Sync: commaai/openpilot:master -> sunnypilot/sunnypilot:master

# Conflicts:
#	.gitmodules
#	.lfsconfig
#	opendbc_repo
#	openpilot/selfdrive/modeld/SConscript
#	openpilot/selfdrive/modeld/modeld.py
#	openpilot/selfdrive/ui/mici/layouts/settings/toggles.py
#	openpilot/system/sentry.py
#	panda
#	scripts/lint/lint.sh
#	tinygrad_repo
#	tools/release/build_stripped.sh
#	tools/release/check-submodules.sh
#	uv.lock

.gitattributes

@@ -1,8 +1,10 @@
-* text=auto
+* text=auto eol=lf
 
 # to move existing files into LFS:
 # git add --renormalize .
 *.onnx filter=lfs diff=lfs merge=lfs -text
+openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl filter=lfs diff=lfs merge=lfs -text
+openpilot/sunnypilot/modeld_v2/models/*.pkl filter=lfs diff=lfs merge=lfs -text
 *.svg filter=lfs diff=lfs merge=lfs -text
 *.png filter=lfs diff=lfs merge=lfs -text
 *.gif filter=lfs diff=lfs merge=lfs -text

.github/CODEOWNERS

@@ -1,11 +0,0 @@
-*       @sunnypilot/dev-internal
-/.github/ @devtekve @sunnyhaibin
-/release/ci/ @devtekve @sunnyhaibin
-/tinygrad_repo @devtekve @Discountchubbs
-/tinygrad/ @devtekve @Discountchubbs
-/selfdrive/controls/lib/longitudinal_planner.py @devtekve @Discountchubbs
-/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py @devtekve @Discountchubbs
-/selfdrive/modeld/ @devtekve @Discountchubbs
-/sunnypilot/model* @devtekve @Discountchubbs
-/sunnypilot/sunnylink/ @devtekve
-/system/athena/ @devtekve

.github/release-drafter.yml

@@ -1,43 +0,0 @@
-exclude-labels:
-  - 'no-changelog'
-categories:
-  - title: '🚀 Features'
-    labels:
-      - 'feature'
-      - 'enhancement'
-  - title: '🐛 Bug Fixes'
-    collapse-after: 5
-    labels:
-      - 'fix'
-      - 'bugfix'
-      - 'bug'
-  - title: '🧰 Maintenance'
-    collapse-after: 5
-    label: 'chore'
-change-template: '- $TITLE @$AUTHOR (#$NUMBER)'
-change-title-escapes: '\<*_&'
-replacers:
-  - search: '/[Ss][Uu][Nn][Nn][Yy][Pp][Ii][Ll][Oo][Tt]/g'
-    replace: 'sunnypilot'
-  - search: '/\b[Ss][Pp]\b/g'
-    replace: 'SP'
-version-resolver:
-  major:
-    labels:
-      - 'major'
-  minor:
-    labels:
-      - 'minor'
-  patch:
-    labels:
-      - 'patch'
-  default: patch
-name-template: 'v$RESOLVED_VERSION 🚀'
-tag-template: 'v$RESOLVED_VERSION'
-version-template: "0.$MAJOR.$MINOR.$PATCH" # The day OP becomes v1, we need to bump this
-tag-prefix: "v0." # The day OP becomes v1, we need to bump this
-prerelease-identifier: "staging"
-template: |
-  ## Changes
-
-  $CHANGES

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

@@ -7,6 +7,24 @@ on:
         description: 'Minimum selector version required for the models (see helpers.py or readme.md)'
         required: true
         type: string
+      target_hardware:
+        description: 'Hardware target to compile for (qcom or chestnut)'
+        required: true
+        type: choice
+        default: 'qcom'
+        options:
+          - qcom
+          - chestnut
+      hf_repo:
+        description: 'Hugging Face dataset repository'
+        required: false
+        type: string
+        default: 'sunnypilot/sunnypilot_models_v1'
+      docs_repo:
+        description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
+        required: false
+        type: string
+        default: 'sunnypilot/sunnypilot-models'
 
 jobs:
   setup:
@@ -21,7 +39,6 @@ jobs:
       - name: Checkout sunnypilot repo
         uses: actions/checkout@v4
         with:
-          repository: sunnypilot/sunnypilot
           path: sunnypilot
           submodules: recursive
 
@@ -34,10 +51,10 @@ jobs:
           echo "tinygrad_ref=$ref" >> $GITHUB_OUTPUT
           echo "tinygrad_ref is $ref"
 
-      - name: Checkout docs repo (sunnypilot-models, gh-pages)
+      - name: Checkout docs repo (gh-pages)
         uses: actions/checkout@v4
         with:
-          repository: sunnypilot/sunnypilot-models
+          repository: ${{ inputs.docs_repo }}
           ref: gh-pages
           path: docs
           ssh-key: ${{ secrets.CI_SUNNYPILOT_DOCS_PRIVATE_KEY }}
@@ -46,13 +63,14 @@ jobs:
         id: get-json
         run: |
           cd docs/docs
-          latest=$(ls driving_models_v*.json | sed -E 's/.*_v([0-9]+)\.json/\1/' | sort -n | tail -1)
+          PREFIX="driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_' || '' }}v"
+          latest=$(ls ${PREFIX}*.json | sed -E "s/${PREFIX}([0-9]+)\.json/\1/" | sort -n | tail -1)
           next=$((latest+1))
-          json_file="driving_models_v${next}.json"
-          cp "driving_models_v${latest}.json" "$json_file"
+          json_file="${PREFIX}${next}.json"
+          cp "${PREFIX}${latest}.json" "$json_file"
           echo "json_file=docs/docs/$json_file" >> $GITHUB_OUTPUT
           echo "json_version=$((next+0))" >> $GITHUB_OUTPUT
-          echo "SRC_JSON_FILE=docs/docs/driving_models_v${latest}.json" >> $GITHUB_ENV
+          echo "SRC_JSON_FILE=docs/docs/${PREFIX}${latest}.json" >> $GITHUB_ENV
 
       - name: Extract tinygrad models
         id: set-matrix
@@ -61,45 +79,24 @@ jobs:
           jq -c '[.bundles[] | select(.runner=="tinygrad") | {ref, display_name: (.display_name | gsub(" \\([^)]*\\)"; "")), is_20hz}]' "$(basename "${SRC_JSON_FILE}")" > matrix.json
           echo "model_matrix=$(cat matrix.json)" >> $GITHUB_OUTPUT
 
-      - name: Set up SSH
-        uses: webfactory/ssh-agent@v0.9.0
-        with:
-          ssh-private-key: ${{ secrets.GITLAB_SSH_PRIVATE_KEY }}
-      - run: |
-          mkdir -p ~/.ssh
-          ssh-keyscan -H gitlab.com >> ~/.ssh/known_hosts
-
-      - name: Clone GitLab docs repo and create new recompiled dir
+      - name: Get next recompiled dir number
         id: create-recompiled-dir
         env:
-          GIT_SSH_COMMAND: 'ssh -o UserKnownHostsFile=~/.ssh/known_hosts'
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_REPO: ${{ github.event.inputs.hf_repo }}
         run: |
-          git clone --depth 1 --filter=tree:0 --sparse git@gitlab.com:sunnypilot/public/${{ vars.MODELS_GITLAB }} gitlab_docs
-          cd gitlab_docs
-          git checkout main
-          git sparse-checkout set --no-cone models/
-          cd models
-          latest_dir=$(ls -d recompiled* 2>/dev/null | sed -E 's/recompiled([0-9]+)/\1/' | sort -n | tail -1)
-          if [[ -z "$latest_dir" ]]; then
-            next_dir=1
-          else
-            next_dir=$((latest_dir+1))
-          fi
-          recompiled_dir="${next_dir}"
-          mkdir -p "recompiled${recompiled_dir}"
-          touch "recompiled${recompiled_dir}/.gitkeep"
-          cd ../..
+          pip install huggingface_hub
+          recompiled_dir=$(python3 -c "
+          from huggingface_hub import HfApi
+          import re, sys
+          api = HfApi()
+          files = api.list_repo_files(repo_id=sys.argv[1], repo_type='dataset')
+          dirs = [re.search(r'models/recompiled([0-9]+)', f) for f in files]
+          nums = [int(m.group(1)) for m in dirs if m]
+          print(max(nums) + 1)
+          " "$HF_REPO")
           echo "recompiled_dir=$recompiled_dir" >> $GITHUB_OUTPUT
 
-      - name: Push empty recompiled dir to GitLab
-        run: |
-          cd gitlab_docs
-          git add models/recompiled${{ steps.create-recompiled-dir.outputs.recompiled_dir }}
-          git config --global user.name "GitHub Action"
-          git config --global user.email "action@github.com"
-          git commit -m "Add recompiled${{ steps.create-recompiled-dir.outputs.recompiled_dir }} for build-all" || echo "No changes to commit"
-          git push origin main
-
       - name: Push new JSON to GitHub docs repo
         run: |
           cd docs
@@ -123,25 +120,31 @@ jobs:
       is_20hz: ${{ matrix.model.is_20hz }}
       recompiled_dir: ${{ needs.setup.outputs.recompiled_dir }}
       json_version: ${{ needs.setup.outputs.json_version }}
+      target_hardware: ${{ github.event.inputs.target_hardware }}
+      hf_repo: ${{ github.event.inputs.hf_repo }}
+      docs_repo: ${{ inputs.docs_repo }}
+      set_min_version: ${{ github.event.inputs.set_min_version }}
+      tinygrad_ref: ${{ needs.setup.outputs.tinygrad_ref }}
     secrets: inherit
 
   retry_failed_models:
     needs: [setup, get_and_build]
     runs-on: ubuntu-latest
-    if: ${{ needs.setup.result != 'failure' && !cancelled() }}
+    if: ${{ !cancelled() && needs.setup.result == 'success' && (needs.get_and_build.result == 'success' || needs.get_and_build.result == 'failure') }}
     outputs:
       retry_matrix: ${{ steps.set-retry-matrix.outputs.retry_matrix }}
     steps:
       - uses: actions/download-artifact@v4
         with:
-          pattern: model-*
+          pattern: artifact-name-*
           path: output
+        continue-on-error: true
 
       - id: set-retry-matrix
         run: |
           echo '${{ needs.setup.outputs.model_matrix }}' > matrix.json
-          built=(); while IFS= read -r line; do built+=("$line"); done < <(
-            find output -maxdepth 1 -name 'model-*' -printf "%f\n" | sed -E 's/^model-//' | sed -E 's/-[0-9]+$//' | sed -E 's/ \([^)]*\)//' | awk '{gsub(/^ +| +$/, ""); print}'
+          built=(); while IFS= read -r line; do [ -n "$line" ] && built+=("$line"); done < <(
+            find output -maxdepth 1 -name 'artifact-name-*' -printf "%f\n" 2>/dev/null | sed -E 's/^artifact-name-//' | awk '{gsub(/^ +| +$/, ""); print}'
           )
           jq -c --argjson built "$(printf '%s\n' "${built[@]}" | jq -R . | jq -s .)" \
             'map(select(.display_name as $n | ($built | index($n | gsub("^ +| +$"; "")) | not)))' matrix.json > retry_matrix.json
@@ -149,7 +152,7 @@ jobs:
 
