enable_offroad_btn_onroad.set_click_callback(lambda: self._handle_always_offroad(True))
@@ -72,8 +67,7 @@ class SettingsLayoutSP(OP.SettingsLayout):
    items = self._scroller._items.copy()

    items.insert(1, models_btn)
-    items.insert(2, laneful_btn)
-    items.insert(6, sunnylink_btn)
+    items.insert(5, sunnylink_btn)

    # front slots (only one ever visible at a time): exit-always-offroad, then enable-onroad
    items.insert(0, self._enable_offroad_btn_onroad)
@@ -1,122 +0,0 @@
-"""
-Copyright (c) 2021-, sunnypilot, and a number of other contributors.
-
-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.
-
-Laneful visuals: cyan lane-center target, thin white "after" path (model path bent by laneful's nudge),
-and a top-center readout of the pull. Mirrors the math in sunnypilot/modeld_v2/laneful.py.
-"""
-import numpy as np
-import pyray as rl
-from openpilot.common.filter_simple import FirstOrderFilter
-from openpilot.common.realtime import DT_MDL
-from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.lib.application import gui_app, FontWeight
-from openpilot.system.ui.lib.shader_polygon import draw_polygon
-from openpilot.system.ui.lib.text_measure import measure_text_cached
-
-CENTER_COLOR = (0, 200, 255)
-AFTER_COLOR = (255, 255, 255)
-# keep in sync with sunnypilot/modeld_v2/laneful.py
-LOOKAHEAD_TIME = 1.5
-MIN_LOOKAHEAD = 10.0
-MAX_ERROR = 0.5
-
-
-class LanefulRenderer:
-  def __init__(self):
-    self._center_points = np.empty((0, 2), dtype=np.float32)
-    self._after_points = np.empty((0, 2), dtype=np.float32)
-    self._trust = 0.0
-    self._strength = 0.0
-    self._frame = 0
-    self._font = gui_app.font(FontWeight.BOLD)
-    # smoothed copies for the readout so the numbers don't flicker
-    self._pull_display = FirstOrderFilter(0.0, 0.5, DT_MDL)
-    self._trust_display = FirstOrderFilter(0.0, 0.5, DT_MDL)
-    self._readout_rect: rl.Rectangle | None = None
-    self._settings_page = None
-
-  def update(self, renderer, max_idx: int) -> None:
-    """Called from the model renderer's update with its lane lines and path already in raw points."""
-    if self._frame % 60 == 0:
-      self._strength = ui_state.params.get("LanefulStrength", return_default=True)
-    self._frame += 1
-
-    left, right = renderer._lane_lines[1].raw_points, renderer._lane_lines[2].raw_points
-    stds = list(ui_state.sm['modelV2'].laneLineStds)
-    if self._strength <= 0.0 or len(left) == 0 or len(right) != len(left) or len(stds) < 3:
-      self._center_points = np.empty((0, 2), dtype=np.float32)
-      self._after_points = np.empty((0, 2), dtype=np.float32)
-      return
-
-    probs = renderer._lane_line_probs
-    l_prob = float(probs[1] * np.interp(stds[1], [0.15, 0.3], [1.0, 0.0]))
-    r_prob = float(probs[2] * np.interp(stds[2], [0.15, 0.3], [1.0, 0.0]))
-    width = np.clip(right[:, 1] - left[:, 1], 2.8, 4.5) if l_prob * r_prob > 0.5 else 3.7
-    center = left.copy()
-    center[:, 1] = (l_prob * (left[:, 1] + width / 2) + r_prob * (right[:, 1] - width / 2)) / (l_prob + r_prob + 1e-4)
-    self._trust = l_prob + r_prob - l_prob * r_prob
-    self._center_points = renderer._map_line_to_polygon(center, 0.1, 0.0, max_idx)
-
-    # "after" path: model path bent toward center the way laneful's pure-pursuit term steers, ending at the lookahead
-    path = renderer._path.raw_points
-    lookahead = max(ui_state.sm['carState'].vEgo * LOOKAHEAD_TIME, MIN_LOOKAHEAD)
-    error = float(np.clip(np.interp(lookahead, center[:, 0], center[:, 1]) - np.interp(lookahead, path[:, 0], path[:, 1]),
-                          -MAX_ERROR, MAX_ERROR))
-    self._pull_display.update(self._trust * error)  # what laneful actually pulls, 0 when lines are untrusted
-    self._trust_display.update(self._trust)
-    after = path.copy()
-    after[:, 1] += self._strength * self._trust * error * (path[:, 0] / lookahead) ** 2
-    self._after_points = renderer._map_line_to_polygon(after, 0.15, renderer._path_offset_z,
-                                                       renderer._get_path_length_idx(path[:, 0], lookahead))
-
-  def draw(self, rect: rl.Rectangle) -> None:
-    if self._center_points.size and self._trust > 0.05:
-      draw_polygon(rect, self._center_points, rl.Color(*CENTER_COLOR, int(np.clip(self._trust, 0.2, 1.0) * 255)))
-    if self._after_points.size:
-      draw_polygon(rect, self._after_points, rl.Color(*AFTER_COLOR, 200))
-    self._readout_rect = None
-    if self._strength > 0.0:
-      self._draw_readout(rect)
-
-  def handle_tap(self, pos) -> bool:
-    """Tapping the readout opens the laneful settings page. Returns True if the tap was consumed."""
-    r = self._readout_rect
-    if r is None or not (r.x - 20 <= pos.x <= r.x + r.width + 20 and r.y - 20 <= pos.y <= r.y + r.height + 20):
-      return False
-    if self._settings_page is None:
-      from openpilot.selfdrive.ui.sunnypilot.mici.layouts.laneful import LanefulLayoutMici
-      self._settings_page = LanefulLayoutMici()
-    gui_app.push_widget(self._settings_page)
-    return True
-
-  def _draw_readout(self, rect: rl.Rectangle) -> None:
-    """Top-center pill: pull toward lane center in cm (capped at 50), arrow = side,
-    bar grows from center toward the pull (full at the cap), brighter with more lane line trust."""
-    pull, trust = self._pull_display.x, self._trust_display.x
-    w, h = 190, 76
-    x, y = rect.x + (rect.width - w) / 2, rect.y + 10
-    cx, cy = x + w / 2, y + 30
-    self._readout_rect = rl.Rectangle(x, y, w, h)
-    rl.draw_rectangle_rounded(self._readout_rect, 0.5, 12, rl.Color(0, 0, 0, 170))
-
-    text = f"{abs(pull) * 100:.0f}"
-    text_w = measure_text_cached(self._font, text, 44, 0).x
-    rl.draw_text_ex(self._font, text, rl.Vector2(cx - text_w / 2, cy - 24), 44, 0, rl.WHITE)
-
-    active = rl.Color(*CENTER_COLOR, int(np.clip(abs(pull) / 0.1, 0.0, 1.0) * 255))
-    idle = rl.Color(255, 255, 255, 40)
-    lx, rx = x + 18, x + w - 18
-    rl.draw_triangle(rl.Vector2(lx, cy), rl.Vector2(lx + 16, cy + 12), rl.Vector2(lx + 16, cy - 12), active if pull < 0 else idle)
-    rl.draw_triangle(rl.Vector2(rx - 16, cy - 12), rl.Vector2(rx - 16, cy + 12), rl.Vector2(rx, cy), active if pull > 0 else idle)
-
-    bar = rl.Rectangle(x + 24, y + h - 16, w - 48, 6)
-    rl.draw_rectangle_rounded(bar, 1.0, 6, rl.Color(255, 255, 255, 40))
-    rl.draw_rectangle(int(cx - 1), int(bar.y - 2), 2, int(bar.height + 4), rl.Color(255, 255, 255, 120))
-    fill = bar.width / 2 * float(np.clip(abs(pull) / MAX_ERROR, 0.0, 1.0))
-    if fill > 1:
-      fill_x = cx if pull > 0 else cx - fill
-      rl.draw_rectangle_rounded(rl.Rectangle(fill_x, bar.y, fill, bar.height), 1.0, 6,
-                                rl.Color(*CENTER_COLOR, int(np.clip(0.3 + 0.7 * trust, 0.0, 1.0) * 255)))
@@ -6,7 +6,7 @@ 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.mici.onroad.laneful import LanefulRenderer
+from openpilot.selfdrive.ui.sunnypilot.onroad.blendful import BlendfulRenderer
 from openpilot.selfdrive.ui.sunnypilot.onroad.rainbow_path import RainbowPath

 LANE_LINE_COLORS_SP = {
@@ -18,4 +18,4 @@ LANE_LINE_COLORS_SP = {
 class ModelRendererSP:
  def __init__(self):
    self.rainbow_path = RainbowPath()
-    self.laneful = LanefulRenderer()
+    self.blendful = BlendfulRenderer()
@@ -0,0 +1,90 @@
+"""
+Copyright (c) 2021-, sunnypilot, and a number of other contributors.
+
+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 pyray as rl
+from openpilot.common.filter_simple import FirstOrderFilter
+from openpilot.common.realtime import DT_MDL
+from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.sunnypilot.modeld_v2.blendful import LANE_WIDTH_CLIP, LOOKAHEAD_TIME, MIN_LOOKAHEAD
+from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.shader_polygon import draw_polygon
+from openpilot.system.ui.lib.text_measure import measure_text_cached
+
+BLENDFUL_COLOR = (0, 200, 255)
+FULL_BAR = 1.0
+
+
+class BlendfulRenderer:
+  def __init__(self, readout: bool = True):
+    self._readout = readout
+    self._center_points = np.empty((0, 2), dtype=np.float32)
+    self._trust = 0.0
+    self._font = gui_app.font(FontWeight.BOLD)
+    self._pull_display = FirstOrderFilter(0.0, 0.5, DT_MDL)
+    self._trust_display = FirstOrderFilter(0.0, 0.5, DT_MDL)
+    self._alpha = FirstOrderFilter(0.0, 0.3, DT_MDL)
+
+  def update(self, renderer, max_idx: int, *map_args) -> None:
+    blendful = ui_state.sm['modelDataV2SP']
+    if ui_state.sm.updated['modelDataV2SP']:
+      self._alpha.update(float(blendful.blendfulTrust > 0.0))
+      if blendful.blendfulTrust > 0.0:
+        self._trust = blendful.blendfulTrust
+      if self._readout:
+        lookahead = max(ui_state.sm['carState'].vEgo * LOOKAHEAD_TIME, MIN_LOOKAHEAD)
+        self._pull_display.update(blendful.blendfulCurvature * lookahead ** 2 / 2)
+        self._trust_display.update(self._trust)
+
+    left, right = renderer._lane_lines[1].raw_points, renderer._lane_lines[2].raw_points
+    stds = list(ui_state.sm['modelV2'].laneLineStds)
+    if self._alpha.x < 0.01 or len(left) == 0 or len(right) != len(left) or len(stds) < 3:
+      self._center_points = np.empty((0, 2), dtype=np.float32)
+      return
+
+    if blendful.blendfulTrust > 0.0:
+      l_prob, r_prob = blendful.blendfulLeftProb, blendful.blendfulRightProb
+      half_width = np.clip(right[:, 1] - left[:, 1], *LANE_WIDTH_CLIP) / 2 if l_prob * r_prob > 0.5 else blendful.blendfulLaneWidth / 2
+      l_var = stds[1] ** 2 / max(l_prob, 1e-4)
+      r_var = stds[2] ** 2 / max(r_prob, 1e-4)
+      center = left.copy()
+      center[:, 1] = (r_var * (left[:, 1] + half_width) + l_var * (right[:, 1] - half_width)) / (l_var + r_var)
+      self._center_points = renderer._map_line_to_polygon(center, 0.15, 0.0, max_idx, *map_args)
+
+  def _color(self, rgb, alpha: float) -> rl.Color:
+    return rl.Color(*rgb, int(alpha * self._alpha.x))
+
+  def draw(self, rect: rl.Rectangle) -> None:
+    if self._center_points.size and self._trust > 0.05:
+      draw_polygon(rect, self._center_points, self._color(BLENDFUL_COLOR, np.clip(self._trust, 0.2, 1.0) * 255))
+    if self._center_points.size and self._readout:
+      self._draw_readout(rect)
+
+  def _draw_readout(self, rect: rl.Rectangle) -> None:
+    pull, trust = self._pull_display.x, self._trust_display.x
+    w, h = 190, 76
+    x, y = rect.x + (rect.width - w) / 2, rect.y + 10
+    cx, cy = x + w / 2, y + 30
+    rl.draw_rectangle_rounded(rl.Rectangle(x, y, w, h), 0.5, 12, self._color((0, 0, 0), 170))
+
+    text = f"{abs(pull) * 100:.0f}"
+    text_w = measure_text_cached(self._font, text, 44, 0).x
+    rl.draw_text_ex(self._font, text, rl.Vector2(cx - text_w / 2, cy - 24), 44, 0, self._color((255, 255, 255), 255))
+
+    active = self._color(BLENDFUL_COLOR, np.clip(abs(pull) / 0.1, 0.0, 1.0) * 255)
+    idle = self._color((255, 255, 255), 40)
+    lx, rx = x + 18, x + w - 18
+    rl.draw_triangle(rl.Vector2(lx, cy), rl.Vector2(lx + 16, cy + 12), rl.Vector2(lx + 16, cy - 12), active if pull < 0 else idle)
+    rl.draw_triangle(rl.Vector2(rx - 16, cy - 12), rl.Vector2(rx - 16, cy + 12), rl.Vector2(rx, cy), active if pull > 0 else idle)
+
+    bar = rl.Rectangle(x + 24, y + h - 16, w - 48, 6)
+    rl.draw_rectangle_rounded(bar, 1.0, 6, self._color((255, 255, 255), 40))
+    rl.draw_rectangle(int(cx - 1), int(bar.y - 2), 2, int(bar.height + 4), self._color((255, 255, 255), 120))
+    fill = bar.width / 2 * float(np.sqrt(np.clip(abs(pull) / FULL_BAR, 0.0, 1.0)))
+    if fill > 1:
+      fill_x = cx if pull > 0 else cx - fill
+      rl.draw_rectangle_rounded(rl.Rectangle(fill_x, bar.y, fill, bar.height), 1.0, 6,
+                                self._color(BLENDFUL_COLOR, np.clip(0.3 + 0.7 * trust, 0.0, 1.0) * 255))
@@ -6,6 +6,7 @@ See the LICENSE.md file in the root directory for more details.
 """
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.selfdrive.ui.ui_state import ui_state, UIStatus
+from openpilot.selfdrive.ui.sunnypilot.onroad.blendful import BlendfulRenderer
 from openpilot.selfdrive.ui.sunnypilot.onroad.chevron_metrics import ChevronMetrics
 from openpilot.selfdrive.ui.sunnypilot.onroad.rainbow_path import RainbowPath
 from openpilot.selfdrive.ui.sunnypilot.ui_state import MADSState
@@ -16,6 +17,7 @@ class ModelRendererSP:
  def __init__(self):
    self.rainbow_path = RainbowPath()
    self.chevron_metrics = ChevronMetrics()
+    self.blendful = BlendfulRenderer(readout=False)
    self._width_filter = FirstOrderFilter(0.9, 0.1, 1 / gui_app.target_fps)