   retry_get_and_build:
     needs: [setup, get_and_build, retry_failed_models]
-    if: ${{ needs.get_and_build.result == 'failure' || (needs.retry_failed_models.outputs.retry_matrix != '[]' && needs.retry_failed_models.outputs.retry_matrix != '') }}
+    if: ${{ !cancelled() && needs.retry_failed_models.result == 'success' && needs.retry_failed_models.outputs.retry_matrix != '[]' && needs.retry_failed_models.outputs.retry_matrix != '' }}
     strategy:
       matrix:
         model: ${{ fromJson(needs.retry_failed_models.outputs.retry_matrix) }}
@@ -161,146 +164,10 @@ jobs:
       is_20hz: ${{ matrix.model.is_20hz }}
       recompiled_dir: ${{ needs.setup.outputs.recompiled_dir }}
       json_version: ${{ needs.setup.outputs.json_version }}
+      target_hardware: ${{ github.event.inputs.target_hardware }}
       artifact_suffix: -retry
+      hf_repo: ${{ github.event.inputs.hf_repo }}
+      docs_repo: ${{ inputs.docs_repo }}
+      set_min_version: ${{ github.event.inputs.set_min_version }}
+      tinygrad_ref: ${{ needs.setup.outputs.tinygrad_ref }}
     secrets: inherit
-
-  publish_models:
-    name: Publish models sequentially
-    needs: [setup, get_and_build, retry_failed_models, retry_get_and_build]
-    if: ${{ !cancelled() && (needs.get_and_build.result != 'failure' || needs.retry_get_and_build.result == 'success' || (needs.retry_failed_models.outputs.retry_matrix != '[]' && needs.retry_failed_models.outputs.retry_matrix != '')) }}
-    runs-on: ubuntu-latest
-    strategy:
-      fail-fast: false
-      max-parallel: 1
-      matrix:
-        model: ${{ fromJson(needs.setup.outputs.model_matrix) }}
-    env:
-      RECOMPILED_DIR: recompiled${{ needs.setup.outputs.recompiled_dir }}
-      JSON_FILE: ${{ needs.setup.outputs.json_file }}
-      ARTIFACT_NAME_INPUT: ${{ matrix.model.display_name }}
-    steps:
-      - name: Set up SSH
-        uses: webfactory/ssh-agent@v0.9.0
-        with:
-          ssh-private-key: ${{ secrets.GITLAB_SSH_PRIVATE_KEY }}
-
-      - name: Add GitLab.com SSH key to known_hosts
-        run: |
-          mkdir -p ~/.ssh
-          ssh-keyscan -H gitlab.com >> ~/.ssh/known_hosts
-
-      - name: Clone GitLab docs repo
-        env:
-          GIT_SSH_COMMAND: 'ssh -o UserKnownHostsFile=~/.ssh/known_hosts'
-        run: |
-          echo "Cloning GitLab"
-          git clone --depth 1 --filter=tree:0 --sparse git@gitlab.com:sunnypilot/public/${{ vars.MODELS_GITLAB }} gitlab_docs
-          cd gitlab_docs
-          echo "checkout models/${RECOMPILED_DIR}"
-          git sparse-checkout set --no-cone models/${RECOMPILED_DIR}
-          git checkout main
-          cd ..
-
-      - name: Checkout docs repo
-        uses: actions/checkout@v4
-        with:
-          repository: sunnypilot/sunnypilot-models
-          ref: gh-pages
-          path: docs
-          ssh-key: ${{ secrets.CI_SUNNYPILOT_DOCS_PRIVATE_KEY }}
-
-      - name: Validate recompiled dir and JSON version
-        run: |
-          if [ ! -d "gitlab_docs/models/$RECOMPILED_DIR" ]; then
-            echo "Recompiled dir $RECOMPILED_DIR does not exist in GitLab repo"
-            exit 1
-          fi
-          if [ ! -f "$JSON_FILE" ]; then
-            echo "JSON file $JSON_FILE does not exist!"
-            exit 1
-          fi
-
-      - name: Download artifact name file
-        uses: actions/download-artifact@v4
-        with:
-          name: artifact-name-${{ env.ARTIFACT_NAME_INPUT }}
-          path: artifact_name
-
-      - name: Read artifact name
-        id: read-artifact-name
-        run: |
-          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
-          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
-
-      - name: Download model artifact
-        uses: actions/download-artifact@v4
-        with:
-          name: ${{ steps.read-artifact-name.outputs.artifact_name }}
-          path: output
-
-      - name: Remove onnx files bc not needed for recompiled dir since they already exist from single build
-        run: |
-          find output -type f -name '*.onnx' -delete
-          find output -type f -name 'big_*.pkl' -delete
-          find output -type f -name 'dmonitoring_model_tinygrad.pkl' -delete
-
-      - name: Copy model artifacts to gitlab
-        env:
-          ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
-        run: |
-          ARTIFACT_DIR="gitlab_docs/models/${RECOMPILED_DIR}/${ARTIFACT_NAME}"
-          mkdir -p "$ARTIFACT_DIR"
-          for path in output/*; do
-            if [ "$(basename "$path")" = "artifact_name.txt" ]; then
-              continue
-            fi
-            name="$(basename "$path")"
-            if [ -d "$path" ]; then
-              mkdir -p "$ARTIFACT_DIR/$name"
-              cp -r "$path"/* "$ARTIFACT_DIR/$name/"
-              echo "Copied dir $name -> $ARTIFACT_DIR/$name"
-            else
-              cp "$path" "$ARTIFACT_DIR/"
-              echo "Copied file $name -> $ARTIFACT_DIR/"
-            fi
-          done
-
-      - name: Push recompiled dir to GitLab
-        env:
-          GITLAB_SSH_PRIVATE_KEY: ${{ secrets.GITLAB_SSH_PRIVATE_KEY }}
-        run: |
-          cd gitlab_docs
-          git checkout main
-          git pull origin main
-          for d in models/"$RECOMPILED_DIR"/*/; do
-            git sparse-checkout add "$d"
-          done
-          git add models/"$RECOMPILED_DIR"
-          git config --global user.name "GitHub Action"
-          git config --global user.email "action@github.com"
-          git commit -m "Update $RECOMPILED_DIR with model from build-all-tinygrad-models" || echo "No changes to commit"
-          git push origin main
-      - run: |
-          cd docs
-          git pull origin gh-pages
-
-      - name: update json
-        run: |
-          ARGS=""
-          [ -n "${{ inputs.set_min_version }}" ] && ARGS="$ARGS --set-min-version \"${{ inputs.set_min_version }}\""
-          ARGS="$ARGS --sort-by-date"
-          ARGS="$ARGS --tinygrad-ref \"${{ needs.setup.outputs.tinygrad_ref }}\""
-          eval python3 docs/json_parser.py \
-            --json-path "$JSON_FILE" \
-            --recompiled-dir "gitlab_docs/models/$RECOMPILED_DIR" \
-            $ARGS
-
-      - name: Push updated json to GitHub
-        run: |
-          cd docs
-          git config --global user.name "GitHub Action"
-          git config --global user.email "action@github.com"
-          git checkout gh-pages
-          git add docs/"$(basename $JSON_FILE)"
-          git commit -m "Update $(basename $JSON_FILE) after recompiling model" || echo "No changes to commit"
-          git push origin gh-pages

.github/workflows/build-default-models.yaml

@@ -0,0 +1,552 @@
+name: Build default models
+
+on:
+  workflow_dispatch:
+    inputs:
+      target:
+        description: 'Model target to build'
+        required: true
+        type: choice
+        options:
+          - small
+          - big
+          - dm
+  workflow_call:
+    inputs:
+      target:
+        description: 'Model target to build (small, big, or dm)'
+        required: true
+        type: string
+
+concurrency:
+  group: build-default-models-${{ inputs.target }}
+  cancel-in-progress: false
+
+env:
+  HF_REPO: sunnypilot/sunnypilot_models_v1
+
+jobs:
+  resolve:
+    runs-on: ubuntu-24.04
+    outputs:
+      model_name: ${{ steps.resolve.outputs.model_name }}
+      safe_model_name: ${{ steps.resolve.outputs.safe_model_name }}
+      onnx_ref: ${{ steps.resolve.outputs.onnx_ref }}
+      onnx_path: ${{ steps.resolve.outputs.onnx_path }}
+      hf_defaults_path: ${{ steps.resolve.outputs.hf_defaults_path }}
+      tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - id: resolve
+        run: |
+          export PYTHONPATH=${{ github.workspace }}
+
+          if [ "${{ inputs.target }}" = "big" ]; then
+            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
+            HF_DEFAULTS_PATH="models/defaults/big"
+          elif [ "${{ inputs.target }}" = "dm" ]; then
+            ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
+            HF_DEFAULTS_PATH="models/defaults/dm"
+            NAME="dmonitoring_model ($(git log -1 --format=%cd --date=format:'%B %d, %Y' -- "$ONNX_PATH"))"
+          else
+            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL; print(DEFAULT_MODEL)")
+            ONNX_PATH="openpilot/selfdrive/modeld/models/driving_supercombo.onnx"
+            HF_DEFAULTS_PATH="models/defaults/small"
+          fi
+          ONNX_REF=""
+          [ -n "$ONNX_PATH" ] && ONNX_REF=$(git log -1 --format='%H' -- "$ONNX_PATH")
+
+          TINYGRAD_REF=$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)
+          if [ -z "$TINYGRAD_REF" ]; then
+            echo "::error::Failed to resolve tinygrad ref"
+            exit 1
+          fi
+
+          SAFE_NAME="${NAME// /-}"
+          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
+          echo "safe_model_name=${SAFE_NAME}" >> $GITHUB_OUTPUT
+          echo "onnx_ref=${ONNX_REF}" >> $GITHUB_OUTPUT
+          echo "onnx_path=${ONNX_PATH}" >> $GITHUB_OUTPUT
+          echo "hf_defaults_path=${HF_DEFAULTS_PATH}" >> $GITHUB_OUTPUT
+          echo "tinygrad_ref=${TINYGRAD_REF}" >> $GITHUB_OUTPUT
+
+  build_small_model:
+    needs: resolve
+    if: ${{ inputs.target == 'small' }}
+    runs-on: [self-hosted, tici]
+    env:
+      MODELS_DIR: openpilot/selfdrive/modeld/models
+      COMPILER: tinygrad_repo/examples/openpilot
+      SMALL_ONNX: openpilot/selfdrive/modeld/models/driving_supercombo.onnx
+      SMALL_PKL: openpilot/selfdrive/modeld/models/driving_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull small ONNX via LFS
+        run: git lfs pull -I "${{ env.SMALL_ONNX }}"
+
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Compile small model from ONNX
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+          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
+
+      - name: Compile driving warps (stock)
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+          MODEL_W=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(s[0])")
+          MODEL_H=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(s[1])")
+          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+          for CAM in "1928,1208" "1344,760"; do
+            CAM_W=$(echo $CAM | cut -d, -f1)
+            CAM_H=$(echo $CAM | cut -d, -f2)
+            STRIDE_Y_UV=$(python3 -c 'import sys; from openpilot.system.camerad.cameras.nv12_info import get_nv12_info; s,y,u,_=get_nv12_info(int(sys.argv[1]),int(sys.argv[2])); print(f"{s},{y},{u},{s*(y+u)}")' $CAM_W $CAM_H)
+            OUTPUT="${{ github.workspace }}/${{ env.MODELS_DIR }}/driving_warp_${CAM_W}x${CAM_H}_tinygrad.pkl"
+            env ${TG_FLAGS} python3 ${{ github.workspace }}/${{ env.COMPILER }}/compile_warp.py \
+              --frame ${CAM_W},${CAM_H},${STRIDE_Y_UV} \
+              --warp-to ${MODEL_W}x${MODEL_H} \
+              --layout yuv420 \
+              --frames 2 \
+              --output "${OUTPUT}"
+          done
+
+      - name: Chunk small pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.SMALL_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked into {len(targets)} files')
+          "
+
+      - name: Prepare output
+        env:
+          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
+          OUTPUT_DIR="${{ github.workspace }}/small_output"
+          PKL_BASE="driving_tinygrad.pkl"
+          mkdir -p "$OUTPUT_DIR"
+
+          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
+
+          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
+            --model-dir "$MODELS_DIR" \
+            --output-dir "$OUTPUT_DIR" \
+            --custom-name "$MODEL_NAME" \
+            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
+
+          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
+
+      - name: Upload small model artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
+          path: ${{ github.workspace }}/small_output/
+
+      - name: Upload artifact name file
+        uses: actions/upload-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          path: ${{ github.workspace }}/small_output/artifact_name.txt
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+
+  build_big_model:
+    needs: resolve
+    if: ${{ inputs.target == 'big' }}
+    runs-on: [self-hosted, chestnut]
+    env:
+      MODELS_DIR: openpilot/selfdrive/modeld/models
+      COMPILER: tinygrad_repo/examples/openpilot
+      BIG_PKL: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull big PKL via LFS
+        run: git lfs pull -I "${{ env.BIG_PKL }}"
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Wait for chestnut PCIe link
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+          python3 -c "
+          import time
+          from openpilot.system.hardware.chestnut.flash import link_up
+          for i in range(10):
+              if link_up():
+                  print(f'PCIe link up after {i+1} attempt(s)')
+                  break
+              time.sleep(1)
+          else:
+              raise RuntimeError('Chestnut PCIe link not ready after 10 attempts')
+          "
+
+      - name: Compile driving warps (chestnut)
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+          MODEL_W=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(s[0])")
+          MODEL_H=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(s[1])")
+          TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32"
+          for CAM in "1928,1208" "1344,760"; do
+            CAM_W=$(echo $CAM | cut -d, -f1)
+            CAM_H=$(echo $CAM | cut -d, -f2)
+            STRIDE_Y_UV=$(python3 -c 'import sys; from openpilot.system.camerad.cameras.nv12_info import get_nv12_info; s,y,u,_=get_nv12_info(int(sys.argv[1]),int(sys.argv[2])); print(f"{s},{y},{u},{s*(y+u)}")' $CAM_W $CAM_H)
+            OUTPUT="${{ github.workspace }}/${{ env.MODELS_DIR }}/big_driving_warp_${CAM_W}x${CAM_H}_tinygrad.pkl"
+            env ${TG_FLAGS} python3 ${{ github.workspace }}/${{ env.COMPILER }}/compile_warp.py \
+              --frame ${CAM_W},${CAM_H},${STRIDE_Y_UV} \
+              --warp-to ${MODEL_W}x${MODEL_H} \
+              --layout yuv420 \
+              --frames 2 \
+              --output "${OUTPUT}"
+          done
+
+      - name: Chunk big pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.BIG_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked into {len(targets)} files')
+          "
+
+      - name: Prepare output
+        env:
+          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
+          OUTPUT_DIR="${{ github.workspace }}/big_output"
+          PKL_BASE="big_driving_tinygrad.pkl"
+          mkdir -p "$OUTPUT_DIR"
+
+          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
+
+          PKL_LFS_SHA256=$(sha256sum "$MODELS_DIR/${PKL_BASE}" | cut -d' ' -f1)
+
+          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
+            --model-dir "$MODELS_DIR" \
+            --output-dir "$OUTPUT_DIR" \
+            --custom-name "$MODEL_NAME" \
+            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}" \
+            --onnx-sha256 "$PKL_LFS_SHA256"
+
+          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
+
+      - name: Upload big model artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
+          path: ${{ github.workspace }}/big_output/
+
+      - name: Upload artifact name file
+        uses: actions/upload-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          path: ${{ github.workspace }}/big_output/artifact_name.txt
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+
+  upload_defaults:
+    needs: [ resolve, build_small_model, build_big_model, build_dm_model ]
+    if: |
+      ${{
+        !cancelled() &&
+        (inputs.target == 'big' && needs.build_big_model.result == 'success' ||
+         inputs.target == 'small' && needs.build_small_model.result == 'success' ||
+         inputs.target == 'dm' && needs.build_dm_model.result == 'success')
+      }}
+    runs-on: ubuntu-24.04
+    permissions:
+      id-token: write
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Pull LFS for resolved ONNX files
+        if: ${{ needs.resolve.outputs.onnx_path != '' }}
+        run: git lfs pull -I "${{ needs.resolve.outputs.onnx_path }}"
+
+      - name: Install huggingface_hub
+        run: pip install --upgrade "huggingface_hub>=0.22.0"
+
+      - name: Download artifact name
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          path: artifact_name
+
+      - name: Read artifact name
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        id: artifact
+        run: |
+          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
+          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
+
+      - name: Download model artifact
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: ${{ steps.artifact.outputs.artifact_name }}
+          path: output
+
+      - name: Upload model to HF
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
+        run: |
+          rm -f output/artifact_name.txt
+          export PYTHONPATH=$(pwd)
+          python3 release/ci/upload_default_model.py \
+            --hf-repo "${{ env.HF_REPO }}" \
+            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
+            --artifact-name "$ARTIFACT_NAME" \
+            --model-dir output \
+            --model-name "${{ needs.resolve.outputs.model_name }}" \
+            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
+            --run-number "${{ github.run_number }}"
+
+      - name: Download DM artifact
+        if: ${{ inputs.target == 'dm' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: dm-model-${{ github.run_number }}
+          path: dm_output
+
+      - name: Generate DM metadata and upload to HF
+        if: ${{ inputs.target == 'dm' }}
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: |
+          export PYTHONPATH=$(pwd)
+          python3 -c "
+          import json, hashlib
+          from pathlib import Path
+          from datetime import datetime, UTC
+
+          dm_dir = Path('dm_output')
+          manifest = list(dm_dir.glob('*.chunkmanifest'))
+          assert manifest, 'No chunkmanifest found'
+          pkl_name = manifest[0].name.removesuffix('.chunkmanifest')
+          num_chunks = int(manifest[0].read_text().strip())
+
+          chunks = []
+          for i in range(num_chunks):
+              chunk = dm_dir / f'{pkl_name}.chunk{i+1:02d}of{num_chunks:02d}'
+              chunks.append({
+                  'file_name': chunk.name,
+                  'sha256': hashlib.sha256(chunk.read_bytes()).hexdigest()
+              })
+
+          digest = hashlib.sha256()
+          for c in chunks:
+              with open(dm_dir / c['file_name'], 'rb') as f:
+                  while block := f.read(1024*1024):
+                      digest.update(block)
+
+          metadata = {
+              'bundles': [{
+                  'short_name': 'DMMODEL',
+                  'display_name': '${{ needs.resolve.outputs.model_name }}',
+                  'ref': '${{ needs.resolve.outputs.onnx_ref }}',
+                  'runner': 'tinygrad',
+                  'build_time': datetime.now(UTC).strftime('%Y-%m-%dT%H:%M:%SZ'),
+                  'models': [{
+                      'type': 'chunked',
+                      'artifact': {
+                          'file_name': pkl_name,
+                          'download_uri': {'url': '', 'sha256': digest.hexdigest()},
+                          'chunks': chunks
+                      }
+                  }]
+              }]
+          }
+          with open(dm_dir / 'metadata.json', 'w') as f:
+              json.dump(metadata, f, indent=2)
+          print('Generated DM metadata.json')
+          "
+
+          python3 release/ci/upload_default_model.py \
+            --hf-repo "${{ env.HF_REPO }}" \
+            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
+            --artifact-name "dm-model-${{ github.run_number }}" \
+            --model-dir dm_output \
+            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
+            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
+            --model-name "${{ needs.resolve.outputs.model_name }}" \
+            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
+            --run-number "${{ github.run_number }}"
+
+  build_dm_model:
+    needs: resolve
+    if: ${{ inputs.target == 'dm' }}
+    runs-on: [self-hosted, tici]
+    env:
+      DM_ONNX: openpilot/selfdrive/modeld/models/dmonitoring_model.onnx
+      DM_PKL: openpilot/selfdrive/modeld/models/dmonitoring_model_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull DM ONNX via LFS
+        run: git lfs pull -I "${{ env.DM_ONNX }}"
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Compile DM model
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          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 \
+            ${{ github.workspace }}/${{ env.DM_ONNX }} \
+            ${{ github.workspace }}/${{ env.DM_PKL }}
+
+      - name: Chunk DM pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.DM_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked {pkl} into {len(targets)} chunks')
+          "
+
+      - name: Compile DM warp
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+          COMPILER="${{ github.workspace }}/tinygrad_repo/examples/openpilot"
+          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
+          DM_SIZE=$(python3 -c "from openpilot.common.transformations.model import DM_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
+
+          for res in $(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')"); do
+            CAM_W=$(echo $res | cut -d x -f1)
+            CAM_H=$(echo $res | cut -d x -f2)
+            STRIDE_INFO=$(python3 -c "
+          import sys
+          from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
+          s,y,u,sz = get_nv12_info(int(sys.argv[1]), int(sys.argv[2]))
+          print(f'{s},{y},{u},{sz}')
+          " $CAM_W $CAM_H)
+            WARP_PKL="${MODELS_DIR}/dm_warp_${res}_tinygrad.pkl"
+            taskset -c 7 env ${TG_FLAGS} python3 "${COMPILER}/compile_warp.py" \
+              --frame ${CAM_W},${CAM_H},${STRIDE_INFO} \
+              --warp-to ${DM_SIZE} \
+              --layout luma \
+              --border-fill 16 \
+              --transform-device NPY \
+              --output "${WARP_PKL}"
+          done
+
+      - name: Prepare DM output
+        run: |
+          mkdir -p dm_output
+          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunk* dm_output/
+          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunkmanifest dm_output/
+          cp ${{ github.workspace }}/openpilot/selfdrive/modeld/models/dm_warp_* dm_output/
+
+      - name: Upload DM artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: dm-model-${{ github.run_number }}
+          path: dm_output/
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+

.github/workflows/build-single-tinygrad-model.yaml

@@ -29,11 +29,29 @@ on:
         required: false
         type: boolean
         default: true
-      bypass_push:
-        description: 'Bypass pushing to GitLab for build-all'
+      target_hardware:
+        description: 'Hardware target to compile for (qcom or chestnut)'
         required: false
-        default: true
-        type: boolean
+        type: string
+        default: 'qcom'
+      hf_repo:
+        description: 'Hugging Face dataset repository (e.g. sunnypilot/sunnypilot_models_v1)'
+        required: false
+        type: string
+        default: 'sunnypilot/sunnypilot_models_v1'
+      docs_repo:
+        description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
+        required: false
+        type: string
+        default: 'sunnypilot/sunnypilot-models'
+      set_min_version:
+        description: 'Minimum selector version'
+        required: false
+        type: string
+      tinygrad_ref:
+        description: 'Tinygrad reference'
+        required: false
+        type: string
   workflow_dispatch:
     inputs:
       upstream_branch:
@@ -65,8 +83,8 @@ on:
           - None
           - Master Models
           - Release Models
-          - 2025 World Models
           - 2026 World Models
+          - 2026 Deep RL Models
           - Custom Merge Models
           - Other
       custom_model_folder:
@@ -81,9 +99,27 @@ on:
         description: 'Minimum selector version'
         required: false
         type: string
+      target_hardware:
+        description: 'Hardware target to compile for'
+        required: false
+        type: choice
+        default: 'qcom'
+        options:
+          - qcom
+          - chestnut
+      hf_repo:
+        description: 'Hugging Face dataset repository'
+        required: false
+        type: string
+        default: 'sunnypilot/sunnypilot_models_v1'
+      docs_repo:
+        description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
+        required: false
+        type: string
+        default: 'sunnypilot/sunnypilot-models'
 env:
   RECOMPILED_DIR: recompiled${{ inputs.recompiled_dir }}
-  JSON_FILE: docs/docs/driving_models_v${{ inputs.json_version }}.json
+  JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_v' || 'v' }}${{ inputs.json_version }}.json
 
 jobs:
   build_model:
@@ -93,56 +129,45 @@ jobs:
       custom_name: ${{ inputs.custom_name || inputs.upstream_branch }}
       is_20hz: ${{ inputs.is_20hz }}
       artifact_suffix: ${{ inputs.artifact_suffix }}
+      target_hardware: ${{ inputs.target_hardware }}
     secrets: inherit
 
   publish_model:
-    if: ${{ !inputs.bypass_push && !cancelled() }}
+    if: ${{ !cancelled() && needs.build_model.result == 'success' }}
     concurrency:
-      group: gitlab-push-${{ inputs.recompiled_dir }}
+      group: hf-push-${{ inputs.recompiled_dir }}
       cancel-in-progress: false
     needs: build_model
     runs-on: ubuntu-latest
+    permissions:
+      id-token: write
+      contents: write
     steps:
-      - name: Set up SSH
-        uses: webfactory/ssh-agent@v0.9.0
-        with:
-          ssh-private-key: ${{ secrets.GITLAB_SSH_PRIVATE_KEY }}
-
-      - name: Add GitLab.com SSH key to known_hosts
-        run: |
-          mkdir -p ~/.ssh
-          ssh-keyscan -H gitlab.com >> ~/.ssh/known_hosts
-
-      - name: Clone GitLab docs repo
-        env:
-          GIT_SSH_COMMAND: 'ssh -o UserKnownHostsFile=~/.ssh/known_hosts'
-        run: |
-          echo "Cloning GitLab"
-          git clone --depth 1 --filter=tree:0 --sparse git@gitlab.com:sunnypilot/public/${{ vars.MODELS_GITLAB }} gitlab_docs
-          cd gitlab_docs
-          echo "checkout models/${RECOMPILED_DIR}"
-          git sparse-checkout set --no-cone models/${RECOMPILED_DIR}
-          git checkout main
-          cd ..
-
       - name: Checkout docs repo
         uses: actions/checkout@v4
         with:
-          repository: sunnypilot/sunnypilot-models
+          repository: ${{ inputs.docs_repo }}
           ref: gh-pages
           path: docs
           ssh-key: ${{ secrets.CI_SUNNYPILOT_DOCS_PRIVATE_KEY }}
 