  @property
@@ -36,7 +36,7 @@ class UIStateSP:
    self.is_sp_release: bool = self.params.get_bool("IsReleaseSpBranch")
    self.sm_services_ext = [
      "modelManagerSP", "selfdriveStateSP", "longitudinalPlanSP", "backupManagerSP",
-      "lateralTorqueParameters", "carStateSP", "liveMapDataSP", "carParamsSP", "lateralDelay"
+      "lateralTorqueParameters", "carStateSP", "liveMapDataSP", "carParamsSP", "lateralDelay", "modelDataV2SP"
    ]

    self.sunnylink_state = SunnylinkState()
@@ -3,7 +3,3 @@ from openpilot.common.basedir import BASEDIR

 MAPD_BIN_DIR = os.path.join(BASEDIR, 'openpilot', 'third_party/mapd_pfeiferj')
 MAPD_PATH = os.path.join(MAPD_BIN_DIR, 'mapd')
-
-# mapd still runs (OSM downloads) but has no position source since ubloxd owns LastGPSPosition;
-# map-based features stay off until mapd is rebuilt
-MAPD_AVAILABLE = False
@@ -4,6 +4,7 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 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 json
 import math
 import platform

@@ -26,6 +27,21 @@ class OsmMapData(BaseMapData):
      self.last_bearing = math.degrees(location.calibratedOrientationNED.value[2])
      self.last_position = Coordinate(location.positionGeodetic.value[0], location.positionGeodetic.value[1])

+    if self.last_position is None:
+      return
+
+    params = {
+      "latitude": self.last_position.latitude,
+      "longitude": self.last_position.longitude,
+    }
+
+    if self.last_bearing is not None:
+      params['bearing'] = self.last_bearing
+
+    # mapd reads its position from the memory params as JSON, so write it for the mapd binary.
+    # LastGPSPosition is registered as BYTES (ubloxd owns the persistent copy for pigeond),
+    # so the JSON payload has to be encoded here.
+    self.mem_params.put("LastGPSPosition", json.dumps(params).encode(), block=True)

  def get_current_speed_limit(self) -> float:
    return float(self.mem_params.get("MapSpeedLimit") or 0.0)
@@ -121,6 +121,10 @@ def update_osm_db() -> None:
  if not mem_params.get("OSMDownloadBounds"):
    mem_params.put("OSMDownloadBounds", "", block=True)

+  # mapd reads LastGPSPosition from the memory params as JSON, and it is registered as BYTES upstream
+  if not mem_params.get("LastGPSPosition"):
+    mem_params.put("LastGPSPosition", b"{}", block=True)
+

 def main_thread():
  update_installed_version(VERSION, params)
@@ -0,0 +1,70 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+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 json
+import math
+import platform
+
+import openpilot.cereal.messaging as messaging
+from openpilot.cereal import log
+from openpilot.common.params import Params
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.sunnypilot.mapd.live_map_data.osm_map_data import OsmMapData
+
+
+class TestOsmMapData(OpenpilotTestCase):
+  """The mapd binary reads its position from the memory params as JSON, so mapd_manager has to feed it."""
+
+  LATITUDE = 32.875134
+  LONGITUDE = -117.209777
+  ALTITUDE = 42.0
+  BEARING = 90.0
+
+  def setup_method(self):
+    self.mem_params = Params("/dev/shm/params") if platform.system() != "Darwin" else Params()
+    self.mem_params.remove("LastGPSPosition")
+    self.map_data = OsmMapData()
+    self.pm = messaging.PubMaster(['liveLocationKalman'])
+
+  def location_message(self, status: log.LiveLocationKalman.Status, position_valid: bool):
+    msg = messaging.new_message('liveLocationKalman', valid=True)
+    location = msg.liveLocationKalman
+    location.status = status
+    location.positionGeodetic = {'value': [self.LATITUDE, self.LONGITUDE, self.ALTITUDE], 'valid': position_valid}
+    location.calibratedOrientationNED = {'value': [0.0, 0.0, math.radians(self.BEARING)], 'valid': True}
+    return msg
+
+  def send_location(self, status: log.LiveLocationKalman.Status, position_valid: bool) -> None:
+    # the first exchange synchronizes the PUB/SUB connection, the second one is actually received
+    self.pm.send('liveLocationKalman', self.location_message(status, position_valid))
+    self.map_data.sm.update(1000)
+    self.pm.send('liveLocationKalman', self.location_message(status, position_valid))
+    self.map_data.sm.update(1000)
+
+  def read_position(self) -> dict:
+    value = self.mem_params.get("LastGPSPosition")
+    self.assertIsNotNone(value, "LastGPSPosition was not written for mapd")
+    return json.loads(value)
+
+  def test_writes_position_for_mapd(self):
+    self.send_location(log.LiveLocationKalman.Status.valid, True)
+    self.map_data.tick()
+
+    position = self.read_position()
+    self.assertAlmostEqual(position['latitude'], self.LATITUDE, delta=1e-6)
+    self.assertAlmostEqual(position['longitude'], self.LONGITUDE, delta=1e-6)
+    self.assertAlmostEqual(position['bearing'], self.BEARING, delta=1e-6)
+
+  def test_invalid_localizer_keeps_last_known_position(self):
+    self.send_location(log.LiveLocationKalman.Status.valid, True)
+    self.map_data.tick()
+
+    self.send_location(log.LiveLocationKalman.Status.uninitialized, False)
+    self.map_data.tick()
+
+    position = self.read_position()
+    self.assertAlmostEqual(position['latitude'], self.LATITUDE, delta=1e-6)
+    self.assertAlmostEqual(position['longitude'], self.LONGITUDE, delta=1e-6)
@@ -0,0 +1,138 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+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
+
+from openpilot.common.filter_simple import FirstOrderFilter
+from openpilot.common.realtime import DT_MDL
+from openpilot.sunnypilot.modeld_v2.constants import ModelConstants
+
+LANE_WIDTH_DEFAULT = 3.6  # m
+LANE_WIDTH_CLIP = (2.8, 4.5)  # m
+LOOKAHEAD_TIME = 1.5  # s
+MIN_LOOKAHEAD = 10.0  # m
+MIN_SPEED = 5.0  # m/s
+LINE_STD = (0.2, 0.6)
+POINT_STD = 0.1
+YIELD = (0.2, 0.45)
+X_IDXS = np.array(ModelConstants.X_IDXS)
+
+
+class Blendful:
+  def __init__(self):
+    self.lane_width = FirstOrderFilter(LANE_WIDTH_DEFAULT, 10.0, DT_MDL, initialized=False)
+    self.line_gone = FirstOrderFilter(np.zeros(2), 2.0, DT_MDL)
+    self.line_probs_slow = FirstOrderFilter(np.zeros(2), 3.0, DT_MDL)
+    self.line_probs = FirstOrderFilter(np.zeros(2), 0.5, DT_MDL)
+    self.usual_offset = FirstOrderFilter(0.0, 10.0, DT_MDL, initialized=False)
+    self.going_around = False
+    self.since_turning = 0.0
+    self.trust = 0.0
+    self.line_trust = 0.0
+    self.dk = 0.0 # delta kappa; difference between lane center and model plan
+    self.l_prob = 0.0
+    self.r_prob = 0.0
+    self.model_curvature = 0.0
+    self.smooth = 0.0 # smoothens lanelines below .53 lat accel
+    self.curvature = 0.0
+
+  def update(self, model_output: dict[str, np.ndarray], v_ego: float, active: bool, model_curvature: float) -> float:
+    self.l_prob = self.r_prob = 0.0
+    fading = not active or v_ego < MIN_SPEED
+    if fading:
+      self.trust = self.line_trust = 0.0
+      self.usual_offset.initialized = False
+      self.lane_width.initialized = False
+      self.going_around = False
+    self.model_curvature = model_curvature
+    target = 0.0 if fading else self._target(model_output, v_ego, model_curvature)
+    target = self.smooth = self.smooth + (target - self.smooth) * DT_MDL / (DT_MDL + np.interp(abs(model_curvature) * v_ego ** 2, [0.18, 0.53], [0.25, 0.0]))
+    build = 0.5 / max(v_ego, 1.0) ** 2 * DT_MDL  # jerk over 1 second
+    release = (0.5 if fading else 2.0) / max(v_ego, 1.0) ** 2 * DT_MDL  # lets go fast, but past zero it builds like any other pull
+    k = self.curvature
+    self.curvature = float(np.clip(target, max(k - release, -build) if k > 0 else k - build, min(k + release, build) if k < 0 else k + build))
+    return self.curvature
+
+  def _target(self, model_output: dict[str, np.ndarray], v_ego: float, model_curvature: float) -> float:
+    lookahead = max(v_ego * LOOKAHEAD_TIME, MIN_LOOKAHEAD)
+    lines = model_output['lane_lines'][0, :, :, 0]
+    stds = model_output['lane_lines_stds'][0, :, :, 0]
+
+    lone_weight = np.interp(abs(model_curvature) * v_ego ** 2, [0.18, 0.53], [0.5, 1.0])  # 0.5 on straights, 1.0 in curves
+    probs = self.line_probs.update(model_output['lane_lines_prob'][0, 1::2][1:3])
+    absent = (probs < 0.3) & (lone_weight > 0.5)
+    gone = self.line_gone.update((model_output['lane_lines_prob'][0, 1::2][1:3] < 0.3).astype(float))
+    missing = np.where(absent, 1.0, gone)
+    dropping = bool(np.any((probs < 0.6 * self.line_probs_slow.update(model_output['lane_lines_prob'][0, 1::2][1:3])) & ~absent))
+    l_prob = float(probs[0] * np.interp(np.interp(0.5 * lookahead, X_IDXS, stds[1]), LINE_STD, [1.0, 0.0]))
+    r_prob = float(probs[1] * np.interp(np.interp(0.5 * lookahead, X_IDXS, stds[2]), LINE_STD, [1.0, 0.0]))
+    self.l_prob, self.r_prob = l_prob, r_prob
+    # one line steadily on its own still centers at lone_weight. a line that is disappearing gives control back to laneless
+    if missing[1] > 0.8 and l_prob > 0.5:
+      lane_trust = l_prob * lone_weight
+    elif missing[0] > 0.8 and r_prob > 0.5:
+      lane_trust = r_prob * lone_weight
+    elif dropping:
+      lane_trust = min(l_prob, r_prob)
+    else:
+      lane_trust = l_prob + r_prob - l_prob * r_prob
+    if lone_weight > 0.5 and lane_trust < self.line_trust:
+      lane_trust = self.line_trust + (lane_trust - self.line_trust) * DT_MDL / (lone_weight - 0.5 + DT_MDL)
+    self.line_trust = lane_trust
+    if lane_trust <= 0.0:
+      self.trust = 0.0
+      return 0.0
+    if l_prob + r_prob <= 0.0:  # keep the last fit while trust lets go
+      self.trust = min(self.trust, lane_trust)
+      return float(self.trust * self.dk)
+
+    win = (X_IDXS >= 0.5 * lookahead) & (X_IDXS <= 1.5 * lookahead)
+    x = X_IDXS[win]
+    half_width = self.lane_width.x / 2
+    if l_prob * r_prob > 0.5:
+      width = np.interp(lookahead, X_IDXS, lines[2]) - np.interp(lookahead, X_IDXS, lines[1])
+      self.lane_width.update(float(np.clip(width, *LANE_WIDTH_CLIP)))
+      half_width = np.clip(lines[2, win] - lines[1, win], *LANE_WIDTH_CLIP) / 2
+    l_var = stds[1, win] ** 2 / max(l_prob, 1e-4)
+    r_var = stds[2, win] ** 2 / max(r_prob, 1e-4)
+    center = (r_var * (lines[1, win] + half_width) + l_var * (lines[2, win] - half_width)) / (l_var + r_var)
+    weight = 1.0 / (l_var * r_var / (l_var + r_var) + POINT_STD ** 2)
+
+    # Fit curvature to place the plant in center: e ~ dk x^2 / 2
+    plan_x = np.interp(x, model_output['plan'][0, :, 0], model_output['plan'][0, :, 1])
+    plan_share = np.interp(abs(model_curvature) * lookahead ** 2 / 2, [0.5, 2.0], [0.3, 0.5]) # blending up to 50% plan with action during sharp curvature
+    error = np.clip(center - ((1 - plan_share) * model_curvature * x ** 2 / 2 + plan_share * plan_x), -1.0, 1.0)
+    dk = 2.0 * np.sum(weight * error * x ** 2) / np.sum(weight * x ** 4)
+
+    # A model planning to end up further from its usual spot in the lane than the plant is now is likely going around something
+    hw_now = np.clip(lines[2, 0] - lines[1, 0], *LANE_WIDTH_CLIP) / 2 if l_prob * r_prob > 0.5 else self.lane_width.x / 2
+    center_now = (l_prob * (lines[1, 0] + hw_now) + r_prob * (lines[2, 0] - hw_now)) / (l_prob + r_prob)
+    plan_y = np.interp(lookahead, model_output['plan'][0, :, 0], model_output['plan'][0, :, 1])
+    offset = plan_y - np.interp(lookahead, x, center)
+    if min(gone) > 0.5:  # both lines gone: turns, intersections, relearn ideal model position
+      self.usual_offset.initialized = False
+    usual = self.usual_offset.x if self.usual_offset.initialized else offset
+    swerve = abs(offset - usual) - 0.25 * abs(model_curvature) * lookahead ** 2 / 2
+    away = swerve - abs(-center_now - usual)
+    lane_curvature = 2.0 * np.polyfit(x, center, 2)[0]
+    inside_curve = abs(lane_curvature) * lookahead ** 2 / 2 > 0.1 and (offset - usual) * lane_curvature > 0
+    self.since_turning = 0.0 if abs(model_curvature) * lookahead ** 2 / 2 > 0.5 else self.since_turning + DT_MDL
+    if inside_curve:
+      self.going_around = False
+    elif away > YIELD[0] and self.since_turning > 2.0:
+      self.going_around = True
+    elif swerve < YIELD[0] / 2:
+      self.going_around = False
+    self.usual_offset.update_alpha(20.0 if self.going_around else 10.0)
+    self.usual_offset.update(offset)
+    if inside_curve:
+      lane_trust *= np.interp(abs(offset) - abs(center_now) - 0.25 * abs(model_curvature) * lookahead ** 2 / 2, (0.5, 1.0), [1.0, 0.0])
+    else:
+      lane_trust *= np.interp(swerve, (YIELD[0] / 2, YIELD[0]), [1.0, 0.0]) if self.going_around else np.interp(away, YIELD, [1.0, 0.0])
+
+    self.trust = lane_trust if lane_trust < self.trust else self.trust + (lane_trust - self.trust) * DT_MDL / (1.5 + DT_MDL)
+    self.dk = dk
+    return float(self.trust * dk)
@@ -7,6 +7,7 @@ See the LICENSE.md file in the root directory for more details.
 """
 import argparse
 import dataclasses
+import inspect
 import itertools
 import mmap
 import re
@@ -45,6 +46,11 @@ def _address(v):
  return _root(v.src[0]), add + start, size