-      - name: Validate recompiled dir and JSON version
+      - name: Install huggingface_hub
+        run: pip install --upgrade "huggingface_hub>=0.22.0"
+
+      - name: Validate hf_repo and JSON version
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
         run: |
-          if [ ! -d "gitlab_docs/models/$RECOMPILED_DIR" ]; then
-            echo "Recompiled dir $RECOMPILED_DIR does not exist in GitLab repo"
-            exit 1
-          fi
           if [ ! -f "$JSON_FILE" ]; then
             echo "JSON file $JSON_FILE does not exist!"
             exit 1
           fi
+          python3 -c "
+          import sys
+          from huggingface_hub import HfApi
+          HfApi().repo_info(repo_id=sys.argv[1], repo_type='dataset')
+          print(f'Success: Repo {sys.argv[1]} exists.')
+          " "${{ inputs.hf_repo }}"
 
       - name: Download artifact name file
         uses: actions/download-artifact@v4
@@ -162,49 +187,26 @@ jobs:
           name: ${{ steps.read-artifact-name.outputs.artifact_name }}
           path: output
 
-      - name: Remove unwanted files
-        run: |
-          find output -type f -name 'dmonitoring_model_tinygrad.pkl' -delete
-          find output -type f -name 'dmonitoring_model.onnx' -delete
-
-      - name: Copy model artifact(s) to GitLab recompiled dir
+      - name: Create models folder
         env:
           ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
         run: |
-          ARTIFACT_DIR="gitlab_docs/models/${RECOMPILED_DIR}/${ARTIFACT_NAME}"
-          mkdir -p "$ARTIFACT_DIR"
-          for path in output/*; do
-            if [ "$(basename "$path")" = "artifact_name.txt" ]; then
-              continue
-            fi
-            name="$(basename "$path")"
-            if [ -d "$path" ]; then
-              mkdir -p "$ARTIFACT_DIR/$name"
-              cp -r "$path"/* "$ARTIFACT_DIR/$name/"
-              echo "Copied dir $name -> $ARTIFACT_DIR/$name"
-            else
-              cp "$path" "$ARTIFACT_DIR/"
-              echo "Copied file $name -> $ARTIFACT_DIR/"
-            fi
-          done
+          mkdir -p "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}"
+          cp -r output/* "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/"
+          rm -f "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/artifact_name.txt"
 
-      - name: Push recompiled dir to GitLab
+      - name: Upload to Hugging Face
         env:
-          GITLAB_SSH_PRIVATE_KEY: ${{ secrets.GITLAB_SSH_PRIVATE_KEY }}
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
         run: |
-          cd gitlab_docs
-          git checkout main
-          git pull origin main
-          for d in models/"$RECOMPILED_DIR"/*/; do
-            git sparse-checkout add "$d"
-          done
-          git add models/"$RECOMPILED_DIR"
-          git config --global user.name "GitHub Action"
-          git config --global user.email "action@github.com"
-          git commit -m "Create/Update $RECOMPILED_DIR with new/updated model from build-single-tinygrad-model" || echo "No changes to commit"
-          git push origin main
+          hf upload ${{ inputs.hf_repo }} \
+            output/ \
+            "models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/" \
+            --repo-type=dataset
 
-      - run: |
+      - name: Pull gh-pages
+        run: |
           cd docs
           git pull origin gh-pages
 
@@ -220,9 +222,11 @@ jobs:
           fi
           [ -n "${{ inputs.generation }}" ] && ARGS="$ARGS --generation \"${{ inputs.generation }}\""
           [ -n "${{ inputs.version }}" ] && ARGS="$ARGS --version \"${{ inputs.version }}\""
+          [ -n "${{ inputs.set_min_version }}" ] && ARGS="$ARGS --set-min-version \"${{ inputs.set_min_version }}\""
+          [ -n "${{ inputs.tinygrad_ref }}" ] && ARGS="$ARGS --tinygrad-ref \"${{ inputs.tinygrad_ref }}\""
           eval python3 docs/json_parser.py \
             --json-path "$JSON_FILE" \
-            --recompiled-dir "gitlab_docs/models/$RECOMPILED_DIR" \
+            --recompiled-dir "local_models/$RECOMPILED_DIR" \
             --sort-by-date \
             $ARGS
 

.github/workflows/compile-warp-kernels.yaml

@@ -0,0 +1,73 @@
+name: Compile warp for sunnypilot modeld
+
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: '0 0 * * 0'
+
+jobs:
+  compile_warps:
+    runs-on: [self-hosted, chestnut]
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Compile Warp Kernels
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+          mkdir -p openpilot/sunnypilot/modeld_v2/models/
+          MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
+          CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
+          echo "Model size: $MODEL_SIZE"
+          echo "Camera resolutions: $CAMERA_RES"
+
+          for res in $CAMERA_RES; do
+            NV12_INFO=$(python3 -c "from openpilot.system.camerad.cameras.nv12_info import get_nv12_info; w, h = map(int, '${res}'.split('x')); print(','.join(map(str, get_nv12_info(w, h))))")
+
+            WARP_PKL="openpilot/sunnypilot/modeld_v2/models/driving_warp_${res}_tinygrad.pkl"
+            echo "Compiling $WARP_PKL on QCOM"
+            taskset -c 7 env DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1 python3 tinygrad_repo/examples/openpilot/compile_warp.py \
+              --frame ${res/x/,},${NV12_INFO} --warp-to ${MODEL_SIZE} --layout yuv420 --frames 2 --output "${WARP_PKL}"
+
+            BIG_WARP_PKL="openpilot/sunnypilot/modeld_v2/models/big_driving_warp_${res}_tinygrad.pkl"
+            echo "Compiling $BIG_WARP_PKL on AMD"
+            taskset -c 7 env DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32 python3 tinygrad_repo/examples/openpilot/compile_warp.py \
+              --frame ${res/x/,},${NV12_INFO} --warp-to ${MODEL_SIZE} --layout yuv420 --frames 2 --output "${BIG_WARP_PKL}"
+          done
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+
+      - name: Create Pull Request
+        uses: peter-evans/create-pull-request@9153d834b60caba6d51c9b9510b087acf9f33f83
+        with:
+          author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
+          token: ${{ secrets.GITHUB_TOKEN }}
+          commit-message: "[bot] Update warp pkl for modeld_v2"
+          title: "[bot] Update modeld_v2 Warp"
+          branch: "auto/compile-warp-kernels"
+          base: "master"
+          delete-branch: true
+          labels: bot
+          add-paths: |
+            openpilot/sunnypilot/modeld_v2/models/*.pkl

.github/workflows/docs.yaml

@@ -18,24 +18,25 @@ concurrency:
 env:
   GIT_CONFIG_COUNT: 1
   GIT_CONFIG_KEY_0: lfs.fetchexclude
-  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
 
 jobs:
   docs:
     name: build docs
-    runs-on: ubuntu-24.04
+    runs-on: ${{
+      (github.repository == 'commaai/openpilot') &&
+      ((github.event_name != 'pull_request') ||
+      (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))
+      && fromJSON('["namespace-profile-amd64-8x16"]')
+      || fromJSON('["ubuntu-24.04"]') }}
     steps:
     - uses: commaai/timeout@v1
-
     - uses: actions/checkout@v7
-      with:
-        submodules: true
+    - run: ./tools/op.sh setup
 
     # Build
     - name: Build docs
-      run: |
-        git lfs pull
-        python docs/serve.py --build
+      run: ./tools/op.sh docs --build
 
     # Push to docs.comma.ai
     - uses: actions/checkout@v7

.github/workflows/download-hf-model-chunks/action.yml

@@ -0,0 +1,73 @@
+name: Download HF model chunks
+description: Resolve and download model chunks from HuggingFace in parallel
+
+inputs:
+  hf_repo:
+    description: HuggingFace dataset repo
+    required: true
+  models:
+    description: 'JSON array of {hf_path, onnx_hash, canonical} objects'
+    required: true
+  dest_dir:
+    description: Destination directory for downloaded chunks
+    required: true
+
+runs:
+  using: composite
+  steps:
+    - name: Download model chunks
+      shell: bash
+      env:
+        HF_REPO: ${{ inputs.hf_repo }}
+        MODELS_JSON: ${{ inputs.models }}
+        DEST_DIR: ${{ inputs.dest_dir }}
+      run: |
+        set -eo pipefail
+        DOWNLOAD_LIST=$(mktemp)
+
+        resolve_chunks() {
+          local HF_PATH="$1" ONNX_HASH="$2" CANONICAL="$3" DEST_DIR="$4"
+          local JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_PATH}/default_models.json"
+          local DEFAULTS BUNDLE ARTIFACT BASE_URL NUM_CHUNKS
+          DEFAULTS=$(curl -fsSL "$JSON_URL")
+          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
+          ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
+          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
+          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
+
+          mkdir -p "$DEST_DIR"
+          while IFS= read -r CHUNK_NAME; do
+            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+' || true)
+            if [ -z "$CHUNK_IDX" ]; then
+              echo "::error::Failed to parse chunk index from: $CHUNK_NAME"
+              return 1
+            fi
+            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
+            printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${CANONICAL}.chunk${CHUNK_IDX}" >> "$DOWNLOAD_LIST"
+          done < <(echo "$ARTIFACT" | jq -r '.chunks[].file_name')
+          echo "$NUM_CHUNKS" > "${DEST_DIR}/${CANONICAL}.chunkmanifest"
+
+          if [ "$CANONICAL" = "dmonitoring_model_tinygrad.pkl" ]; then
+            for warp in dm_warp_1928x1208_tinygrad.pkl dm_warp_1344x760_tinygrad.pkl; do
+              ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${warp}', safe=':/'))")
+              printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${warp}" >> "$DOWNLOAD_LIST"
+            done
+          fi
+        }
+
+        echo "$MODELS_JSON" | jq -c '.[]' | while IFS= read -r model; do
+          HF_PATH=$(echo "$model" | jq -r '.hf_path')
+          ONNX_HASH=$(echo "$model" | jq -r '.onnx_hash')
+          CANONICAL=$(echo "$model" | jq -r '.canonical')
+          resolve_chunks "$HF_PATH" "$ONNX_HASH" "$CANONICAL" "$DEST_DIR"
+        done
+
+        TOTAL=$(wc -l < "$DOWNLOAD_LIST")
+        echo "Downloading $TOTAL chunks with 8 parallel connections..."
+        xargs -P8 -d'\n' -I{} bash -c '
+          URL="${1%%	*}"
+          DEST="${1#*	}"
+          echo "Downloading $(basename "$DEST")"
+          curl -fsSL --retry 3 --retry-delay 5 -o "$DEST" "$URL"
+        ' _ {} < "$DOWNLOAD_LIST"
+        rm -f "$DOWNLOAD_LIST"