+def _buffer(u):
+  from tinygrad.uop.ops import Ops
+  return u.buffer if u.op is Ops.BUFFER else getattr(u.arg, "buffer", None)
+
+
 def _patched(buf, topo) -> tuple[bytearray, dict]:
  from tinygrad.uop.ops import Ops
  blob, rows = bytearray(buf.max_numel() * buf.dtype.itemsize), {}
@@ -72,7 +78,7 @@ def _evaluate(u, env):
    table, index = _root(u.src[0].src[0]), _evaluate(u.src[0].src[1], env)
    return struct.unpack_from(u.dtype.fmt, table.arg, index * u.dtype.itemsize)[0] if table.op is Ops.BINARY and index is not None else None
  if u.op in GroupOp.ALU and None not in (values := [_evaluate(x, env) for x in u.src]):
-    return exec_alu(u.op, u.dtype, values, False)
+    return exec_alu(u.op, u.dtype, values, *([False] if "truncate_output" in inspect.signature(exec_alu).parameters else []))
  return None


@@ -112,7 +118,7 @@ def convert(jit, kwargs: dict, frame: dict, target) -> tuple[dict, memoryview]:
  from tinygrad.uop.ops import Ops
  submit = jit.captured._linear.src[0].without_after
  kernels, topo = submit.arg.aux.kernels, list(jit.captured._linear.toposort(enter_calls=True))
-  allocs = {str(u.tag): u for u in topo if u.op is Ops.ALLOC and u.tag is not None}
+  allocs = {str(name): u for u in topo if u.op is Ops.ALLOC and (name := getattr(u, "tag", None) or u.arg.name) is not None}
  (commands, patched), kernargs = _patched(allocs["cmdbuf_compute_0"], topo), allocs["kernargs_compute_0"]
  argument_words, pokes = _patched(kernargs, topo)[1], _input_pokes(submit, kernargs)
  sh = {name: getattr(amd_gpu, f"reg{name}") + amd_gpu.GC_BASE__INST0_SEG0 - pm4.PACKET3_SET_SH_REG_START
@@ -158,7 +164,7 @@ def convert(jit, kwargs: dict, frame: dict, target) -> tuple[dict, memoryview]:
        args.append({"input": pokes[slot][0]})
      elif slot in argument_words:
        base, at, nbytes = _address(argument_words[slot])
-        args.append({"buffer": buffers.setdefault(base, len(buffers)), "offset": at, "nbytes": nbytes or base.arg.buffer.nbytes, "dtype": u8})
+        args.append({"buffer": buffers.setdefault(base, len(buffers)), "offset": at, "nbytes": nbytes or base.max_numel() * base.dtype.itemsize, "dtype": u8})
    outs, ins = kernel[6]
    calls.append({"kind": "program", "name": re.sub(r"\x1b\[[0-9;]*m", "", kernel[1]), "lib": programs[image_alloc], "target": dataclasses.asdict(target),
                  "signature": [[f"data{i}", i, u8, [a.get("nbytes", 1)]] for i, a in enumerate(args)], "global_size": grid, "local_size": local,
@@ -166,12 +172,13 @@ def convert(jit, kwargs: dict, frame: dict, target) -> tuple[dict, memoryview]:
    needs_init |= {args[i]["buffer"] for i in ins if "buffer" in args[i] and args[i]["buffer"] not in written}
    written |= {args[i]["buffer"] for i in outs if "buffer" in args[i]}

+  assert all(_buffer(b) is not None for b, i in buffers.items() if i in needs_init), "a kernel reads a scratch before any kernel writes it"
  names = list(jit.captured.expected_names)
  inputs = [{"slot": slot, "name": names[slot] if slot < len(names) else None, "dtype": repr(u.dtype), "numel": int(u.max_numel()), "device": u.device}
            for slot, u in enumerate(_prepare_jit_inputs((), kwargs)[0])]
  header = {"input_names": names, "calls": calls, "returns": {"kind": "NoneType", "tensors": []}, "inputs": inputs,
-            "buffers": [{"nbytes": b.arg.buffer.nbytes, "device": b.arg.buffer.device, "dtype": u8}
-                        | ({"init": blob.add(b.arg.buffer.ensure_allocated().as_memoryview())} if i in needs_init else {}) for b, i in buffers.items()],
+            "buffers": [{"nbytes": bb.nbytes if (bb := _buffer(b)) else b.max_numel() * b.dtype.itemsize, "device": bb.device if bb else b.device, "dtype": u8}
+                        | ({"init": blob.add(bb.ensure_allocated().as_memoryview())} if i in needs_init else {}) for b, i in buffers.items()],
            "check": {"inputs": [[path, store(array), device] for path, array, device in frame["inputs"]],
                      "outputs": [store(array) for array in frame["outputs"]], "output_container": frame["output_container"]}}
  with sink:
@@ -250,6 +250,12 @@ def _allocate_buffers(header: dict, blob: memoryview, device_map: dict | None, s
  return buffers


+def _fields(what, /, **values):  # a tinygrad dataclass built or replaced with the fields it has today: a dropped field is fine, a new required one is not
+  known = {field.name for field in dataclasses.fields(what)}
+  values = {name: value for name, value in values.items() if name in known}
+  return what(**values) if isinstance(what, type) else dataclasses.replace(what, **values)
+
+
 def _program_uop(call: dict, lib: bytes):
  from tinygrad.helpers import Target
  from tinygrad.uop.ops import KernelInfo, Ops, ProgramInfo, UOp
@@ -257,9 +263,9 @@ def _program_uop(call: dict, lib: bytes):
  for name, compact_slot, dtype, shape in call["signature"]:
    parameter = UOp.param(call["globals"][compact_slot], _dtype(dtype), math.prod(shape))
    image = (shape[0], shape[1]) if len(shape) == 3 and shape[2] == 4 else None
-    parameters.append(parameter.replace(arg=dataclasses.replace(parameter.arg, name=name, image=image)))
-  info = ProgramInfo(global_size=tuple(call["global_size"]), local_size=tuple(call["local_size"]), vars=(), globals=tuple(call["globals"]),
-                     outs=tuple(call["outs"]), ins=tuple(call["ins"]), target=Target(**call["target"]))
+    parameters.append(parameter.replace(arg=_fields(parameter.arg, name=name, image=image)))
+  info = _fields(ProgramInfo, global_size=tuple(call["global_size"]), local_size=tuple(call["local_size"]), globals=tuple(call["globals"]),
+                 outs=tuple(call["outs"]), ins=tuple(call["ins"]), target=_fields(Target, **call["target"]))
  return UOp(Ops.PROGRAM, src=(UOp(Ops.SINK, arg=KernelInfo(name=call["name"])), UOp(Ops.LINEAR, src=tuple(parameters)),
                               UOp(Ops.SOURCE, arg=""), UOp(Ops.BINARY, arg=lib)), arg=info)

@@ -1,79 +0,0 @@
-"""
-Copyright (c) 2021-, sunnypilot, and a number of other contributors.
-
-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.
-
-Laneful: nudge the model's curvature toward the lane center seen by the lane lines.
-The model stays in charge; this only adds a pure-pursuit correction weighted by lane line confidence,
-and fades to zero (plain laneless) when the lines are weak.
-"""
-import numpy as np
-
-from openpilot.common.filter_simple import FirstOrderFilter
-from openpilot.common.realtime import DT_MDL
-from openpilot.sunnypilot.modeld_v2.constants import ModelConstants, Plan
-
-LANE_WIDTH_DEFAULT = 3.7  # m
-LANE_WIDTH_CLIP = (2.8, 4.5)  # m
-LOOKAHEAD_TIME = 1.5  # s
-MIN_LOOKAHEAD = 10.0  # m
-MAX_ERROR = 0.5  # m, cap on how far laneful can pull
-MIN_SPEED = 9.0  # m/s
-
-
-class Laneful:
-  def __init__(self):
-    self.lane_width = FirstOrderFilter(LANE_WIDTH_DEFAULT, 10.0, DT_MDL)
-
-  def update(self, model_output: dict[str, np.ndarray], v_ego: float, strength: float, desire_active: bool) -> float:
-    """Returns a curvature offset to add to the model's raw desired curvature."""
-    if strength <= 0.0 or desire_active or v_ego < MIN_SPEED or 'lane_lines' not in model_output:
-      return 0.0
-
-    lookahead = max(v_ego * LOOKAHEAD_TIME, MIN_LOOKAHEAD)
-    lines = model_output['lane_lines'][0, :, :, 0]
-    left_y = np.interp(lookahead, ModelConstants.X_IDXS, lines[1])
-    right_y = np.interp(lookahead, ModelConstants.X_IDXS, lines[2])
-
-    # line confidence, discounted when the model is unsure where the line is
-    probs = model_output['lane_lines_prob'][0, 1::2]
-    stds = model_output['lane_lines_stds'][0, :, 0, 0]
-    l_prob = float(probs[1] * np.interp(stds[1], [0.15, 0.3], [1.0, 0.0]))
-    r_prob = float(probs[2] * np.interp(stds[2], [0.15, 0.3], [1.0, 0.0]))
-
-    if l_prob * r_prob > 0.5:
-      self.lane_width.update(float(np.clip(right_y - left_y, *LANE_WIDTH_CLIP)))
-    half_width = self.lane_width.x / 2
-
-    # one weak line -> hug the strong one at half a lane width
-    center_y = (l_prob * (left_y + half_width) + r_prob * (right_y - half_width)) / (l_prob + r_prob + 1e-4)
-    lane_trust = l_prob + r_prob - l_prob * r_prob
-
-    plan = model_output['plan'][0, :, Plan.POSITION]
-    plan_y = np.interp(lookahead, plan[:, 0], plan[:, 1])
-
-    error = np.clip(center_y - plan_y, -MAX_ERROR, MAX_ERROR)
-    return float(strength * lane_trust * 2.0 * error / lookahead ** 2)
-
-
-if __name__ == "__main__":
-  def fake_output(left_y, right_y, prob=0.9, std=0.1, plan_y=0.0):
-    x = np.array(ModelConstants.X_IDXS)
-    lines = np.zeros((1, 4, len(x), 2), dtype=np.float32)
-    lines[0, 1, :, 0], lines[0, 2, :, 0] = left_y, right_y
-    plan = np.zeros((1, len(x), 15), dtype=np.float32)
-    plan[0, :, 0], plan[0, :, 1] = x, plan_y
-    return {'lane_lines': lines, 'plan': plan,
-            'lane_lines_prob': np.full((1, 8), prob, dtype=np.float32),
-            'lane_lines_stds': np.full((1, 4, len(x), 2), std, dtype=np.float32)}
-
-  lf = Laneful()
-  assert abs(lf.update(fake_output(-1.85, 1.85), 25.0, 1.0, False)) < 1e-6, "centered -> no nudge"
-  assert lf.update(fake_output(-1.0, 2.7), 25.0, 1.0, False) > 0, "lane center to the +y side -> nudge toward +y"
-  assert lf.update(fake_output(-2.7, 1.0), 25.0, 1.0, False) < 0, "lane center to the -y side -> nudge toward -y"
-  assert lf.update(fake_output(-1.0, 2.7), 25.0, 1.0, True) == 0.0, "off during lane change/turn"
-  assert lf.update(fake_output(-1.0, 2.7, std=0.5), 25.0, 1.0, False) == 0.0, "blurry lines -> laneless"
-  assert lf.update(fake_output(-1.0, 2.7), 25.0, 0.0, False) == 0.0, "strength 0 -> off"
-  assert lf.update(fake_output(-1.0, 2.7), 25.0, 0.5, False) < lf.update(fake_output(-1.0, 2.7), 25.0, 1.0, False)
-  print("laneful self-check ok")
@@ -7,6 +7,7 @@ See the LICENSE.md file in the root directory for more details.
 """

 from collections.abc import Callable
+from functools import partial
 import gc
 import os
 os.environ['GMMU'] = '0'
@@ -39,7 +40,7 @@ from openpilot.selfdrive.modeld.modeld import ChestnutGpuState

 from openpilot.sunnypilot.modeld_v2.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState, get_curvature_from_output
 from openpilot.sunnypilot.modeld_v2.parse_model_outputs import Parser
-from openpilot.sunnypilot.modeld_v2.laneful import Laneful
+from openpilot.sunnypilot.modeld_v2.blendful import Blendful
 from openpilot.sunnypilot.modeld_v2.constants import ModelConstants, Plan
 from openpilot.sunnypilot.modeld_v2.meta_helper import load_meta_constants
 from openpilot.sunnypilot.modeld_v2.camera_offset_helper import CameraOffsetHelper
@@ -230,7 +231,7 @@ class ModelState(ModelStateBase):

  def get_action_from_model(self, model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action,
                            lat_action_t: float, long_action_t: float, v_ego: float,
-                            laneful_curvature: float = 0.0) -> log.ModelDataV2.Action:
+                            blendful: Callable[[float], float] | None = None) -> log.ModelDataV2.Action:
    if 'action' not in model_output:
      plan = model_output['plan'][0]
      desired_accel = get_accel_from_plan(plan[:, Plan.VELOCITY][:, 0], plan[:, Plan.ACCELERATION][:, 0], self.constants.T_IDXS,
@@ -242,7 +243,8 @@ class ModelState(ModelStateBase):
    else:
      desired_accel = model_output['action'][0, 1]
      desired_curvature = model_output['action'][0, 0] / (max(1.0, v_ego))**2
-    desired_curvature += laneful_curvature
+    if blendful is not None:
+      desired_curvature += blendful(desired_curvature)