.github/workflows/release-drafter.yml

@@ -1,28 +0,0 @@
-name: Release Drafter
-
-on:
-  push:
-    branches:
-      - master
-    tags:
-      - 'v*'
-  pull_request_target:
-    types: [opened, reopened, synchronize]
-  workflow_dispatch:
-
-permissions:
-  contents: read
-
-jobs:
-  update_release_draft:
-    permissions:
-      contents: write
-      pull-requests: write
-    runs-on: ubuntu-latest
-    steps:
-      - uses: release-drafter/release-drafter@v6
-        with:
-          config-name: release-drafter.yml
-          prerelease: ${{ !startsWith(github.ref, 'refs/tags/v') }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/release.yaml

@@ -7,7 +7,7 @@ on:
 env:
   GIT_CONFIG_COUNT: 1
   GIT_CONFIG_KEY_0: lfs.fetchexclude
-  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
 
 jobs:
   build___nightly:
@@ -34,3 +34,7 @@ jobs:
     - run: ./tools/op.sh setup
     - name: Push __nightly
       run: BRANCH=__nightly tools/release/build_stripped.sh
+    - name: Push chestnut nightly
+      run: |
+        git lfs pull --exclude=''
+        INCLUDE_BIG_MODEL=1 BRANCH=__nightly-chestnut tools/release/build_stripped.sh

.github/workflows/repo-maintenance.yaml

@@ -11,7 +11,7 @@ env:
   PYTHONPATH: ${{ github.workspace }}
   GIT_CONFIG_COUNT: 1
   GIT_CONFIG_KEY_0: lfs.fetchexclude
-  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
 
 jobs:
   package_updates:

.github/workflows/sunnypilot-build-model.yaml

@@ -31,7 +31,7 @@ on:
         type: string
         default: ''
       target_hardware:
-        description: 'Hardware target to compile for (qcom or usbgpu)'
+        description: 'Hardware target to compile for (qcom or chestnut)'
         required: false
         type: string
         default: 'qcom'
@@ -57,7 +57,7 @@ on:
         type: choice
         options:
           - qcom
-          - usbgpu
+          - chestnut
         default: 'qcom'
 
 
@@ -80,6 +80,7 @@ jobs:
         with:
           repository: commaai/openpilot
           ref: ${{ inputs.upstream_branch }}
+          fetch-depth: 1
           submodules: recursive
           path: openpilot
 
@@ -89,26 +90,40 @@ jobs:
         with:
           repository: sunnypilot/sunnypilot
           ref: ${{ inputs.upstream_branch }}
+          fetch-depth: 1
           submodules: recursive
           path: openpilot
       - name: Get commit date
         id: commit-date
         run: |
-          cd ${{ github.workspace }}/openpilot
+          cd ${{ github.workspace }}/openpilot/openpilot
           commit_date=$(git log -1 --format=%cd --date=format:'%B %d, %Y')
           echo "model_date=${commit_date}" >> $GITHUB_OUTPUT
           cat $GITHUB_OUTPUT
       - run: |
-          cd ${{ github.workspace }}/openpilot
-          git lfs pull
+          cd ${{ github.workspace }}/openpilot/openpilot
+          if [ "${{ inputs.target_hardware }}" != "chestnut" ]; then
+            git lfs pull -X "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/dmonitoring_*.onnx,**/selfdrive/modeld/models/big_*.pkl,**/selfdrive/modeld/models/dmonitoring_*.pkl"
+            rm -f selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/dmonitoring_*.onnx selfdrive/modeld/models/big_*.pkl selfdrive/modeld/models/dmonitoring_*.pkl
+          else
+            git lfs pull -I "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/big_*.pkl" -X ""
+            find selfdrive/modeld/models -type f \( -name "*.onnx" -o -name "*.pkl" \) ! -name "big_*.onnx" ! -name "big_*.pkl" -delete
+          fi
+          if grep -lIF "version https://git-lfs.github.com/spec/v1" selfdrive/modeld/models/*.onnx selfdrive/modeld/models/*.pkl 2>/dev/null; then
+            echo "::error::the ONNX or PKL files above are still LFS pointers, not real models"
+            exit 1
+          fi
       - name: 'Upload Artifact'
         uses: actions/upload-artifact@v4
         with:
           name: models-${{ env.REF }}${{ inputs.artifact_suffix  }}
-          path: ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
+          path: |
+            ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
+            ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.pkl
+          if-no-files-found: error
 
   build_model:
-    runs-on: [self-hosted, tici]
+    runs-on: [self-hosted, "${{ inputs.target_hardware == 'chestnut' && 'chestnut' || 'tici' }}"]
     needs: get_model
     env:
       MODEL_NAME: ${{ inputs.custom_name || inputs.upstream_branch }} (${{ needs.get_model.outputs.model_date }})
@@ -116,24 +131,9 @@ jobs:
     steps:
       - uses: actions/checkout@v4
         with:
+          fetch-depth: 1
           submodules: recursive
 
-      - run: git lfs pull
-      - name: Cache SCons
-        uses: actions/cache@v4
-        with:
-          path: ${{env.SCONS_CACHE_DIR}}
-          key: scons-${{ runner.os }}-${{ runner.arch }}-${{ github.head_ref || github.ref_name }}-model-${{ github.sha }}
-          # Note: GitHub Actions enforces cache isolation between different build sources (PR builds, workflow dispatches, etc.)
-          #   for security. Only caches from the default branch are shared across all builds. This is by design and cannot be overridden.
-          restore-keys: |
-            scons-${{ runner.os }}-${{ runner.arch }}-${{ github.head_ref || github.ref_name }}-model
-            scons-${{ runner.os }}-${{ runner.arch }}-${{ github.head_ref || github.ref_name }}
-            scons-${{ runner.os }}-${{ runner.arch }}-${{ env.MASTER_NEW_BRANCH }}-model
-            scons-${{ runner.os }}-${{ runner.arch }}-${{ env.MASTER_BRANCH }}-model
-            scons-${{ runner.os }}-${{ runner.arch }}-${{ env.MASTER_NEW_BRANCH }}
-            scons-${{ runner.os }}-${{ runner.arch }}-${{ env.MASTER_BRANCH }}
-            scons-${{ runner.os }}-${{ runner.arch }}
 
       - name: Set environment variables
         id: set-env
@@ -144,7 +144,7 @@ jobs:
           export UV_PYTHON_PREFERENCE=managed
           export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
           export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
-          uv sync
+          uv sync --frozen
           printenv >> $GITHUB_ENV
           if [[ "${{ runner.debug }}" == "1" ]]; then
             cat $GITHUB_OUTPUT
@@ -166,15 +166,13 @@ jobs:
           fi
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
-          rm -rf ${{ env.MODELS_DIR }}/*.onnx
+          rm -rf ${{ env.MODELS_DIR }}/*.onnx*
 
       - name: Download model artifacts
         uses: actions/download-artifact@v4
         with:
           name: models-${{ env.REF }}${{ inputs.artifact_suffix }}
           path: ${{ env.MODELS_DIR }}
-      - run: |
-          rm -f ${{ env.MODELS_DIR }}/{dmonitoring_model,big_driving_policy,big_driving_vision,big_driving_supercombo}.onnx
 
       - name: Build Model
         run: |
@@ -188,62 +186,87 @@ jobs:
           MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
           CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
 
-          if [ "${{ inputs.target_hardware }}" == "usbgpu" ]; then
-            echo "USBGPU build"
-            export USBGPU=1
-            TG_FLAGS="DEV=AMD USBGPU=1 IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+          TG_FLAGS_QCOM="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+          if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
+            echo "CHESTNUT build"
+            export CHESTNUT=1
+            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1"
             OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
           else
             echo "QCOM build"
-            TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+            TG_FLAGS="$TG_FLAGS_QCOM"
             OUTPUT_PKL="${{ env.MODELS_DIR }}/driving_tinygrad.pkl"
           fi
 
-          # Generate metadata for all ONNX files
-          find "${{ env.MODELS_DIR }}" -maxdepth 1 -name '*.onnx' | while IFS= read -r onnx_file; do
-            echo "Generating metadata: $onnx_file"
-            env ${TG_FLAGS} python3 "${{ env.MODELS_DIR }}/../get_model_metadata.py" "$onnx_file" || true
-          done
+          NATIVE_PKL=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "*.pkl" -print -quit)
 
-          # Detect model type and build compile args
-          VISION_ONNX="${{ env.MODELS_DIR }}/driving_vision.onnx"
-          POLICY_ONNX="${{ env.MODELS_DIR }}/driving_policy.onnx"
-          OFF_POLICY_ONNX="${{ env.MODELS_DIR }}/driving_off_policy.onnx"
-          ON_POLICY_ONNX="${{ env.MODELS_DIR }}/driving_on_policy.onnx"
-          SUPERCOMBO_ONNX=""
-          for f in "${{ env.MODELS_DIR }}/supercombo.onnx" "${{ env.MODELS_DIR }}/driving_supercombo.onnx"; do
-            if [ -f "$f" ]; then
-              SUPERCOMBO_ONNX="$f"
-              break
+          if [ -n "$NATIVE_PKL" ]; then
+            echo "Found native precompiled pkl: $NATIVE_PKL"
+            if [ "$NATIVE_PKL" != "$OUTPUT_PKL" ]; then
+              mv "$NATIVE_PKL" "$OUTPUT_PKL"
             fi
-          done
+            echo "Chunking pkl"
+            python3 -c "from openpilot.common.file_chunker import chunk_file, get_chunk_targets; import os; p='$OUTPUT_PKL'; chunk_file(p, get_chunk_targets(p, os.path.getsize(p)))"
+          else
+            # Generate metadata for all ONNX files
+            find "${{ env.MODELS_DIR }}" -maxdepth 1 -name '*.onnx' | while IFS= read -r onnx_file; do
+              echo "Generating metadata: $onnx_file"
+              env ${TG_FLAGS_QCOM} python3 "${{ env.MODELS_DIR }}/../get_model_metadata.py" "$onnx_file" || true
+            done
 
-          MODEL_TYPE="" ONNX_ARGS="" OUTPUT_NAME=""
-          if [ -f "$VISION_ONNX" ]; then
-            ONNX_ARGS="--vision-onnx $VISION_ONNX"
-            if [ -f "$ON_POLICY_ONNX" ] && [ -f "$OFF_POLICY_ONNX" ]; then
-              MODEL_TYPE=vision_multi_policy
-              ONNX_ARGS="$ONNX_ARGS --off-policy-onnx $OFF_POLICY_ONNX --on-policy-onnx $ON_POLICY_ONNX"
-            elif [ -f "$OFF_POLICY_ONNX" ] && [ -f "$POLICY_ONNX" ]; then
-              MODEL_TYPE=vision_multi_policy
-              ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX --off-policy-onnx $OFF_POLICY_ONNX"
-            elif [ -f "$POLICY_ONNX" ]; then
-              MODEL_TYPE=vision_policy
-              ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX"
+            # Detect model type and build compile args
+            VISION_ONNX=""
+            for f in "${{ env.MODELS_DIR }}/driving_vision.onnx" "${{ env.MODELS_DIR }}/big_driving_vision.onnx"; do
+              [ -f "$f" ] && VISION_ONNX="$f" && break
+            done
+
+            POLICY_ONNX=""
+            for f in "${{ env.MODELS_DIR }}/driving_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_policy.onnx"; do
+              [ -f "$f" ] && POLICY_ONNX="$f" && break
+            done
+
+            OFF_POLICY_ONNX=""
+            for f in "${{ env.MODELS_DIR }}/driving_off_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_off_policy.onnx"; do
+              [ -f "$f" ] && OFF_POLICY_ONNX="$f" && break
+            done
+
+            ON_POLICY_ONNX=""
+            for f in "${{ env.MODELS_DIR }}/driving_on_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_on_policy.onnx"; do
+              [ -f "$f" ] && ON_POLICY_ONNX="$f" && break
+            done
+
+            SUPERCOMBO_ONNX=""
+            for f in "${{ env.MODELS_DIR }}/supercombo.onnx" "${{ env.MODELS_DIR }}/driving_supercombo.onnx" "${{ env.MODELS_DIR }}/big_supercombo.onnx" "${{ env.MODELS_DIR }}/big_driving_supercombo.onnx"; do
+              [ -f "$f" ] && SUPERCOMBO_ONNX="$f" && break
+            done
+
+            MODEL_TYPE="" ONNX_ARGS="" OUTPUT_NAME=""
+            if [ -f "$VISION_ONNX" ]; then
+              ONNX_ARGS="--vision-onnx $VISION_ONNX"
+              if [ -f "$ON_POLICY_ONNX" ] && [ -f "$OFF_POLICY_ONNX" ]; then
+                MODEL_TYPE=vision_multi_policy
+                ONNX_ARGS="$ONNX_ARGS --off-policy-onnx $OFF_POLICY_ONNX --on-policy-onnx $ON_POLICY_ONNX"
+              elif [ -f "$OFF_POLICY_ONNX" ] && [ -f "$POLICY_ONNX" ]; then
+                MODEL_TYPE=vision_multi_policy
+                ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX --off-policy-onnx $OFF_POLICY_ONNX"
+              elif [ -f "$POLICY_ONNX" ]; then
+                MODEL_TYPE=vision_policy
+                ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX"
+              fi
+            elif [ -f "$SUPERCOMBO_ONNX" ]; then
+              MODEL_TYPE=supercombo
+              ONNX_ARGS="--supercombo-onnx $SUPERCOMBO_ONNX"
             fi
-          elif [ -f "$SUPERCOMBO_ONNX" ]; then
-            MODEL_TYPE=supercombo
-            ONNX_ARGS="--supercombo-onnx $SUPERCOMBO_ONNX"
-          fi
 
-          if [ -n "$MODEL_TYPE" ]; then
-            echo "Detected: $MODEL_TYPE -> $OUTPUT_PKL"
-            env ${TG_FLAGS} python3 "$COMPILE_MODELD" \
-              --model-type $MODEL_TYPE \
-              --model-size $MODEL_SIZE \
-              --camera-resolutions $CAMERA_RES \
-              $ONNX_ARGS \
-              --output "$OUTPUT_PKL"
+            if [ -n "$MODEL_TYPE" ]; then
+              echo "Detected: $MODEL_TYPE -> $OUTPUT_PKL"
+              env ${TG_FLAGS} python3 "$COMPILE_MODELD" \
+                --model-type $MODEL_TYPE \
+                --model-size $MODEL_SIZE \
+                --camera-resolutions $CAMERA_RES \
+                $ONNX_ARGS \
+                --output "$OUTPUT_PKL"
+            fi
           fi
 
       - name: Prepare Output
@@ -254,10 +277,8 @@ jobs:
           # Copy the model files
           rsync -avm \
             --include='*.dlc' \
-            --include='*.pkl' \
             --include='*.chunk*' \
             --include='*.chunkmanifest' \
-            --include='*.onnx' \
             --exclude='*' \
             --delete-excluded \
             --chown=comma:comma \

.github/workflows/sunnypilot-build-prebuilt.yaml

@@ -4,12 +4,8 @@ env:
   BUILD_DIR: "/data/openpilot"
   OUTPUT_DIR: ${{ github.workspace }}/output
   CI_DIR: ${{ github.workspace }}/release/ci
-  SCONS_CACHE_DIR: ${{ github.workspace }}/release/ci/scons_cache
   PUBLIC_REPO_URL: "https://github.com/sunnypilot/sunnypilot"
 
-  # Branch configurations
-  STAGING_SOURCE_BRANCH: 'master'
-
   # Runtime configuration
   SOURCE_BRANCH: "${{ github.head_ref || github.ref_name }}"
 
@@ -40,8 +36,11 @@ jobs:
       publish_concurrency_group: ${{ steps.strategy.outputs.publish_concurrency_group }}
       is_stable_branch: ${{ steps.strategy.outputs.is_stable_branch }}
       build: ${{ steps.strategy.outputs.build }}
+      include_big_model: ${{ steps.strategy.outputs.include_big_model }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
       - name: Extract deploy strategy
         id: strategy
         run: |
@@ -82,6 +81,9 @@ jobs:
             stable_version=$(cat openpilot/sunnypilot/common/version.h | grep SUNNYPILOT_VERSION | sed -e 's/[^0-9|.]//g');
             echo "version=$([ "$is_stable_branch" = "true" ] && echo "$stable_version" || echo "$BUILD")" >> $GITHUB_OUTPUT
             echo "extra_version_identifier=${environment}" >> $GITHUB_OUTPUT
+
+            include_big_model="$(echo "$CONFIG" | jq -r '.include_big_model // false')";
+            echo "include_big_model=$include_big_model" >> $GITHUB_OUTPUT
           fi
           echo "build=$BUILD" >> $GITHUB_OUTPUT
           cat $GITHUB_OUTPUT
@@ -96,6 +98,8 @@ jobs:
       }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
       - name: Wait for Tests
         uses: ./.github/workflows/wait-for-action # Path to where you place the action
         with:
@@ -109,11 +113,6 @@ jobs:
       group: build-${{ github.head_ref || github.ref_name }}
       cancel-in-progress: false
     runs-on: [self-hosted, tici]
-    outputs:
-      new_branch: ${{ needs.prepare_strategy.outputs.new_branch }}
-      version: ${{ needs.prepare_strategy.outputs.version }}
-      extra_version_identifier: ${{ needs.prepare_strategy.outputs.extra_version_identifier }}
-      commit_sha: ${{ github.sha }}
     if: ${{
       (always() && !cancelled() && !failure()) &&
       needs.prepare_strategy.result == 'success' &&
@@ -124,31 +123,14 @@ jobs:
     steps:
       - uses: actions/checkout@v4
         with:
+          fetch-depth: 1
           submodules: recursive
           ref: ${{ env.SOURCE_BRANCH }}
           repository: ${{ github.event.pull_request.head.repo.fork && github.event.pull_request.head.repo.full_name || github.repository }}
       - run: git lfs pull
 
-      - name: Cache SCons
-        uses: actions/cache@v4
-        with:
-          path: ${{env.SCONS_CACHE_DIR}}
-          key: scons-${{ runner.os }}-${{ runner.arch }}-${{ env.SOURCE_BRANCH }}-${{ github.sha }}
-          # Note: GitHub Actions enforces cache isolation between different build sources (PR builds, workflow dispatches, etc.)
-          #   for security. Only caches from the default branch are shared across all builds. This is by design and cannot be overridden.
-          restore-keys: |
-            scons-${{ runner.os }}-${{ runner.arch }}-${{ env.SOURCE_BRANCH }}
-            scons-${{ runner.os }}-${{ runner.arch }}-${{ env.STAGING_SOURCE_BRANCH }}
-            scons-${{ runner.os }}-${{ runner.arch }}
-
       - name: Set environment variables
-        id: set-env
         run: |
-          echo "new_branch=${{ needs.prepare_strategy.outputs.new_branch }}" >> $GITHUB_OUTPUT
-          echo "version=${{ needs.prepare_strategy.outputs.version }}" >> $GITHUB_OUTPUT
-          echo "extra_version_identifier=${{ needs.prepare_strategy.outputs.extra_version_identifier }}" >> $GITHUB_OUTPUT
-          echo "commit_sha=${{ github.sha }}" >> $GITHUB_OUTPUT
-
           # Set up common environment
           source /etc/profile;
           export UV_PROJECT_ENVIRONMENT=${HOME}/venv
@@ -157,9 +139,6 @@ jobs:
           export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
           uv sync
           printenv >> $GITHUB_ENV
-          if [[ "${{ runner.debug }}" == "1" ]]; then
-            cat $GITHUB_OUTPUT
-          fi
 
       - name: Setup build environment
         run: |
@@ -168,7 +147,7 @@ jobs:
           echo "Starting build stage..."
           echo "BUILD_DIR: ${BUILD_DIR}"
           echo "CI_DIR: ${CI_DIR}"
-          echo "VERSION: ${{ steps.set-env.outputs.version }}"
+          echo "VERSION: ${{ needs.prepare_strategy.outputs.version }}"
           echo "UV_PROJECT_ENVIRONMENT: ${UV_PROJECT_ENVIRONMENT}"
           echo "VIRTUAL_ENV: ${VIRTUAL_ENV}"
           echo "-------"
@@ -180,61 +159,44 @@ jobs:
 
       - name: Build Main Project
         run: |
-          export PYTHONPATH="$BUILD_DIR"
-          ./tools/release/release_files.py | sort | uniq | rsync -rRl${RUNNER_DEBUG:+v} --files-from=- . $BUILD_DIR/
+          export PYTHONPATH="$BUILD_DIR:$BUILD_DIR/msgq_repo:$BUILD_DIR/opendbc_repo:$BUILD_DIR/rednose_repo:$BUILD_DIR/teleoprtc_repo:$BUILD_DIR/tinygrad_repo"
+          ./tools/release/release_files.py | xargs -0 cp -pR --parents -t "$BUILD_DIR" --
+          # outside the checkout, which is wiped each run. /data/scons_cache is the device's, not ours.
+          SCONS_CACHE="$RUNNER_WORKSPACE/scons_cache"
+          mkdir -p "$SCONS_CACHE"
           cd $BUILD_DIR
-          ln -sfn msgq_repo/msgq msgq
-          ln -sfn opendbc_repo/opendbc opendbc
-          ln -sfn rednose_repo/rednose rednose
-          ln -sfn teleoprtc_repo/teleoprtc teleoprtc
-          ln -sfn tinygrad_repo/tinygrad tinygrad
-          sed -i '/from .board.jungle import PandaJungle, PandaJungleDFU/s/^/#/' panda/__init__.py
-          echo "Building sunnypilot's modeld_v2..."
-          scons -j$(nproc) cache_dir=${{env.SCONS_CACHE_DIR}} --minimal openpilot/sunnypilot/modeld_v2
-          echo "Building sunnypilot's locationd..."
-          scons -j2 cache_dir=${{env.SCONS_CACHE_DIR}} --minimal openpilot/sunnypilot/selfdrive/locationd
-          echo "Building openpilot's locationd..."
-          scons -j1 cache_dir=${{env.SCONS_CACHE_DIR}} --minimal openpilot/selfdrive/locationd
+          echo "Building locationd..."
+          # -j1: parallel rednose generators OOM the device
+          scons -j1 cache_dir="$SCONS_CACHE" --minimal \
+            openpilot/selfdrive/locationd openpilot/sunnypilot/selfdrive/locationd
           echo "Building rest of sunnypilot"
-          scons -j$(nproc) cache_dir=${{env.SCONS_CACHE_DIR}} --minimal
+          SKIP_TINYGRAD_COMPILE=1 /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
           touch ${BUILD_DIR}/prebuilt
           if [[ "${{ runner.debug }}" == "1" ]]; then
             ls -la ${BUILD_DIR}
           fi
 
-      - name: Prepare Output
+      - name: Strip release tree
         run: |
-          sudo rm -rf ${OUTPUT_DIR}
-          mkdir -p ${OUTPUT_DIR}
-          rsync -am${RUNNER_DEBUG:+v} \
-            --exclude='.sconsign.dblite' \
-            --exclude='*.a' \
-            --exclude='*.o' \
-            --exclude='*.os' \
-            --exclude='*.pyc' \
-            --exclude='moc_*' \
-            --exclude='__pycache__' \
-            --exclude='Jenkinsfile' \
-            --exclude='**/release/' \
-            --exclude='**/.github/' \
-            --exclude='**/openpilot/selfdrive/ui/replay/' \
-            --exclude='**/__pycache__/' \
-            --exclude='${{env.SCONS_CACHE_DIR}}' \
-            --exclude='**/.git/' \
-            --exclude='**/SConstruct' \
-            --exclude='**/SConscript' \
-            --exclude='**/.venv/' \
-            --exclude='openpilot/selfdrive/modeld/models/*.onnx*' \
-            --exclude='openpilot/sunnypilot/modeld*/models/*.onnx*' \
-            --exclude='openpilot/third_party/*x86*' \
-            --exclude='openpilot/third_party/*Darwin*' \
-            --delete-excluded \
-            --chown=comma:comma \
-            ${BUILD_DIR}/ ${OUTPUT_DIR}/
+          cd $BUILD_DIR
+          find . -name '*.a' -delete
+          find . -name '*.o' -delete
+          find . -name '*.os' -delete
+          find . -name '*.pyc' -delete
+          find . -name 'moc_*' -delete
+          find . -name '__pycache__' -type d -exec rm -rf {} +
+          find . -name 'SConstruct' -delete
+          find . -name 'SConscript' -delete
+          rm -rf .sconsign.dblite Jenkinsfile tools/release/ release/
+          rm -f openpilot/selfdrive/modeld/models/*.onnx*
+          rm -f openpilot/sunnypilot/modeld*/models/*.onnx*
+          find openpilot/third_party/ -name '*x86*' -exec rm -r {} +
+          find openpilot/third_party/ -name '*Darwin*' -exec rm -r {} +
+          cd -
 