    stop = v_ego < 0.3 and desired_accel < 0.1
    desired_accel = smooth_value(desired_accel, prev_action.desiredAcceleration, self.LONG_SMOOTH_SECONDS)
@@ -369,8 +371,8 @@ def main(demo=False):
  DH = DesireHelper()
  meta_constants = load_meta_constants()
  RELC = RoadEdgeLaneChangeController()
-  laneful = Laneful()
-  laneful_strength = 0.0
+  blendful = Blendful()
+  blendful_enabled = False

  while True:
    # Keep receiving frames until we are at least 1 frame ahead of previous extra frame
@@ -414,7 +416,7 @@ def main(demo=False):
      model.lat_delay = get_lat_delay(params, sm["lateralDelay"].lateralDelay)
      model.PLANPLUS_CONTROL = params.get("PlanplusControl", return_default=True)
      camera_offset_helper.set_offset(params.get("CameraOffset", return_default=True))
-      laneful_strength = params.get("LanefulStrength", return_default=True)
+      blendful_enabled = params.get_bool("Blendful")
    lat_delay = model.lat_delay + model.LAT_SMOOTH_SECONDS
    if sm.updated["extrinsicsCalibration"] and sm.seen['narrowRoadCameraState'] and sm.seen['deviceState']:
      device_from_calib_euler = np.array(sm["extrinsicsCalibration"].rpyCalib, dtype=np.float32)
@@ -488,9 +490,9 @@ def main(demo=False):

      if not sm['carControl'].latActive:
        prev_action.desiredCurvature = sm['controlsState'].curvature
-      laneful_curvature = laneful.update(model_output, v_ego, laneful_strength,
-                                         desire != log.Desire.none or DH.lane_change_state != log.LaneChangeState.off)
-      action = model.get_action_from_model(model_output, prev_action, lat_action_t, long_action_t, v_ego, laneful_curvature)
+      blendful_active = blendful_enabled and desire == log.Desire.none and DH.lane_change_state == log.LaneChangeState.off
+      action = model.get_action_from_model(model_output, prev_action, lat_action_t, long_action_t, v_ego,
+                                           partial(blendful.update, model_output, v_ego, blendful_active))
      prev_action = action
      fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
                     publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
@@ -507,6 +509,13 @@ def main(demo=False):
      modelv2_send.modelV2.meta.laneChangeDirection = DH.lane_change_direction
      mdv2sp_send.valid = modelv2_send.valid
      mdv2sp_send.modelDataV2SP.laneTurnDirection = DH.lane_turn_direction
+      mdv2sp_send.modelDataV2SP.blendfulCurvature = blendful.curvature
+      mdv2sp_send.modelDataV2SP.blendfulTrust = float(blendful.trust)
+      mdv2sp_send.modelDataV2SP.modelCurvature = float(blendful.model_curvature)
+      mdv2sp_send.modelDataV2SP.blendfulGoingAround = bool(blendful.going_around)
+      mdv2sp_send.modelDataV2SP.blendfulLeftProb = blendful.l_prob
+      mdv2sp_send.modelDataV2SP.blendfulRightProb = blendful.r_prob
+      mdv2sp_send.modelDataV2SP.blendfulLaneWidth = float(blendful.lane_width.x)
      drivingdata_send.drivingModelData.meta.laneChangeState = DH.lane_change_state
      drivingdata_send.drivingModelData.meta.laneChangeDirection = DH.lane_change_direction

@@ -23,7 +23,7 @@ def record_kernel_linear():
  recorded, hcq_compile, compile_linear = [], realize.hcq_compile, jit.compile_linear

  def recording_compile_linear(*args, **kwargs):
-    with mock.patch.object(realize, "hcq_compile", lambda linear, *a, **k: (recorded.append(linear), hcq_compile(linear, *a, **k))[1]):
+    with mock.patch.object(realize, "hcq_compile", lambda linear, *a, **k: (linear.src and recorded.append(linear), hcq_compile(linear, *a, **k))[1]):
      return compile_linear(*args, **kwargs)

  with mock.patch.object(jit, "compile_linear", recording_compile_linear):
@@ -38,6 +38,18 @@ def capture_frame(jit, kwargs: dict, output_container: str | None = None):
  return {"inputs": inputs, "outputs": [tensor.numpy().copy() for tensor in outputs], "output_container": output_container}, result


+def kernel_signature(ast, elf) -> list:
+  from tinygrad.dtype import AddrSpace
+  if hasattr(ast, "kernel_params"):
+    if any(p.arg.addrspace is AddrSpace.ALU for p in ast.kernel_params):
+      raise ValueError(f"{elf.name} takes a variable, which plain artifacts don't support")
+    compact = {slot: i for i, slot in enumerate(ast.arg.globals)}
+    return [[p.arg.name, compact[p.arg.slot], repr(p.dtype), [int(x) for x in p._shape]] for p in ast.kernel_params]
+  if not all(isinstance(slot, int) for _, slot, _, _ in elf.signature):
+    raise ValueError("TinyELF.signature lost its slots and this tinygrad has no UOp.kernel_params: update kernel_signature")
+  return [[name, slot, repr(dtype), [int(x) for x in shape]] for name, slot, dtype, shape in elf.signature]
+
+
 def serialize_jit(jit, kernel_linear, check: dict | None = None) -> tuple[dict, memoryview]:
  from tinygrad.uop.ops import Ops
  sink = tempfile.TemporaryFile(dir=".")
@@ -51,6 +63,12 @@ def serialize_jit(jit, kernel_linear, check: dict | None = None) -> tuple[dict,
    if uop.op is Ops.PARAM:
      input_specs.setdefault(uop.arg.slot, {"dtype": repr(uop.dtype), "numel": int(uop.max_numel()), "device": uop.device})
      return {"input": uop.arg.slot}
+    root, offset = uop, 0
+    while root.op in (Ops.AFTER, Ops.BITCAST, Ops.SHRINK):
+      offset, root = offset + (root.src[1].arg * root.src[0].dtype.itemsize if root.op is Ops.SHRINK else 0), root.src[0]
+    if root.op is Ops.ALLOC:
+      base = bases.setdefault(id(root), (len(bases), root, root.dtype))
+      return {"buffer": base[0], "offset": offset, "nbytes": int(uop.max_numel()) * uop.dtype.itemsize, "dtype": repr(uop.dtype)}
    buffer = uop.buffer
    root = buffer._base if buffer._base is not None else buffer
    base = bases.setdefault(id(root), (len(bases), root, uop.base.dtype if buffer._base is None else uop.dtype))
@@ -63,7 +81,7 @@ def serialize_jit(jit, kernel_linear, check: dict | None = None) -> tuple[dict,
      elf, info = ast.to_elf(), ast.arg
      global_size, local_size = info.launch_dims({})
      calls.append({"kind": "program", "name": elf.name, "lib": blob.add(bytes(elf.lib)), "target": dataclasses.asdict(elf.target),
-                    "signature": [[name, slot, repr(dtype), [int(x) for x in shape]] for name, slot, dtype, shape in elf.signature],
+                    "signature": kernel_signature(ast, elf),
                    "global_size": [int(x) for x in global_size], "local_size": [int(x) for x in local_size],
                    "globals": list(info.globals), "outs": list(info.outs), "ins": list(info.ins), "args": arguments})
      outs, ins = info.outs, info.ins
@@ -77,7 +95,9 @@ def serialize_jit(jit, kernel_linear, check: dict | None = None) -> tuple[dict,