       - name: 'Tar.gz files'
         run: |
-          tar czf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }} .
+          tar czf prebuilt.tar.gz -C ${{ env.BUILD_DIR }} .
           ls -la prebuilt.tar.gz
 
       - name: 'Upload Artifact'
@@ -242,6 +204,7 @@ jobs:
         with:
           name: prebuilt
           path: prebuilt.tar.gz
+          compression-level: 0
 
       - name: Re-enable powersave
         if: always()
@@ -249,22 +212,276 @@ jobs:
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
 
+  prepare_chestnut:
+    needs: [ prepare_strategy ]
+    runs-on: ubuntu-24.04
+    if: ${{ needs.prepare_strategy.outputs.include_big_model == 'true' }}
+    concurrency:
+      group: prepare-chestnut
+      cancel-in-progress: false
+    outputs:
+      onnx_sha256: ${{ steps.resolve.outputs.onnx_sha256 }}
+    env:
+      GH_REPO: ${{ github.repository }}
+      HF_REPO: sunnypilot/sunnypilot_models_v1
+      HF_DEFAULTS_PATH: models/defaults/big
+    steps:
+      - name: Resolve tinygrad ref via API
+        id: resolve
+        run: |
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl?ref=${REF}" --jq '.sha')
+          [ -n "$BLOB_SHA" ] || { echo "::error::Failed to resolve big_driving_tinygrad.pkl blob SHA"; exit 1; }
+          ONNX_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          echo "big PKL hash: $ONNX_HASH"
+          [ -n "$ONNX_HASH" ] || { echo "::error::Failed to extract big PKL hash"; exit 1; }
+
+          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
+          echo "tinygrad ref: $TINYGRAD_REF"
+
+          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
+
+          check_defaults() {
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            [ -n "$BUNDLE" ] && [ "$BUNDLE" != "null" ]
+          }
+
+          if check_defaults; then
+            echo "HF defaults match repo tinygrad ref"
+            exit 0
+          fi
+
+          echo "No matching model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=big
+          sleep 10
+
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
+          for i in $(seq 1 90); do
+            sleep 30
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/90: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "Big model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
+            fi
+          done
+
+          echo "::error::Build run did not complete within 45 minutes"
+          exit 1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Cancel run on failure
+        if: failure()
+        run: gh run cancel ${{ github.run_id }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+  prepare_small_model:
+    needs: [ prepare_strategy ]
+    runs-on: ubuntu-24.04
+    concurrency:
+      group: prepare-small-model
+      cancel-in-progress: false
+    outputs:
+      driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
+    env:
+      GH_REPO: ${{ github.repository }}
+      HF_REPO: sunnypilot/sunnypilot_models_v1
+      HF_DEFAULTS_PATH: models/defaults/small
+    steps:
+      - name: Resolve tinygrad ref via API
+        id: resolve
+        run: |
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.sha')
+          DRIVING_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          echo "Driving ONNX hash: $DRIVING_HASH"
+          [ -n "$DRIVING_HASH" ] || { echo "::error::Failed to extract driving ONNX hash"; exit 1; }
+
+          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
+          echo "tinygrad ref: $TINYGRAD_REF"
+
+          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
+
+          check_defaults() {
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            DRIVING=$(echo "$DEFAULTS" | jq --arg hash "$DRIVING_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            [ -n "$DRIVING" ] && [ "$DRIVING" != "null" ] || return 1
+          }
+
+          if check_defaults; then
+            echo "HF defaults match repo tinygrad ref"
+            exit 0
+          fi
+
+          echo "No matching model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=small
+          sleep 10
+
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
+          for i in $(seq 1 60); do
+            sleep 30
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "Small model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
+            fi
+          done
+
+          echo "::error::Small model build did not complete within 30 minutes"
+          exit 1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Cancel run on failure
+        if: failure()
+        run: gh run cancel ${{ github.run_id }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+  prepare_dm_model:
+    needs: [ prepare_strategy ]
+    runs-on: ubuntu-24.04
+    concurrency:
+      group: prepare-dm-model
+      cancel-in-progress: false
+    outputs:
+      dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
+    env:
+      GH_REPO: ${{ github.repository }}
+      HF_REPO: sunnypilot/sunnypilot_models_v1
+      HF_DEFAULTS_PATH: models/defaults/dm
+    steps:
+      - name: Resolve tinygrad ref via API
+        id: resolve
+        run: |
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.sha')
+          DM_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          echo "DM ONNX hash: $DM_HASH"
+          [ -n "$DM_HASH" ] || { echo "::error::Failed to extract DM ONNX hash"; exit 1; }
+
+          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
+          echo "tinygrad ref: $TINYGRAD_REF"
+
+          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
+
+          check_defaults() {
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            DM=$(echo "$DEFAULTS" | jq --arg hash "$DM_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            [ -n "$DM" ] && [ "$DM" != "null" ] || return 1
+          }
+
+          if check_defaults; then
+            echo "HF defaults match DM tinygrad ref"
+            exit 0
+          fi
+
+          echo "No matching DM model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=dm
+          sleep 10
+
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
+          for i in $(seq 1 60); do
+            sleep 30
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "DM model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but DM model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
+            fi
+          done
+
+          echo "::error::DM model build did not complete within 30 minutes"
+          exit 1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Cancel run on failure
+        if: failure()
+        run: gh run cancel ${{ github.run_id }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
   publish:
     concurrency:
-      # We do a bit of a hack here to avoid canceling the publishing job if a new commit comes in while we're publishing by adding the sha to the group name.
-      # This means that if multiple commits come in while we're publishing, they will be queued up and publish one after the other.
-      # Otherwise, if a job is waiting to be published due to environment wait time, it would be canceled by a new commit and restart the wait time.
       group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}
       cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
-    if: ${{ (always() && !cancelled() && !failure()) && needs.build.result == 'success' && needs.prepare_strategy.result == 'success' && (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) }}
-    needs: [ build, prepare_strategy ]
+    if: ${{
+      always() && !cancelled() &&
+      needs.build.result == 'success' &&
+      needs.prepare_strategy.result == 'success' &&
+      needs.prepare_small_model.result == 'success' &&
+      needs.prepare_dm_model.result == 'success' &&
+      (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) &&
+      (needs.prepare_strategy.outputs.include_big_model != 'true' || needs.prepare_chestnut.result == 'success')
+      }}
+    needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
     runs-on: ubuntu-24.04
     environment: ${{ needs.prepare_strategy.outputs.environment }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
 
-      - name: Download build artifacts
+      - name: Download prebuilt artifact
         uses: actions/download-artifact@v4
         with:
           name: prebuilt
@@ -274,6 +491,17 @@ jobs:
           mkdir -p ${{ env.OUTPUT_DIR }}
           tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
 
+      - name: Download model chunks from HF
+        uses: ./.github/workflows/download-hf-model-chunks
+        with:
+          hf_repo: sunnypilot/sunnypilot_models_v1
+          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
+          models: |
+            [
+              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
+              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"}
+            ]
+
       - name: Configure Git
         run: |
           git config --global user.email "github-actions[bot]@users.noreply.github.com"
@@ -283,36 +511,95 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
-          echo '${{ toJSON(needs.build.outputs) }}'
+          echo '${{ toJSON(needs.prepare_strategy.outputs) }}'
           ls -la ${{ env.OUTPUT_DIR }}
 
           ${{ env.CI_DIR }}/publish.sh \
             "${{ github.workspace }}" \
             "${{ env.OUTPUT_DIR }}" \
-            "${{ needs.build.outputs.new_branch }}" \
-            "${{ needs.build.outputs.version }}" \
+            "${{ needs.prepare_strategy.outputs.new_branch }}" \
+            "${{ needs.prepare_strategy.outputs.version }}" \
             "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
-            "${{ needs.build.outputs.extra_version_identifier }}"
-
-          echo ""
-          echo "----   ℹ️ To update the list of branches that auto deploy prebuilts  -----"
-          echo ""
-          echo "1. Go to: ${{ github.server_url }}/${{ github.repository }}/settings/variables/actions/AUTO_DEPLOY_PREBUILT_BRANCHES"
-          echo "2. Current value: ${{ vars.AUTO_DEPLOY_PREBUILT_BRANCHES }}"
-          echo "3. Update as needed (JSON array with no spaces)"
+            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
 
       - name: Tag ${{ needs.prepare_strategy.outputs.environment }}
         if: ${{ needs.prepare_strategy.outputs.is_stable_branch == 'true' && (github.event_name != 'push' || !startsWith(github.ref, 'refs/tags/')) }}
         run: |
             TAG="${{ needs.prepare_strategy.outputs.environment }}/${{ needs.prepare_strategy.outputs.version }}/${{ needs.prepare_strategy.outputs.build }}"
-            git tag -f -a ${TAG} -m "${{ needs.prepare_strategy.outputs.environment }} @ ${{ needs.prepare_strategy.outputs.version }} of build ${{ needs.build.outputs.build }}."
+            git tag -f -a ${TAG} -m "${{ needs.prepare_strategy.outputs.environment }} @ ${{ needs.prepare_strategy.outputs.version }} of build ${{ needs.prepare_strategy.outputs.build }}."
             git push -f origin ${TAG}
 
+  publish_chestnut:
+    concurrency:
+      group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}-chestnut
+      cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
+    if: ${{
+      always() && !cancelled() &&
+      needs.build.result == 'success' &&
+      needs.prepare_strategy.result == 'success' &&
+      needs.prepare_small_model.result == 'success' &&
+      needs.prepare_dm_model.result == 'success' &&
+      needs.prepare_chestnut.result == 'success' &&
+      (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt'))
+      }}
+    needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
+    runs-on: ubuntu-24.04
+    environment: ${{ needs.prepare_strategy.outputs.environment }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
+
+      - name: Download prebuilt artifact
+        uses: actions/download-artifact@v4
+        with:
+          name: prebuilt
+
+      - name: Untar prebuilt
+        run: |
+          mkdir -p ${{ env.OUTPUT_DIR }}
+          tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
+
+      - name: Download model chunks from HF
+        uses: ./.github/workflows/download-hf-model-chunks
+        with:
+          hf_repo: sunnypilot/sunnypilot_models_v1
+          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
+          models: |
+            [
+              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
+              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"},
+              {"hf_path": "models/defaults/big", "onnx_hash": "${{ needs.prepare_chestnut.outputs.onnx_sha256 }}", "canonical": "big_driving_tinygrad.pkl"}
+            ]
+
+      - name: Configure Git
+        run: |
+          git config --global user.email "github-actions[bot]@users.noreply.github.com"
+          git config --global user.name "github-actions[bot]"
+
+      - name: Publish chestnut branch
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
+
+          ${{ env.CI_DIR }}/publish.sh \
+            "${{ github.workspace }}" \
+            "${{ env.OUTPUT_DIR }}" \
+            "$CHESTNUT_BRANCH" \
+            "${{ needs.prepare_strategy.outputs.version }}" \
+            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
+            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
+
   notify:
     needs:
     - prepare_strategy
     - build
     - publish
+    - publish_chestnut
+    - prepare_chestnut
+    - prepare_small_model
+    - prepare_dm_model
     runs-on: ubuntu-24.04
     if: ${{ (always() && !cancelled() && !failure())
       && needs.publish.result == 'success'
@@ -320,11 +607,12 @@ jobs:
       && (fromJSON(vars.DEV_FEEDBACK_NOTIFICATION_BRANCHES_V2)[github.head_ref || github.ref_name] != null) }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
 