  ret = jit.captured.ret
  returns = {"kind": type(ret).__name__, "tensors": [describe(t.uop.base) | {"shape": [int(x) for x in t.shape]} for t in flatten(ret)]}
-  buffers = [{"nbytes": base.nbytes, "device": base.device, "dtype": repr(dtype)}
+  from tinygrad.device import Buffer
+  assert not [base for index, base, _ in bases.values() if index in needs_init and not isinstance(base, Buffer)], "a kernel reads a scratch before writing it"
+  buffers = [{"nbytes": base.nbytes if isinstance(base, Buffer) else int(base.max_numel()) * dtype.itemsize, "device": base.device, "dtype": repr(dtype)}
             | ({"init": blob.add(base.as_memoryview())} if index in needs_init else {}) for index, base, dtype in bases.values()]
  names = list(jit.captured.expected_names)
  if check is not None:
@@ -0,0 +1,121 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+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 os
+import re
+import sys
+import tempfile
+import unittest
+from unittest import mock
+import numpy as np
+
+os.environ.setdefault("CHECK_OOB", "0")
+os.environ.setdefault("GMMU", "0")
+if sys.platform == "darwin" and os.environ.get("DEV", "").startswith("MOCKUSB"):  # the mock's VRAM is a memfd, which macOS lacks: an unlinked file is the same
+  from tinygrad.runtime.autogen import libc
+
+  def _memfd_create(name, flags):
+    fd, path = tempfile.mkstemp()
+    os.unlink(path)
+    return fd
+  libc.memfd_create = _memfd_create
+
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.sunnypilot.modeld_v2 import convert_upstream_pkl
+from openpilot.sunnypilot.modeld_v2.convert_upstream_pkl import convert
+from openpilot.sunnypilot.modeld_v2.helpers import PlainJit, load_model
+from openpilot.sunnypilot.modeld_v2.plain_artifact_compiler import capture_frame
+
+IMG, DESIRE, STATE, OUT = (6, 8, 8), (8,), (4, 16), (1, 32)
+
+
+class TestConvertUpstreamPkl(OpenpilotTestCase):
+  @classmethod
+  def setUpClass(cls):
+    super().setUpClass()
+    if not os.environ.get("TINYGRAD_TESTS"):
+      raise unittest.SkipTest("TINYGRAD_TESTS not set. skipping converter test")
+    from tinygrad import Device, Tensor
+    assert Device.DEFAULT == "AMD" and getattr(Device["AMD"], "is_usb", False), f"{Device.DEFAULT} is not an AMD device behind the USB bridge"
+    assert (Tensor([1, 2, 3]) * 2).tolist() == [2, 4, 6]
+    cls.tmp = tempfile.TemporaryDirectory()
+    cls.rng = np.random.default_rng(0)
+    cls.weights = Tensor(cls.rng.standard_normal((16, 32)).astype(np.float32)).realize()
+    cls.bias = Tensor(cls.rng.standard_normal((1, 32)).astype(np.float32)).realize()
+    cls.input_specs = {"input_imgs": (IMG, "uint8", Device.DEFAULT), "desire": (DESIRE, "float32", Device.DEFAULT),
+                       "features": (STATE, "float32", Device.DEFAULT)}
+    cls.output_specs = {"outputs": (OUT, "float32", Device.DEFAULT), "next_features": (STATE, "float32", Device.DEFAULT)}
+
+  @classmethod
+  def tearDownClass(cls):
+    cls.tmp.cleanup()
+    super().tearDownClass()
+
+  def model(self, input_imgs, desire, features, output_buffers):
+    from tinygrad import Tensor
+    feat = features.mean(axis=0).reshape(1, 16) + input_imgs.float().mean() + desire.sum()
+    Tensor.realize(output_buffers["outputs"].assign((feat @ self.weights + self.bias).relu()),
+                   output_buffers["next_features"].assign(features[1:].cat(feat * 2)))
+
+  def inputs(self, seed: int) -> dict:
+    from examples.openpilot.helpers import allocate_inputs
+    rng = np.random.default_rng(seed)
+
+    def initialize(arrays: dict):
+      for value in arrays.values():
+        value[...] = rng.standard_normal(value.shape) if value.dtype.kind == "f" else rng.integers(0, 256, value.shape)
+    return allocate_inputs(self.input_specs, initialize) | {"output_buffers": allocate_inputs(self.output_specs)}
+
+  def jit(self):
+    from tinygrad import TinyJit
+    run = TinyJit(self.model, prune=True)
+    kwargs = self.inputs(1)
+    run(**kwargs)
+    run(**kwargs)
+    return run
+
+  def assert_matches_eager(self, plain, seed: int):
+    fresh, expected = self.inputs(seed), self.inputs(seed)
+    plain(**fresh)
+    self.model(**expected)
+    for name in self.output_specs:
+      assert np.array_equal(fresh["output_buffers"][name].numpy(), expected["output_buffers"][name].numpy()), name
+
+  def convert(self, jit) -> tuple[dict, memoryview]:
+    from tinygrad import Device
+    kwargs = self.inputs(2)
+    frame, _ = capture_frame(jit, kwargs, "output_buffers")
+    header, blob = convert(jit, kwargs, frame, Device[Device.DEFAULT].renderer.target)
+    kernels = jit.captured._linear.src[0].without_after.arg.aux.kernels
+    assert [call["name"] for call in header["calls"]] == [re.sub(r"\x1b\[[0-9;]*m", "", kernel[1]) for kernel in kernels]
+    assert all(re.fullmatch(r"\w+", call["name"]) for call in header["calls"]), "kernel names: failure point 1"
+    assert [(tuple(call["outs"]), tuple(call["ins"])) for call in header["calls"]] == [tuple(kernel[6]) for kernel in kernels], "outs/ins: failure point 1"
+    bound = {argument["input"] for call in header["calls"] for argument in call["args"] if "input" in argument}
+    assert bound == {spec["slot"] for spec in header["inputs"]}, f"input slots bound by pokes {sorted(bound)}: failure point 4"
+    assert [spec["name"] for spec in header["inputs"]][:len(self.input_specs)] == sorted(self.input_specs)
+    return header, blob
+
+  def test_converted_jit_matches_eager(self):  # the submit decoded into plain calls, replayed against its own frame
+    jit = self.jit()
+    plain = PlainJit(*self.convert(jit))
+    self.assert_matches_eager(plain, 3)
+    self.assert_matches_eager(plain, 4)
+
+  def test_pickle_round_trip_through_main(self):
+    from examples.openpilot.helpers import dump_pickle, load_pickle
+    from tinygrad.engine.realize import lower_and_compile
+    pkl, out = os.path.join(self.tmp.name, "tiny_tinygrad.pkl"), os.path.join(self.tmp.name, "tiny_plain.pkl")
+    dump_pickle({"run": self.jit(), "input_specs": self.input_specs, "output_specs": self.output_specs, "metadata": {"name": "tiny"}}, pkl)
+
+    artifact = load_pickle(pkl, out_of_band=True)
+    artifact["run"].captured._linear = lower_and_compile(artifact["run"].captured._linear)
+    self.assert_matches_eager(PlainJit(*self.convert(artifact["run"])), 5)
+
+    with mock.patch.object(sys, "argv", ["convert_upstream_pkl", pkl, out]):
+      convert_upstream_pkl.main()
+    bundle = load_model(out, cache=False, verify=True)
+    assert bundle["metadata"] == {"name": "tiny"} and bundle["input_specs"] == self.input_specs and bundle["output_specs"] == self.output_specs
+    self.assert_matches_eager(bundle["run"], 6)
@@ -0,0 +1,162 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+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 dataclasses
+import functools
+import inspect
+import os
+import sys
+import tempfile
+from unittest import mock
+import numpy as np
+import unittest
+
+import openpilot.sunnypilot.modeld_v2.helpers as helpers
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.sunnypilot.modeld_v2 import compile_warp
+from openpilot.sunnypilot.modeld_v2.frame_fusion import frame_part, pack_layout
+from openpilot.sunnypilot.modeld_v2.helpers import PlainJit, cache_is_fresh, load_model, read_parts, write_bundle
+from openpilot.sunnypilot.modeld_v2.plain_artifact_compiler import capture_frame, record_kernel_linear, serialize_jit
+
+CAM_W, CAM_H, MODEL_W, MODEL_H = 32, 16, 16, 8
+FRAME = f"{CAM_W},{CAM_H},{CAM_W},{CAM_H},{CAM_H // 2},{CAM_W * CAM_H * 3 // 2}"
+FRAME_SIZE = CAM_W * CAM_H * 3 // 2
+HOST = {"desire": (8,), "traffic_convention": (2,)}
+STATE, OUT = (4, 16), (1, 32)
+
+
+def compile_jit(fn, inputs: dict, output_container: str | None = None) -> tuple[dict, memoryview]:
+  from tinygrad import TinyJit
+  run = TinyJit(fn, prune=True)
+  with record_kernel_linear() as recorded:
+    run(**inputs)
+    run(**inputs)
+    check, _ = capture_frame(run, inputs, output_container)
+  assert len(recorded) == 1, f"expected one captured kernel list, got {len(recorded)}"
+  return serialize_jit(run, recorded[0], check)
+
+
+class TestPlainArtifact(OpenpilotTestCase):
+  @classmethod
+  def setUpClass(cls):
+    super().setUpClass()
+    if not os.environ.get("TINYGRAD_TESTS"):
+      raise unittest.SkipTest("TINYGRAD_TESTS env var not set, skipping artifact test.")
+    from tinygrad import Tensor
+    cls.tmp = tempfile.TemporaryDirectory()
+    cls.rng = np.random.default_rng(0)
+    cls.weights = Tensor(cls.rng.standard_normal((16, 32)).astype(np.float32)).realize()
+    cls.bias = Tensor(cls.rng.standard_normal((1, 32)).astype(np.float32)).realize()
+
+  @classmethod
+  def tearDownClass(cls):
+    cls.tmp.cleanup()
+    super().tearDownClass()
+
+  def model(self, x, h):  # a two input, one weight model: the shape of a policy without the size
+    return ((x @ self.weights + self.bias).relu() + h.mean()).contiguous()
+
+  def tensors(self, seed: int):
+    from tinygrad import Tensor
+    rng = np.random.default_rng(seed)
+    return {"x": Tensor(rng.standard_normal((1, 16)).astype(np.float32)).realize(), "h": Tensor(rng.standard_normal((4, 16)).astype(np.float32)).realize()}
+
+  def artifact(self, name: str = "model") -> str:
+    path = os.path.join(self.tmp.name, f"{name}_tinygrad.pkl")
+    if not os.path.exists(path):
+      write_bundle(path, {"run": compile_jit(self.model, self.tensors(1))}, {"metadata": {"name": name}})
+    return path
+
+  def test_round_trip_matches_jit(self):  # compiler -> bundle -> PlainJit, replay verified, then fresh inputs bit exact with eager tinygrad
+    bundle = load_model(self.artifact(), cache=False, verify=True)
+    assert bundle["metadata"] == {"name": "model"} and isinstance(bundle["run"], PlainJit)
+    fresh = self.tensors(2)
+    assert np.array_equal(bundle["run"](**fresh).numpy(), self.model(**fresh).numpy())
+
+  def test_replay_check_catches_a_changed_kernel(self):
+    parts, extras = read_parts(self.artifact())
+    header, blob = parts["run"]
+    poisoned = dict(header, check=dict(header["check"], outputs=[header["check"]["inputs"][0][1]]))
+    with self.assertRaises(helpers.ArtifactMismatch):
+      PlainJit(poisoned, blob)
+
+  def test_cache_round_trip_holds_no_weights_and_is_rebuilt_when_stale(self):
+    path = self.artifact("cached")
+    expected = load_model(path, cache=False, verify=False)["run"](**self.tensors(3)).numpy()
+    load_model(path)
+    assert cache_is_fresh(path)
+    with open(f"{path}.cache", "rb") as file:
+      cache = file.read()
+    assert self.weights.numpy().tobytes() not in cache and len(cache) < os.path.getsize(path)
+    with mock.patch.object(helpers, "PlainJit", side_effect=AssertionError("a fresh cache must not rebuild")):
+      cached = load_model(path)
+    assert np.array_equal(cached["run"](**self.tensors(3)).numpy(), expected)
+    with mock.patch.object(helpers, "tinygrad_identity", return_value="another tinygrad"):
+      assert not cache_is_fresh(path)
+      assert isinstance(load_model(path)["run"], PlainJit)
+      assert cache_is_fresh(path)
+    assert not cache_is_fresh(path)  # keyed on the tinygrad that wrote it, so the next boot after a bump rebuilds once
+    os.utime(path)
+    with mock.patch.object(helpers, "tinygrad_identity", return_value="another tinygrad"):
+      assert not cache_is_fresh(path)
+
+  def test_fused_with_warp_matches_warp_then_model(self):
+    from tinygrad import Tensor
+    warp_path = os.path.join(self.tmp.name, "warp_tinygrad.pkl")
+    with mock.patch.object(sys, "argv", ["compile_warp", "--frame", FRAME, "--warp-to", f"{MODEL_W}x{MODEL_H}", "--output", warp_path]):
+      compile_warp.main()
+    warp = load_model(warp_path, cache=False)["run"]
+
+    def native(new_img, desire, traffic_convention, state_feat_q, output_buffers):
+      feat = state_feat_q.mean(axis=0).reshape(1, 16) + new_img.float().mean() + desire.sum() + traffic_convention[0]
+      Tensor.realize(output_buffers["outputs"].assign((feat @ self.weights + self.bias).relu()),
+                     output_buffers["next_state_feat_q"].assign(state_feat_q[1:].cat(feat * 2)))
+
+    def model_inputs(new_img):
+      return {"new_img": new_img} | {name: Tensor(np.ones(shape, np.float32) * 0.5).realize() for name, shape in HOST.items()} | \
+             {"state_feat_q": Tensor(self.rng.standard_normal(STATE).astype(np.float32)).realize(),
+              "output_buffers": {"outputs": Tensor.zeros(OUT).contiguous().realize(), "next_state_feat_q": Tensor.zeros(STATE).contiguous().realize()}}
+    frames = Tensor(self.rng.integers(0, 256, (2, FRAME_SIZE), dtype=np.uint8)).realize()
+    tfm = Tensor(np.tile(np.eye(3, dtype=np.float32), (2, 1, 1))).realize()
+    path = os.path.join(self.tmp.name, "native_tinygrad.pkl")
+    part = compile_jit(native, model_inputs(warp(input_frame=frames, M_inv=tfm).realize()), "output_buffers")
+    extras = {"input_specs": {"new_img": ((2, 6, MODEL_H // 2, MODEL_W // 2), "|u1", "CPU"), "state_feat_q": (STATE, "<f4", "CPU")}
+              | {name: (shape, "<f4", "CPU") for name, shape in HOST.items()},
+              "output_specs": {"outputs": (OUT, "<f4", "CPU"), "next_state_feat_q": (STATE, "<f4", "CPU")},
+              "metadata": {"output_shapes": {"outputs": OUT, "next_state_feat_q": STATE}}}
+    write_bundle(path, {"run": part}, extras)
+
+    fused = load_model(path, cache=False, extend=functools.partial(frame_part, warp_path))
+    assert fused["run"].input_names == ["host", "state_feat_q"]
+    offsets, packed = pack_layout(HOST, FRAME_SIZE)
+    host = np.zeros(packed, np.uint8)
+    inputs = model_inputs(None)
+    for name, shape in ({"tfm": (2, 3, 3)} | HOST).items():
+      np.ndarray(shape, np.float32, host, offsets[name])[...] = tfm.numpy() if name == "tfm" else inputs[name].numpy()
+    host[offsets["frames"]:] = frames.numpy().ravel()
+    fused["run"](host=Tensor(host, device="NPY"), state_feat_q=inputs["state_feat_q"], output_buffers=inputs["output_buffers"])
+
+    expected = model_inputs(warp(input_frame=frames, M_inv=tfm).realize()) | {k: inputs[k] for k in ("state_feat_q",)}
+    native(**expected)
+    for name in ("outputs", "next_state_feat_q"):
+      assert np.array_equal(inputs["output_buffers"][name].numpy(), expected["output_buffers"][name].numpy()), name
+
+  def test_tinygrad_api_the_loader_reads(self):
+    import tinygrad.engine.jit as jit
+    from tinygrad.device import Buffer, TinyELF
+    from tinygrad.helpers import Target
+    from tinygrad.uop.ops import ParamArg, ProgramInfo, UOp
+    fields = {cls: {f.name for f in dataclasses.fields(cls)} for cls in (ProgramInfo, ParamArg, Target)}
+    assert fields[ProgramInfo] >= {"global_size", "local_size", "globals", "outs", "ins", "target"}, "ProgramInfo changed: update helpers._program_uop"
+    assert fields[ParamArg] >= {"slot", "dtype", "name", "image"}, "ParamArg changed: update helpers._program_uop"
+    assert fields[Target] >= {"device", "renderer", "arch"}, "Target changed: update the 'target' key in plain_artifact_compiler.serialize_jit"
+    assert "signature" in getattr(TinyELF, "__annotations__", {}) or hasattr(UOp, "kernel_params"), \
+      "kernel signatures moved: update plain_artifact_compiler.serialize_jit"
+    assert callable(getattr(UOp, "param", None)) and callable(getattr(UOp, "from_buffer", None)), "UOp.param/from_buffer: update helpers.PlainJit"
+    assert callable(getattr(UOp, "store_call", None)) and callable(getattr(UOp, "call", None)), "UOp.call/store_call: update helpers.PlainJit"
+    assert callable(getattr(Buffer, "view", None)) and callable(getattr(Buffer, "ensure_allocated", None)), "Buffer.view: update helpers._upload"
+    assert callable(getattr(jit, "compile_linear", None)) and callable(getattr(jit, "_prepare_jit_inputs", None)), "engine.jit: update helpers._Jit"
+    assert "expected_names" in inspect.signature(jit.CapturedJit).parameters, "CapturedJit: update helpers.PlainJit and plain_artifact_compiler.serialize_jit"
@@ -22,7 +22,7 @@ DEFAULT_MODEL_NAME_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "mode
 MODEL_HASH_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "models", "tests", "model_hash")
 BIG_MODEL_HASH_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "models", "tests", "big_model_hash")
 SUPERCOMBO_ONNX_PATH = os.path.join(BASEDIR, "openpilot", "selfdrive", "modeld", "models", "driving_supercombo.onnx")
-BIG_SUPERCOMBO_ONNX_PATH = os.path.join(BASEDIR, "openpilot", "selfdrive", "modeld", "models", "big_driving_supercombo.onnx")
+BIG_DRIVING_PKL_PATH = os.path.join(BASEDIR, "openpilot", "selfdrive", "modeld", "models", "big_driving_tinygrad.pkl")


 def _read_model_name_fields():
@@ -47,18 +47,17 @@ def update_model_hash():

  print(f"Generated and updated new combined model hash to {MODEL_HASH_PATH}")

-  if os.path.exists(BIG_SUPERCOMBO_ONNX_PATH):
-    import subprocess
-    rel = os.path.relpath(BIG_SUPERCOMBO_ONNX_PATH, os.getcwd())
-    pointer = subprocess.check_output(["git", "show", f"HEAD:{rel}"], text=True)
-    oid = next(l.split(":", 1)[1] for l in pointer.splitlines() if l.startswith("oid sha256:"))
-    big_fingerprint = f"{oid}:{fields.get('DEFAULT_BIG_MODEL', '')}:{fields.get('DEFAULT_BIG_MODEL_REF', '')}"
-    big_combined_hash = hashlib.sha256(big_fingerprint.encode()).hexdigest()
+  import subprocess
+  rel = os.path.relpath(BIG_DRIVING_PKL_PATH, os.getcwd())
+  pointer = subprocess.check_output(["git", "show", f"HEAD:{rel}"], text=True)
+  oid = next(l.split(":", 1)[1] for l in pointer.splitlines() if l.startswith("oid sha256:"))
+  big_fingerprint = f"{oid}:{fields.get('DEFAULT_BIG_MODEL', '')}:{fields.get('DEFAULT_BIG_MODEL_REF', '')}"
+  big_combined_hash = hashlib.sha256(big_fingerprint.encode()).hexdigest()

-    with open(BIG_MODEL_HASH_PATH, "w") as f:
-      f.write(big_combined_hash)
+  with open(BIG_MODEL_HASH_PATH, "w") as f:
+    f.write(big_combined_hash)

-    print(f"Generated and updated new big model hash to {BIG_MODEL_HASH_PATH}")
+  print(f"Generated and updated new big model hash to {BIG_MODEL_HASH_PATH}")


 def get_ref_for_name(url: str, name: str) -> str:
@@ -7,7 +7,10 @@ See the LICENSE.md file in the root directory for more details.

 import asyncio
 import os
+import re
+import threading
 import time
+from concurrent.futures import ThreadPoolExecutor

 import requests
 from openpilot.common.params import Params
@@ -22,12 +25,101 @@ from openpilot.sunnypilot.models.helpers import (ACTIVE_BUNDLE_KEYS, get_active_

 # (connect, read) seconds. read is per-request inactivity, not a total cap
 DOWNLOAD_TIMEOUT = (30, 30)
+# HuggingFace throttles each connection to ~1-2 MB/s but not the connection count; 12 saturates the device link
+MAX_CONCURRENT_PIECES = 12
+PIECE_SIZE = 8 * 1024 * 1024
+PIECE_ATTEMPTS = 3
+PIECE_BACKOFF = 1.0  # seconds, growing linearly: waits 1 s then 2 s between a piece's three attempts
+TRANSIENT_HTTP_STATUS = frozenset({408, 429, 500, 502, 503, 504})
+REPORT_INTERVAL = 0.5  # seconds between progress publications
+# byte ranges count encoded bytes but iter_content yields decoded ones, so ask for an unencoded body
+NO_COMPRESSION = {"Accept-Encoding": "identity"}
+SPEED_SMOOTHING = 0.7  # weight of the previous speed sample in the published speed
+SPEED_FLOOR = 0.05 * 1024 ** 2  # bytes/s; anything slower would only display as 0.0 MB/s, so it reads as no rate


 class DownloadCancelled(Exception):
  pass


+def _is_transient(e: BaseException) -> bool:
+  if isinstance(e, requests.HTTPError):
+    return e.response is not None and e.response.status_code in TRANSIENT_HTTP_STATUS
+  return isinstance(e, (requests.ConnectionError, requests.Timeout, requests.exceptions.ChunkedEncodingError))
+
+
+class _Progress:
+  def __init__(self):
+    self._bytes = 0
+    self._lock = threading.Lock()
+
+  def add_bytes(self, n: int) -> None:
+    with self._lock:
+      self._bytes += n
+
+  def snapshot(self) -> int:
+    with self._lock:
+      return self._bytes
+
+
+def _piece_ranges(total: int, piece_size: int) -> list[tuple[int, int]]:
+  return [(start, min(start + piece_size, total)) for start in range(0, total, piece_size)]
+
+
+def _prepare_target(path: str, total: int) -> None:
+  with open(path, "wb") as f:
+    f.truncate(total)
+
+
+def _content_range_total(response: requests.Response) -> int | None:
+  if response.status_code != 206:
+    return None
+  match = re.fullmatch(r"bytes \d+-\d+/(\d+)", response.headers.get("Content-Range", ""))
+  return int(match.group(1)) if match else None
+
+
+def _probe_size(url: str) -> tuple[int, bool]:
+  with requests.get(url, headers={**NO_COMPRESSION, "Range": "bytes=0-0"}, stream=True, timeout=DOWNLOAD_TIMEOUT) as response:
+    response.raise_for_status()
+    total = _content_range_total(response)
+    if total is not None:
+      return total, True
+    return int(response.headers.get("Content-Length", 0)), False
+
+
+def _fetch_piece(url: str, path: str, index: int, start: int, end: int | None, progress: _Progress,
+                 cancel: threading.Event, block_size: int) -> None:
+  headers = {**NO_COMPRESSION, "Range": f"bytes={start}-{end - 1}"} if end is not None else NO_COMPRESSION
+  label = f"{os.path.basename(path)} piece {index}"
+  for attempt in range(PIECE_ATTEMPTS):
+    written = 0
+    try:
+      with requests.get(url, headers=headers, stream=True, timeout=DOWNLOAD_TIMEOUT) as response:
+        response.raise_for_status()
+        if end is not None and response.status_code != 206:
+          raise ValueError(f"server ignored byte range for {label}")
+        with open(path, "r+b") as f:
+          f.seek(start)
+          for block in response.iter_content(chunk_size=block_size):
+            if cancel.is_set():
+              raise DownloadCancelled("Download cancelled")
+            f.write(block)
+            written += len(block)
+            progress.add_bytes(len(block))
+          if end is None:
+            f.truncate()  # unknown length: the body defines the file size
+          if end is not None and written != end - start:
+            raise requests.exceptions.ConnectionError(f"short read: {written} of {end - start} bytes")
+      return
+    except requests.RequestException as e:
+      progress.add_bytes(-written)  # the piece restarts from scratch
+      if not _is_transient(e) or attempt == PIECE_ATTEMPTS - 1:
+        raise
+      cloudlog.warning(f"retrying {label} after {type(e).__name__}: {e}")
+      if cancel.wait(PIECE_BACKOFF * (1 + attempt)):
+        raise DownloadCancelled("Download cancelled") from None
+
+
 class ModelManagerSP:
  """Manages model downloads and status reporting"""

@@ -41,7 +133,7 @@ class ModelManagerSP:
    self.source_models: dict[str, list[custom.ModelManagerSP.ModelBundle]] = {}
    self.selected_bundle: custom.ModelManagerSP.ModelBundle = None
    self.active_bundle: custom.ModelManagerSP.ModelBundle = get_active_bundle(self.params, chestnut=self.chestnut_present)
-    self._chunk_size = 128 * 1000  # 128 KB chunks
+    self._block_size = 128 * 1000  # 128 KB network read blocks
    self._download_start_times: dict[str, float] = {}  # Track start time per model
    self._download_ref: bytes | str | None = None

@@ -56,7 +148,6 @@ class ModelManagerSP:
    self._download_ref = None

  def _sync_artifact_progress(self, source_artifact) -> None:
-    """Mirror download progress to all artifacts sharing the same filename in the selected bundle."""
    if not self.selected_bundle:
      return
    for model in self.selected_bundle.models:
@@ -65,9 +156,9 @@ class ModelManagerSP:
        artifact.downloadProgress.status = source_artifact.downloadProgress.status
        artifact.downloadProgress.progress = source_artifact.downloadProgress.progress
        artifact.downloadProgress.eta = source_artifact.downloadProgress.eta
+        artifact.downloadProgress.speed = source_artifact.downloadProgress.speed

  def _calculate_eta(self, filename: str, progress: float) -> int:
-    """Calculate ETA based on elapsed time and current progress"""
    if filename not in self._download_start_times or progress <= 0:
      return 60  # Default ETA for new downloads

@@ -75,39 +166,74 @@ class ModelManagerSP:
    if elapsed_time <= 0:
      return 60

-    # If we're at X% after Y seconds, we can estimate total time as (Y / X) * 100
    total_estimated_time = (elapsed_time / progress) * 100
    eta = total_estimated_time - elapsed_time
-
    return max(1, int(eta))  # Return at least 1 second if download is ongoing

-  async def _download_file(self, url: str, path: str, model) -> None:
-    """Downloads a file with progress tracking"""
-    self._download_start_times[model.fileName] = time.monotonic()
+  def _set_progress(self, artifact, status, progress: float, eta: int = 0, speed: float = 0.0) -> None:
+    artifact.downloadProgress.status = status
+    artifact.downloadProgress.progress = progress
+    artifact.downloadProgress.eta = eta
+    artifact.downloadProgress.speed = speed
+    self._sync_artifact_progress(artifact)
+    self._report_status()

-    with requests.get(url, stream=True, timeout=DOWNLOAD_TIMEOUT) as response:  # noqa: ASYNC210
-      response.raise_for_status()
-      total_size = int(response.headers.get("content-length", 0))
-      bytes_downloaded = 0
+  def _publish_progress(self, artifact, done_bytes: int, total: int, speed: float) -> None:
+    # held at 99 until the file passes its hash check
+    progress = min(99.0, done_bytes / total * 100) if total > 0 else 0.0
+    if speed > 0 and total > 0:
+      eta = max(1, int((total - done_bytes) / speed))
+    else:
+      eta = self._calculate_eta(artifact.fileName, progress)
+    self._set_progress(artifact, custom.ModelManagerSP.DownloadStatus.downloading, progress, eta, speed)

-      with open(path, 'wb') as f:  # noqa: ASYNC230
-        for chunk in response.iter_content(chunk_size=self._chunk_size):  # type: bytes
-          f.write(chunk)
-          bytes_downloaded += len(chunk)
+  async def _report_until_done(self, tasks: list[asyncio.Future], artifact, progress: _Progress, total: int,
+                               started: tuple[int, float]) -> None:
+    pending = set(tasks)
+    last_bytes, last_time = started
+    speed = 0.0
+    while pending:
+      done, pending = await asyncio.wait(pending, timeout=REPORT_INTERVAL)
+      for task in done:
+        task.result()  # re-raises a worker failure
+      if self._download_interrupted():
+        raise DownloadCancelled("Download cancelled")
+      now = time.monotonic()
+      done_bytes = progress.snapshot()
+      if (dt := now - last_time) > 0:
+        instant = max(0.0, (done_bytes - last_bytes) / dt)  # bytes/s this tick; clamped since retried pieces can lower the byte count
+        speed = instant if speed == 0 else SPEED_SMOOTHING * speed + (1 - SPEED_SMOOTHING) * instant
+        if speed < SPEED_FLOOR:  # a stall decays toward 0 without reaching it, and a near-0 speed overflows the eta
+          speed = 0.0
+      last_time, last_bytes = now, done_bytes
+      self._publish_progress(artifact, done_bytes, total, speed)

-          if self._download_interrupted():
-            raise DownloadCancelled("Download cancelled")
+  async def _download_file(self, url: str, path: str, artifact) -> None:
+    self._download_start_times[artifact.fileName] = time.monotonic()
+    loop = asyncio.get_running_loop()

-          if total_size > 0:
-            progress = (bytes_downloaded / total_size) * 100
-            model.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.downloading
-            model.downloadProgress.progress = progress
-            model.downloadProgress.eta = self._calculate_eta(model.fileName, progress)
-            self._sync_artifact_progress(model)
-            self._report_status()
+    total, ranged = await loop.run_in_executor(None, _probe_size, url)
+    pieces: list[tuple[int, int | None]] = list(_piece_ranges(total, PIECE_SIZE)) if ranged else [(0, None)]
+    await loop.run_in_executor(None, _prepare_target, path, total)
+    progress = _Progress()
+    cancel = threading.Event()
+    started = progress.snapshot(), time.monotonic()  # before any worker can land bytes

-    # Clean up start time after download completes
-    del self._download_start_times[model.fileName]
+    with ThreadPoolExecutor(max_workers=MAX_CONCURRENT_PIECES) as pool:
+      tasks = [loop.run_in_executor(pool, _fetch_piece, url, path, i, start, end, progress, cancel, self._block_size)
+               for i, (start, end) in enumerate(pieces)]
+      try:
+        await self._report_until_done(tasks, artifact, progress, total, started)
+      except BaseException as e:
+        cancel.set()
+        if isinstance(e, DownloadCancelled):
+          artifact.downloadProgress.canceling = True
+          self._set_progress(artifact, custom.ModelManagerSP.DownloadStatus.downloading, artifact.downloadProgress.progress)
+        for task in tasks:
+          task.cancel()  # drops queued pieces; running ones see the event at their next block
+        await asyncio.gather(*tasks, return_exceptions=True)
+        raise
+    del self._download_start_times[artifact.fileName]

  async def _process_artifact(self, artifact, destination_path: str) -> None:
    if not artifact.downloadUri.uri:
@@ -119,33 +245,31 @@ class ModelManagerSP:
    expected_hash = artifact.downloadUri.sha256
    filename = artifact.fileName
    full_path = os.path.join(destination_path, filename)
+    status = custom.ModelManagerSP.DownloadStatus
+    artifact.downloadProgress.canceling = False

    try:
+      self._set_progress(artifact, status.verifying, 0)
      if await verify_file(full_path, expected_hash):
-        artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.cached
-        artifact.downloadProgress.progress = 100
-        artifact.downloadProgress.eta = 0
-        self._sync_artifact_progress(artifact)
-        self._report_status()
+        self._set_progress(artifact, status.cached, 100)
        return

+      self._set_progress(artifact, status.downloading, 0)
      await self._download_file(url, full_path, artifact)
+      self._set_progress(artifact, status.verifying, 99)
      if not await verify_file(full_path, expected_hash):
        raise ValueError(f"Hash validation failed for {filename}")

-      artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.downloaded
-      artifact.downloadProgress.progress = 100
-      artifact.downloadProgress.eta = 0
-      self._sync_artifact_progress(artifact)
-      self._report_status()
+      self._set_progress(artifact, status.downloaded, 100)

    except DownloadCancelled:
      self._download_start_times.pop(artifact.fileName, None)
-      artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.failed
+      artifact.downloadProgress.status = status.failed
      artifact.downloadProgress.eta = 0
+      artifact.downloadProgress.speed = 0
      self._sync_artifact_progress(artifact)
      if self.selected_bundle:
-        self.selected_bundle.status = custom.ModelManagerSP.DownloadStatus.failed
+        self.selected_bundle.status = status.failed
      self._report_status()
      raise

@@ -153,11 +277,12 @@ class ModelManagerSP:
      cloudlog.error(f"Error downloading {filename}: {str(e)}")
      if os.path.isfile(full_path):  # noqa: ASYNC240
        os.remove(full_path)
-      artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.failed
+      artifact.downloadProgress.status = status.failed
      artifact.downloadProgress.eta = 0
+      artifact.downloadProgress.speed = 0
      self._sync_artifact_progress(artifact)
      if self.selected_bundle:
-        self.selected_bundle.status = custom.ModelManagerSP.DownloadStatus.failed
+        self.selected_bundle.status = status.failed
      self._report_status()
      self._download_start_times.pop(artifact.fileName, None)
      raise
@@ -197,6 +322,7 @@ class ModelManagerSP:
          artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.cached
          artifact.downloadProgress.progress = 100
          artifact.downloadProgress.eta = 0
+          artifact.downloadProgress.speed = 0
        else:
          seen_artifacts.add(artifact.fileName)
          await self._process_artifact(artifact, destination_path)
@@ -272,12 +398,7 @@ class ModelManagerSP:
        rk.keep_time()

  def clear_model_cache(self) -> None:
-    """
-    Clears the model cache directory of all files except those in the active model bundle.
-    """
-
-    # Get list of files used by both slots' selected bundles (either may become
-    # the truly active bundle depending on hardware availability)
+    """ Clears the model cache directory of all files except those in the active model bundle."""
    active_files = []
    for source in ACTIVE_BUNDLE_KEYS:
      if selected_bundle := get_selected_bundle(self.params, source):
@@ -285,7 +406,6 @@ class ModelManagerSP:
          if model.artifact.fileName:
            active_files.append(model.artifact.fileName)

-    # Remove all files except active ones
    model_dir = Paths.model_root()
    try:
      for filename in os.listdir(model_dir):
@@ -1,4 +1,4 @@
 DEFAULT_MODEL = "CD210"
 DEFAULT_MODEL_REF = "5b6436a90cf6902b8aaa71c2b6f3d7164d8ae391"
-DEFAULT_BIG_MODEL = "Cinque Terre Model v2"
-DEFAULT_BIG_MODEL_REF = "37bfa1413edcdc2e8844984b83727c33f81d8f46"
+DEFAULT_BIG_MODEL = "Mountain Dew Model v3"
+DEFAULT_BIG_MODEL_REF = "1e219d7785cfb7b7343c7f2366347fc86e7ce5f2"
@@ -1 +1 @@
-2c814f08a2c51323b87839fbf8d2c2a9853a2b5536271b3d67f7b7a2de7f9374
+330fdf61b5519642ebccd93aa50f2d7c4ba6c08c5a10c36a2cf155e498700cef
@@ -10,7 +10,7 @@ import subprocess

 from openpilot.sunnypilot import get_file_hash
 from openpilot.sunnypilot.models.default_model import MODEL_HASH_PATH, SUPERCOMBO_ONNX_PATH, BIG_MODEL_HASH_PATH, \
-                                                      BIG_SUPERCOMBO_ONNX_PATH, _read_model_name_fields
+                                                      BIG_DRIVING_PKL_PATH, _read_model_name_fields
 import hashlib
 from openpilot.common.test import OpenpilotTestCase

@@ -36,12 +36,9 @@ class TestDefaultModel(OpenpilotTestCase):

    assert combined_hash == current_hash, "Run openpilot/sunnypilot/models/default_model.py to update the default model name and hash"

-  def test_compare_big_onnx_hashes(self):
-    if not os.path.exists(BIG_SUPERCOMBO_ONNX_PATH):
-      self.skipTest("big_driving_supercombo.onnx not present")
-
+  def test_compare_big_pkl_hashes(self):
    fields = _read_model_name_fields()
-    oid = _get_lfs_oid(os.path.relpath(BIG_SUPERCOMBO_ONNX_PATH, os.getcwd()))
+    oid = _get_lfs_oid(os.path.relpath(BIG_DRIVING_PKL_PATH, os.getcwd()))
    big_fingerprint = f"{oid}:{fields.get('DEFAULT_BIG_MODEL', '')}:{fields.get('DEFAULT_BIG_MODEL_REF', '')}"
    combined_hash = hashlib.sha256(big_fingerprint.encode()).hexdigest()

@@ -9,7 +9,6 @@ from openpilot.common.params import Params
 from openpilot.common.realtime import DT_MDL
 from openpilot.selfdrive.car.cruise import V_CRUISE_UNSET
 from openpilot.sunnypilot import PARAMS_UPDATE_PERIOD
-from openpilot.sunnypilot.mapd import MAPD_AVAILABLE
 from openpilot.sunnypilot.navd.helpers import Coordinate
 from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control import MIN_V

@@ -76,7 +75,7 @@ class SmartCruiseControlMap:
  def __init__(self):
    self.params = Params()
    self.mem_params = Params("/dev/shm/params") if platform.system() != "Darwin" else self.params
-    self.enabled = MAPD_AVAILABLE and self.params.get_bool("SmartCruiseControlMap")
+    self.enabled = self.params.get_bool("SmartCruiseControlMap")
    self.long_enabled = False
    self.long_override = False
    self.is_enabled = False
@@ -102,7 +101,7 @@ class SmartCruiseControlMap:

  def update_params(self):
    if self.frame % int(PARAMS_UPDATE_PERIOD / DT_MDL) == 0:
-      self.enabled = MAPD_AVAILABLE and self.params.get_bool("SmartCruiseControlMap")
+      self.enabled = self.params.get_bool("SmartCruiseControlMap")

  def update_calculations(self, sm: messaging.SubMaster) -> None:
    gps = sm[self.gps_location_service]
@@ -8,7 +8,7 @@ import json
 import math
 import platform
 from types import SimpleNamespace
-from unittest.mock import MagicMock, patch
+from unittest.mock import MagicMock

 from openpilot.cereal import custom
 from openpilot.common.params import Params
@@ -23,8 +23,6 @@ MapState = VisionState = custom.LongitudinalPlanSP.SmartCruiseControl.MapState
 class TestSmartCruiseControlMap(OpenpilotTestCase):

  def setup_method(self):
-    self.mapd_patch = patch("openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.map_controller.MAPD_AVAILABLE", True)
-    self.mapd_patch.start()
    self.params = Params()
    self.mem_params = Params("/dev/shm/params") if platform.system() != "Darwin" else self.params
    self.reset_params()
@@ -32,9 +30,6 @@ class TestSmartCruiseControlMap(OpenpilotTestCase):
    self.sm = MagicMock()
    self.sm.__getitem__.return_value = SimpleNamespace(latitude=0.0, longitude=0.0)

-  def teardown_method(self):
-    self.mapd_patch.stop()
-
  def reset_params(self):
    self.params.put_bool("SmartCruiseControlMap", True, block=True)

@@ -55,14 +50,6 @@ class TestSmartCruiseControlMap(OpenpilotTestCase):
    assert self.scc_m.state == VisionState.disabled
    assert not self.scc_m.is_active

-  def test_mapd_unavailable(self):
-    self.mapd_patch.stop()
-    self.scc_m = SmartCruiseControlMap()
-    for _ in range(int(10. / DT_MDL)):
-      self.scc_m.update(self.sm, True, False, 0., 0., 0.)
-    assert self.scc_m.state == VisionState.disabled
-    self.mapd_patch.start()
-
  def test_disabled(self):
    for _ in range(int(10. / DT_MDL)):
      self.scc_m.update(self.sm, False, False, 0., 0., 0.)
@@ -13,7 +13,6 @@ from openpilot.common.gps import get_gps_location_service
 from openpilot.common.params import Params
 from openpilot.common.realtime import DT_MDL
 from openpilot.sunnypilot import PARAMS_UPDATE_PERIOD, get_sanitize_int_param
-from openpilot.sunnypilot.mapd import MAPD_AVAILABLE
 from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit import LIMIT_MAX_MAP_DATA_AGE, LIMIT_ADAPT_ACC
 from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit.common import Policy, OffsetType

@@ -49,8 +48,6 @@ class SpeedLimitResolver:
      Policy.max().value,
      self.params
    )
-    if not MAPD_AVAILABLE:
-      self.policy = Policy.car_state_only
    self._policy_to_sources_map = {
      Policy.car_state_only: [SpeedLimitSource.car],
      Policy.map_data_only: [SpeedLimitSource.map],
@@ -94,7 +91,7 @@ class SpeedLimitResolver:

  def update_params(self):
    if self.frame % int(PARAMS_UPDATE_PERIOD / DT_MDL) == 0:
-      self.policy = self.params.get("SpeedLimitPolicy", return_default=True) if MAPD_AVAILABLE else Policy.car_state_only
+      self.policy = self.params.get("SpeedLimitPolicy", return_default=True)
      self.is_metric = self.params.get_bool("IsMetric")
      self.offset_type = self.params.get("SpeedLimitOffsetType", return_default=True)
      self.offset_value = self.params.get("SpeedLimitValueOffset", return_default=True)
@@ -15,7 +15,6 @@ from opendbc.sunnypilot.car.tesla.values import TeslaFlagsSP
 from openpilot.common.params import Params
 from openpilot.common.swaglog import cloudlog
 from openpilot.common.hardware import HARDWARE
-from openpilot.sunnypilot.mapd import MAPD_AVAILABLE


 # Wire-protocol version for the capabilities payload. Bump on breaking changes
@@ -44,7 +43,6 @@ CAPABILITY_FIELDS = (
  "device_type",
  "subaru_has_sng",
  "hyundai_alpha_long_available",
-  "mapd_available",
 )

 CAPABILITY_LABELS: dict[str, str] = {
@@ -67,7 +65,6 @@ CAPABILITY_LABELS: dict[str, str] = {
  "device_type": "Device type",
  "subaru_has_sng": "Subaru Stop-and-Go available",
  "hyundai_alpha_long_available": "Hyundai Alpha Longitudinal available",
-  "mapd_available": "Map data available",
 }

 # Explicit defaults for non-boolean capability fields
@@ -135,7 +132,6 @@ def generate_capabilities(params: Params | None = None) -> dict:
  caps["is_sp_release"] = params.get_bool("IsReleaseSpBranch")
  caps["is_development"] = params.get_bool("IsDevelopmentBranch")
  caps["stock_longitudinal"] = params.get_bool("ToyotaEnforceStockLongitudinal")
-  caps["mapd_available"] = MAPD_AVAILABLE

  bundle = params.get("CarPlatformBundle")
  bundle_brand = _bundle_field(bundle, "brand")
@@ -156,7 +156,7 @@ The tables below describe the **compiled** `settings_ui.json` schema — what th

 **Enablement rules**: Grayed out (disabled) when rules fail. Frontend shows a contextual badge explaining why.

-**Capability fields** (referenced in rules): `has_longitudinal_control`, `has_icbm`, `icbm_available`, `torque_allowed`, `brand`, `pcm_cruise`, `alpha_long_available`, `steer_control_type`, `has_bsm`, `is_release`, `is_sp_release`, `is_development`, `tesla_has_vehicle_bus`, `has_stop_and_go`, `stock_longitudinal`, `mapd_available`
+**Capability fields** (referenced in rules): `has_longitudinal_control`, `has_icbm`, `icbm_available`, `torque_allowed`, `brand`, `pcm_cruise`, `alpha_long_available`, `steer_control_type`, `has_bsm`, `is_release`, `is_sp_release`, `is_development`, `tesla_has_vehicle_bus`, `has_stop_and_go`, `stock_longitudinal`

 ---

@@ -857,47 +857,19 @@
                    },
                    {
                      "value": 1,
-                      "label": "Map Data Only",
-                      "enablement": [
-                        {
-                          "type": "capability",
-                          "field": "mapd_available",
-                          "equals": true
-                        }
-                      ]
+                      "label": "Map Data Only"
                    },
                    {
                      "value": 2,
-                      "label": "Car State Priority",
-                      "enablement": [
-                        {
-                          "type": "capability",
-                          "field": "mapd_available",
-                          "equals": true
-                        }
-                      ]
+                      "label": "Car State Priority"
                    },
                    {
                      "value": 3,
-                      "label": "Map Data Priority",
-                      "enablement": [
-                        {
-                          "type": "capability",
-                          "field": "mapd_available",
-                          "equals": true
-                        }
-                      ]
+                      "label": "Map Data Priority"
                    },
                    {
                      "value": 4,
-                      "label": "Combined",
-                      "enablement": [
-                        {
-                          "type": "capability",
-                          "field": "mapd_available",
-                          "equals": true
-                        }
-                      ]
+                      "label": "Combined"
                    }
                  ]
                },
@@ -1029,11 +1001,6 @@
                }
              ],
              "enablement": [
-                {
-                  "type": "capability",
-                  "field": "mapd_available",
-                  "equals": true
-                },
                {
                  "type": "any",
                  "conditions": [
@@ -2054,8 +2021,14 @@
        {
          "id": "model_behavior",
          "title": "Model Behavior",
-          "description": "Lane desire and lead-vehicle awareness tuning",
+          "description": "Lane desire, Blendful lane centering, and lead-vehicle awareness tuning",
          "items": [
+            {
+              "key": "Blendful",
+              "widget": "toggle",
+              "title": "Blendful Mode",
+              "description": "Nudges the car toward the lane center when the lane lines are clear. Drives laneless when they are not."
+            },
            {
              "key": "LaneTurnDesire",
              "widget": "toggle",
@@ -167,28 +167,12 @@ sections:
        label: Car State Only
      - value: 1
        label: Map Data Only
-        enablement:
-        - type: capability
-          field: mapd_available
-          equals: true
      - value: 2
        label: Car State Priority
-        enablement:
-        - type: capability
-          field: mapd_available
-          equals: true
      - value: 3
        label: Map Data Priority
-        enablement:
-        - type: capability
-          field: mapd_available
-          equals: true
      - value: 4
        label: Combined
-        enablement:
-        - type: capability
-          field: mapd_available
-          equals: true
    - key: SpeedLimitOffsetType
      widget: multiple_button
      title: Speed Limit Offset Type
@@ -262,9 +246,6 @@ sections:
        field: has_icbm
        equals: true
    enablement:
-    - type: capability
-      field: mapd_available
-      equals: true
    - type: any
      conditions:
      - type: capability
@@ -9,8 +9,12 @@ description: Driving model behavior and camera calibration
 sections:
 - id: model_behavior
  title: Model Behavior
-  description: Lane desire and lead-vehicle awareness tuning
+  description: Lane desire, Blendful lane centering, and lead-vehicle awareness tuning
  items:
+  - key: Blendful
+    widget: toggle
+    title: Blendful Mode
+    description: Nudges the car toward the lane center when the lane lines are clear. Drives laneless when they are not.
  - key: LaneTurnDesire
    widget: toggle
    title: Use Lane Turn Desires
@@ -57,7 +57,7 @@ class DownloadStatusAction(ItemAction):
    self.icon: str | None = None
    self.icon_color: rl.Color | None = None
    self._font = gui_app.font(FontWeight.NORMAL)
-    # raw progress arrives in steps, one per 128KB chunk the manager publishes
+    # raw progress arrives in steps, one per progress report from the manager
    self._progress = FirstOrderFilter(0.0, 0.5, 1 / gui_app.target_fps)
    # integrated per frame; (t * speed) % span jumps whenever the fill width changes
    self._sweep = 0.0
Author	SHA1	Message	Date
discountchubbs	9d98fe4376	he does not like 1ms	2026-10-23 11:56:25 -07:00
discountchubbs	0ce9fca933	decay one line and give full authority in curvy curves; kappa=curv	2026-10-23 11:55:31 -07:00
James Vecellio-Grant	2110ffab00	Merge branch 'master' into laneful-curves	2026-10-23 00:05:23 -07:00
discountchubbs	cda505ea6d	satisfy royjr	2026-10-22 23:54:18 -07:00
discountchubbs	aa559e48a2	smoother release authority	2026-10-22 23:52:10 -07:00
royjr	02c7b60600	fine	2026-10-23 00:35:06 -04:00
royjr	d28e027943	keep pill current	2026-10-23 00:12:41 -04:00
royjr	f179460982	so I can sleep at night	2026-10-23 00:05:04 -04:00
royjr	16b17e051f	tick on new data	2026-10-23 00:03:15 -04:00
royjr	8efe325a71	gate like rainbow	2026-10-22 23:55:28 -04:00
royjr	9c391b4842	cleanup	2026-10-22 23:46:50 -04:00
royjr	6ac88a7be0	move to models	2026-10-22 23:25:32 -04:00
royjr	4dbb49430b	tizi	2026-10-22 23:25:32 -04:00
royjr	5de324ab96	ill take it from here thanks	2026-10-22 23:25:32 -04:00
royjr	d904487eed	sqrt bar	2026-10-22 23:25:32 -04:00
royjr	2ffb986f3b	blue only	2026-10-22 23:25:32 -04:00
discountchubbs	c4f1dc179f	dead	2026-10-22 20:17:03 -07:00
Jason Wen	8e740e0ac6	bump opendbc	2026-10-22 22:20:29 -04:00
royjr	15bf3dcd94	fade out blue	2026-10-22 18:15:10 -04:00
royjr	6e0ce4a6f9	match width	2026-10-22 18:15:10 -04:00
royjr	d45d7e2de7	white is model path	2026-10-22 18:15:10 -04:00
royjr	a3ef498512	dont guess	2026-10-22 18:15:10 -04:00
royjr	21f45673fd	use blendful trust	2026-10-22 18:15:10 -04:00
royjr	fd39f4f820	fade on trust	2026-10-22 18:15:10 -04:00
royjr	cb71cdc54d	use constants	2026-10-22 18:15:10 -04:00
royjr	afd0ce66c9	no tap	2026-10-22 18:15:10 -04:00
royjr	5854346c2f	blendful	2026-10-22 18:15:10 -04:00
James Vecellio-Grant	270704ad47	Merge branch 'master' into laneful-curves	2026-10-22 10:55:59 -07:00
James Vecellio-Grant	9d029d683d	models: self healing test for tg (#2072 ) * models: self healing test for tg * rm container * ew * set env * set var	2026-10-22 13:43:42 -04:00
James Vecellio-Grant	4ebb756ee5	Merge branch 'master' into laneful-curves	2026-10-22 10:15:23 -07:00
Amy Jeanes	f78c6c2377	models: publish the download speed and derive the eta from it (#2052 ) * models: publish the download speed and derive the eta from it Fills in DownloadProgress.speed (bytes per second, declared with the parallel downloader). The reporter measures the rate between its 0.5 s reports, smooths it, and derives the eta from the bytes remaining at that rate instead of extrapolating elapsed time. Speed is zeroed when a download ends, fails or is cancelled and for a cached artifact, and copied across artifacts that share a file like the other progress fields. The big UI's Models page shows "12.3 MB/s" next to the progress bar and the mici models panel shows it beside the percentage. Both take the max across a bundle's artifacts, not the sum, since artifacts sharing a file mirror the same transfer and only one file is ever in flight. A stall decays the smoothed speed toward 0 without ever reaching it, so below 0.05 MB/s, which would only display as "0.0 MB/s", it snaps to 0. Both UIs then show "--.- MB/s" while downloading with no rate (before the first reading or during a stall) instead of a stuck "0.0 MB/s" or nothing, and the speed recovers straight to the real rate once data flows again. The snap also keeps the eta in range: without it a stall of about 25 s drove remaining / speed past the capnp UInt32 eta, and the capnp error failed the download outright instead of leaving the stall to the read timeout and retries. A test holds a piece stalled until the published speed reaches exactly 0, and errors on that overflow without the snap. Assisted-by: Claude Code (Claude Opus 4.8) Assisted-by: Claude Code (Claude Opus 5.5) * remove unneeded comments Assisted-by: Claude Code (Claude Opus 5.5) * models: take the speed baseline before the workers start The reporter took its starting byte count after the piece workers were submitted, and starting each pool thread lets earlier workers run, so bytes landed in that gap never counted toward a speed sample. Take the baseline in _download_file before any worker exists and pass it in. The test runs every piece inline in submit, so the whole file lands before the reporter starts; with the late baseline the speed stays 0. Assisted-by: Claude Code (Claude Opus 5.5)	2026-10-21 16:13:52 -07:00
nayan	ee7bf203fe	ffs	2026-10-21 17:20:08 -04:00
James Vecellio-Grant	1aa3a430fb	models: pin tg to @02e6981 (#2071 )	2026-10-21 11:11:24 -07:00
Amy Jeanes	ddd7b14ebc	models: download whole-file artifacts with parallel byte ranges (#2051 ) * models: download whole-file artifacts with parallel byte ranges HuggingFace's Xet CAS throttles each connection to roughly 1-2 MB/s but does not limit connection count, so the single-stream _download_file left the link idle most of the time. Replace it with a downloader that probes the size with a one-byte Range request, creates the file at its final size and streams each 8 MB piece straight to its offset from one of 12 worker threads. The file is never copied or assembled and only ever occupies its own size on disk. A server that answers the probe with 200 gets one plain stream instead. Every request sends Accept-Encoding: identity, because byte ranges count encoded bytes while requests hands back decoded ones, so a compressed response would land at the wrong offsets and fail as a short read. Workers only write bytes; a reporter coroutine on the event loop publishes progress every 0.5 s (instead of every 128 KB), re-raises the first worker failure and polls the cancel ref. Transient errors (connection, timeout, truncated body, HTTP 408/429/500/502/503/504) give a piece up to three attempts; any other HTTP error fails the download at once. The whole-file path now also publishes "verifying" while hashing before and after the transfer, and the download is hashed against the manifest exactly as before. A cancel has to wait for in-flight pieces to unwind (a blocked socket read cannot be interrupted), so the row shows "canceling..." through a new DownloadProgress.canceling flag instead of a frozen bar, and the mici cancel button hides once the ref is gone, as it already does on the big UI. DownloadProgress gains speed, canceling and resuming, appended to the capnp so older readers are unaffected. All three are declared here so the wire format lands in one place; speed and resuming are filled in by the follow-up speed and resume changes. Builds on #2050, which drops chunking and publishes models as whole files; this makes that whole-file download parallel. Measured on a comma 3X on WiFi: ~2 MB/s single stream, 17-24 MB/s steady and 30-60 MB/s peak with 12 range connections, the count picked from an on-device sweep. Disk is not the bottleneck (eMMC writes at 56-67 MB/s with fdatasync). Tests drive the real downloader against a local threaded range server: piece tiling, actual parallelism (a stalled piece does not block the others), the no-range fallback, per-piece retry, 4xx, cancel via ModelManager_DownloadRef and mid-piece, verify/cached/downloaded state, a probe failure moving past verifying, and hash mismatch cleanup. Also drops two chunk-era leftovers in the tests: a stale "no chunks" note on manifest_bundle and a one-item URL loop in the live manifest check. Assisted-by: Claude Code (Claude Opus 4.8) Assisted-by: Claude Code (Claude Opus 5.5) * remove unneeded comments * models: trim the manager tests to the regressions they catch Each remaining test is there because a deliberate break in manager.py, helpers.py or fetcher.py fails it. Tests that only re-checked what another already catches are merged into a happy-path download or a table, and checks of constants rather than behaviour are dropped. The fake server now starts per test, keeps its state in one dataclass, and can cut a response short. Against 66 deliberate breaks, every one the old tests caught still fails, and a 404 being retried, a short read and its retry, and the display flags choosing the big model without a GPU are now caught too. Assisted-by: Claude Code (Claude Opus 5.5) * Update test_manager_download.py * Update manager.py --------- Co-authored-by: James Vecellio-Grant <159560811+Discountchubbs@users.noreply.github.com>	2026-10-21 09:35:43 -07:00
discountchubbs	62cf10ff05	let unwind be handled by laneless	2026-10-21 08:17:55 -07:00
discountchubbs	7707a3e384	interpolate smoothness on straights to reduce mr kumar and his mdv3 jiggle shennanigans	2026-10-20 22:56:10 -07:00
discountchubbs	e87a605fb2	relearn ideal sim pose	2026-10-20 18:39:44 -07:00
James Vecellio-Grant	11603b2de7	Update modeld.py	2026-10-20 18:02:52 -07:00
James Vecellio-Grant	644e23f8ef	Update modeld.py	2026-10-20 17:55:15 -07:00
discountchubbs	7847dbf148	sm logging + qlog logging	2026-10-20 15:47:46 -07:00
discountchubbs	0af369cae0	blendful	2026-10-20 13:28:20 -07:00
James Vecellio-Grant	77d0c2d665	Ui fix	2026-10-20 07:16:14 -07:00
discountchubbs	4d2d3f69f5	winner takes all trust system in lane lines	2026-10-19 23:11:22 -07:00
discountchubbs	e9fc7a2465	less is more	2026-10-19 21:43:35 -07:00
discountchubbs	61154655cd	handle one line flicker by trust÷2	2026-10-19 20:25:29 -07:00
discountchubbs	ed4e8aeea6	jerk limiting correctin strength so that hecker doesnt spin spin yo wheel	2026-10-19 20:20:45 -07:00
discountchubbs	a3ed6bd2f0	blending 50% on sharp curvaruerqw	2026-10-19 16:49:48 -07:00
discountchubbs	46c0b31997	blend 30% plan with action projeciton	2026-10-19 16:28:07 -07:00
discountchubbs	8a50860648	quicker entry	2026-10-19 14:16:46 -07:00
discountchubbs	563fa3c782	sharp curvies have some issues :O	2026-10-19 13:38:52 -07:00
discountchubbs	0b3459fbdc	decay trust when model intends to move plant off lane. think going around cones and stuff	2026-10-19 13:10:03 -07:00
discountchubbs	54a22bd8bd	blended correction over .3 s	2026-10-19 12:54:53 -07:00
discountchubbs	6c674810ee	default to 1.0 while i test variable weighting	2026-10-19 12:38:16 -07:00
discountchubbs	e64f67ec7e	red diff that	2026-10-19 12:36:35 -07:00
discountchubbs	9c7655c45e	modeld_v2: blended laneful using weighted stds	2026-10-19 12:11:27 -07:00
discountchubbs	60c6464a14	Merge remote-tracking branch 'origin/master' into laneful-curves # Conflicts: # openpilot/selfdrive/ui/mici/onroad/model_renderer.py # openpilot/sunnypilot/modeld_v2/modeld.py	2026-10-19 12:08:14 -07:00
James Vecellio-Grant	922513f312	ci: lfs pointers survive gc (#2066 ) * ci: lfs pointers survive gc * comma got gc'ed * format	2026-10-18 22:41:23 -07:00
Kumar	0dacd0eec4	Revert "mapd: disable map-based Smart Cruise Control and speed limit sources until mapd has a position source" (#2065 ) This reverts commit `b6170ac5e9`.	2026-10-18 19:25:14 -07:00
Kumar	09b2f4bbe0	mapd: fix mapd GPS position handling (#2064 ) * mapd: restore the position mapd reads from llk * turn it on * mapd ui * Revert "mapd ui" This reverts commit `857d430297`. * Revert "turn it on" This reverts commit `2a5d9a62be`.	2026-10-18 19:07:32 -07:00
Amy Jeanes	0120b66f05	modeld: set AM_PERF_LEVEL to high for perf (#2061 ) set AM_PERF_LEVEL to high for perf Co-authored-by: James Vecellio-Grant <159560811+Discountchubbs@users.noreply.github.com>	2026-10-18 16:16:49 -07:00
James Vecellio-Grant	f09b04c267	ci: upload big model over lfs (#2063 ) ci: push chestnut via lfs	2026-10-18 16:14:06 -07:00
James Vecellio-Grant	f0617e11a6	ci: fix default models (#2062 ) * ci: fix default models * shouldnt of been deleted * skip dm warp as well	2026-10-18 15:30:33 -07:00
Jason Wen	0739fe823d	Sync: `commaai/openpilot:master` → `sunnypilot/sunnypilot:master` (#2059 )	2026-10-18 15:39:49 -04:00
Jason Wen	b6170ac5e9	mapd: disable map-based Smart Cruise Control and speed limit sources until mapd has a position source	2026-10-18 15:25:45 -04:00
James Vecellio-Grant	e6864661c9	modeld_v2: create a compiled pkl -> gpu kernel artifact converter (#2053 )	2026-10-18 15:25:45 -04:00
James Vecellio-Grant	4ff90ff8d0	modeld_v2: compile models to plain gpu memory artifact (#2050 )	2026-10-18 15:25:45 -04:00
Jason Wen	2149006ec7	Merge commit '35e78a9d9518855ec0dacec919e719624a28131f' into sync-20261016 # Conflicts: # .gitattributes # .gitignore # .gitmodules # opendbc_repo # openpilot/common/params_keys.h # openpilot/common/version.py # openpilot/selfdrive/car/card.py # openpilot/selfdrive/controls/lib/longitudinal_planner.py # openpilot/selfdrive/controls/plannerd.py # openpilot/selfdrive/controls/tests/test_latcontrol.py # openpilot/selfdrive/modeld/modeld.py # openpilot/selfdrive/pandad/pandad.py # openpilot/selfdrive/selfdrived/alerts_offroad.json # openpilot/selfdrive/selfdrived/selfdrived.py # openpilot/selfdrive/test/longitudinal_maneuvers/plant.py # openpilot/selfdrive/ui/layouts/settings/developer.py # openpilot/selfdrive/ui/layouts/settings/toggles.py # openpilot/selfdrive/ui/mici/layouts/home.py # openpilot/selfdrive/ui/mici/layouts/onboarding.py # openpilot/selfdrive/ui/mici/onroad/model_renderer.py # openpilot/selfdrive/ui/onroad/model_renderer.py # openpilot/selfdrive/ui/soundd.py # openpilot/selfdrive/ui/translations/app.pot # openpilot/selfdrive/ui/translations/app_de.po # openpilot/selfdrive/ui/translations/app_en.po # openpilot/selfdrive/ui/translations/app_es.po # openpilot/selfdrive/ui/translations/app_fr.po # openpilot/selfdrive/ui/translations/app_ja.po # openpilot/selfdrive/ui/translations/app_ko.po # openpilot/selfdrive/ui/translations/app_pt-BR.po # openpilot/selfdrive/ui/translations/app_th.po # openpilot/selfdrive/ui/translations/app_tr.po # openpilot/selfdrive/ui/translations/app_uk.po # openpilot/selfdrive/ui/translations/app_zh-CHS.po # openpilot/selfdrive/ui/translations/app_zh-CHT.po # openpilot/selfdrive/ui/ui_state.py # openpilot/system/hardware/chestnut/status.py # openpilot/system/manager/process_config.py # openpilot/system/ui/README.md # panda # tinygrad_repo	2026-10-18 15:25:44 -04:00