       - name: Prepare notification message
         id: message
         run: |
-          TEMPLATE='${{ vars.DISCOURSE_GENERAL_UPDATE_NOTICE }}'
           export VERSION="${{ needs.prepare_strategy.outputs.version }}"
           export branch_name="${{ env.SOURCE_BRANCH }}"
           export new_branch="${{ needs.prepare_strategy.outputs.new_branch }}"
@@ -333,6 +621,7 @@ jobs:
           export commit_short_sha="${commit_short_sha:0:7}"
           export extra_version_identifier="${{ needs.prepare_strategy.outputs.extra_version_identifier || github.run_number }}"
           export PUBLIC_REPO_URL="${{ env.PUBLIC_REPO_URL }}"
+          export chestnut_branch="${{ needs.prepare_chestnut.result == 'success' && format('{0}-chestnut', needs.prepare_strategy.outputs.new_branch) || '' }}"
 
           MESSAGE=$(cat << 'EOF' | envsubst
           ${{ vars.DISCOURSE_GENERAL_UPDATE_NOTICE }}
@@ -373,7 +662,7 @@ jobs:
               owner: context.repo.owner,
               repo: context.repo.repo,
               issue_number: prNumber,
-              name: process.env.LABELf
+              name: process.env.LABEL
             });
 
             console.log(`Removed '${process.env.LABEL}' label from PR #${prNumber}`);

.github/workflows/test-discourse.yaml.yml

@@ -1,78 +0,0 @@
-name: Debug Discourse Posting
-
-on:
-  push:
-
-jobs:
-  test-discourse-post:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Post test message to Discourse
-        uses: ./.github/workflows/post-to-discourse
-        with:
-          discourse-url: ${{ vars.DISCOURSE_URL }}
-          api-key: ${{ secrets.DISCOURSE_API_KEY }}
-          api-username: ${{ secrets.DISCOURSE_API_USERNAME }}
-          topic-id: ${{ vars.DISCOURSE_UPDATES_TOPIC_ID }}
-          message: |
-            ## 🧪 Test Post from GitHub Actions
-            
-            **This is a test post to verify Discourse integration**
-            
-            - **Workflow**: ${{ github.workflow }}
-            - **Run Number**: #${{ github.run_number }}
-            - **Branch**: `${{ github.ref_name }}`
-            - **Commit**: ${{ github.sha }}
-            - **Actor**: @${{ github.actor }}
-            - **Timestamp**: ${{ github.event.head_commit.timestamp }}
-            
-            ---
-            
-            ### Fake Build Info (for testing)
-            - **Version**: 0.9.8-test
-            - **Build**: #42
-            - **Branch**: release-test
-            
-            [View workflow run](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }})
-            
-            *This is an automated test message. Drive safe! 🚗💨*
-      
-      
-      - name: Create topic on Discourse
-        uses: ./.github/workflows/post-to-discourse
-        with:
-          discourse-url: ${{ vars.DISCOURSE_URL }}
-          api-key: ${{ secrets.DISCOURSE_API_KEY }}
-          api-username: ${{ secrets.DISCOURSE_API_USERNAME }}
-          #topic-id: ${{ vars.DISCOURSE_UPDATES_TOPIC_ID }}
-          category-id: 4
-          title: "This is a test of a new topic instead of a reply"
-          message: |
-            ## 🧪 Test Post from GitHub Actions
-            
-            **This is a test post to verify Discourse integration**
-            
-            - **Workflow**: ${{ github.workflow }}
-            - **Run Number**: #${{ github.run_number }}
-            - **Branch**: `${{ github.ref_name }}`
-            - **Commit**: ${{ github.sha }}
-            - **Actor**: @${{ github.actor }}
-            - **Timestamp**: ${{ github.event.head_commit.timestamp }}
-            
-            ---
-            
-            ### Fake Build Info (for testing)
-            - **Version**: 0.9.8-test
-            - **Build**: #42
-            - **Branch**: release-test
-            
-            [View workflow run](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }})
-            
-            *This is an automated test message. Drive safe! 🚗💨*
-      - name: Display results
-        if: always()
-        run: |
-          echo "::notice::Discourse post test completed"
-          echo "Check your Discourse topic to verify the post appeared correctly"

.github/workflows/test_models.yml

@@ -0,0 +1,84 @@
+name: Test Models Compatibility With Tinygrad Changes
+on:
+  pull_request:
+    paths:
+      - 'tinygrad_repo'
+  workflow_dispatch:
+
+jobs:
+  generate-matrix:
+    runs-on: ubuntu-latest
+    outputs:
+      models: ${{ steps.set-matrix.outputs.models }}
+    steps:
+      - uses: actions/checkout@v4
+      - name: Fetch and Parse json
+        id: set-matrix
+        run: |
+          python3 -c '
+          import json, urllib.request, os, re
+
+          with open("openpilot/sunnypilot/models/fetcher.py", "r") as f:
+            urls = re.findall(r"MODEL_URL(?:_CHESTNUT)?\s*=\s*[\"'"'"']([^\"'"'"']+)[\"'"'"']", f.read())
+
+          artifacts = []
+          for url in urls:
+            data = json.loads(urllib.request.urlopen(url).read())
+            for bundle in data.get("bundles", []):
+              for model in bundle.get("models", []):
+                if "artifact" in model:
+                  artifacts.append(model["artifact"])
+
+          with open(os.environ["GITHUB_OUTPUT"], "a") as f:
+            f.write(f"models={json.dumps(artifacts)}\n")
+          '
+
+  test-model:
+    name: Test ${{ matrix.artifact.file_name }}
+    needs: generate-matrix
+    runs-on: ubuntu-latest
+    container: ghcr.io/commaai/openpilot-base:latest
+    strategy:
+      fail-fast: false
+      matrix:
+        artifact: ${{ fromJson(needs.generate-matrix.outputs.models) }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: true
+
+      - name: Download Model Chunks in Parallel
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: |
+          mkdir -p /tmp/model_chunks
+          echo '${{ toJson(matrix.artifact.chunks) }}' > chunks.json
+
+          BASE_URL="${{ matrix.artifact.download_uri.url }}"
+          export BASE_DIR=$(dirname "$BASE_URL")
+
+          python3 -c '
+          import json, os
+          with open("chunks.json") as f:
+            chunks = json.load(f)
+          manifest_path = f"/tmp/model_chunks/${{ matrix.artifact.file_name }}.chunkmanifest"
+          with open(manifest_path, "w") as f:
+            f.write(str(len(chunks)))
+          base_dir = os.environ["BASE_DIR"]
+          hf_token = os.environ.get("HF_TOKEN", "")
+          with open("/tmp/curl_config.txt", "w") as f:
+            for c in chunks:
+              fn = c["file_name"]
+              f.write(f"url = \"{base_dir}/{fn}\"\noutput = \"/tmp/model_chunks/{fn}\"\n")
+              if hf_token:
+                f.write(f"header = \"Authorization: Bearer {hf_token}\"\n")
+          '
+          curl -Z --parallel-immediate --parallel-max 12 --retry 3 --retry-all-errors -s -S -f -L -K /tmp/curl_config.txt
+
+      - name: Run Model Compatibility Test
+        env:
+          MODEL_BASE_NAME: ${{ matrix.artifact.file_name }}
+          MODEL_CHUNK_DIR: "/tmp/model_chunks"
+          PYTHONPATH: ".:./tinygrad_repo"
+        run: |
+          python3 -m pytest openpilot/sunnypilot/modeld_v2/tests/test_models.py

.github/workflows/tests.yaml

@@ -22,7 +22,7 @@ env:
   PYTHONPATH: ${{ github.workspace }}
   GIT_CONFIG_COUNT: 1
   GIT_CONFIG_KEY_0: lfs.fetchexclude
-  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
 
 jobs:
   build_release:

.github/workflows/ui_preview.yaml

@@ -25,7 +25,8 @@ env:
 
 jobs:
   preview:
-    if: github.repository == 'sunnypilot/sunnypilot'
+    if: false # tmp disable due to GH API rate limiting flakiness
+    #if: github.repository == 'sunnypilot/sunnypilot'
     name: preview
     runs-on: ubuntu-latest
     timeout-minutes: 20

.gitignore

@@ -50,6 +50,8 @@ st[0-9A-Za-z][0-9A-Za-z][0-9A-Za-z][0-9A-Za-z][0-9A-Za-z][0-9A-Za-z]
 *.stats
 *.pkl
 *.pkl*
+!openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
+!openpilot/sunnypilot/modeld_v2/models/*.pkl
 config.json
 compile_commands.json
 compare_runtime*.html

.gitmodules

@@ -19,3 +19,4 @@
 [submodule "sunnypilot/neural_network_data"]
 	path = openpilot/sunnypilot/neural_network_data
   url = https://github.com/sunnypilot/neural-network-data.git
+

.lfsconfig

@@ -1,4 +1,5 @@
 [lfs]
 	url = https://gitlab.com/sunnypilot/public/sunnypilot-new-lfs.git/info/lfs
 	pushurl = ssh://git@gitlab.com/sunnypilot/public/sunnypilot-new-lfs.git
+
 	locksverify = false

Jenkinsfile

@@ -12,16 +12,18 @@ def retryWithDelay(int maxRetries, int delay, Closure body) {
 def device(String ip, String step_label, String cmd) {
   withCredentials([file(credentialsId: 'id_rsa', variable: 'key_file')]) {
     def ssh_cmd = """
-ssh -o ControlMaster=auto -o ControlPath=/tmp/ssh_control_%C -o ControlPersist=yes -o ConnectTimeout=5 -o ServerAliveInterval=5 -o ServerAliveCountMax=2 -o BatchMode=yes -o StrictHostKeyChecking=no -i ${key_file} 'comma@${ip}' exec /usr/bin/bash <<'END'
+ssh -o ControlMaster=no -o ControlPath=none -o ConnectTimeout=5 -o ServerAliveInterval=5 -o ServerAliveCountMax=12 -o BatchMode=yes -o StrictHostKeyChecking=no -i ${key_file} 'comma@${ip}' exec setpriv --pdeathsig HUP /usr/bin/bash <<'END'
 
 set -e
 
 export TERM=xterm-256color
 
-shopt -s huponexit # kill all child processes when the shell exits
+trap 'kill 0' HUP # stop this process group on SSH disconnect
 
 export CI=1
 export PYTHONWARNINGS=error
+export PYTHONFAULTHANDLER=1
+export COMMA_CACHE=/data/tmp/comma_download_cache
 #export LOGPRINT=debug # this has gotten too spammy...
 export TEST_DIR=${env.TEST_DIR}
 export SOURCE_DIR=${env.SOURCE_DIR}
@@ -68,7 +70,8 @@ export LD_LIBRARY_PATH="\$(python -c 'import ffmpeg; print(ffmpeg.LIB_DIR)'):/us
 ln -snf ${env.TEST_DIR} /data/pythonpath
 
 cd ${env.TEST_DIR} || true
-time ${cmd}
+time ( ${cmd} ) &
+wait \$!
 END"""
 
     sh script: ssh_cmd, label: step_label
@@ -168,7 +171,7 @@ node {
   env.GIT_BRANCH = checkout(scm).GIT_BRANCH
   env.GIT_COMMIT = checkout(scm).GIT_COMMIT
 
-  def excludeBranches = ['__nightly', 'devel', 'devel-staging',
+  def excludeBranches = ['__nightly', '__nightly-chestnut', 'devel', 'devel-staging',
                          'release-tizi', 'release-tizi-staging', 'release-mici', 'release-mici-staging', 'testing-closet*', 'hotfix-*']
   def excludeRegex = excludeBranches.join('|').replaceAll('\\*', '.*')
 
@@ -200,6 +203,12 @@ node {
       )
     }
 
+    if (env.BRANCH_NAME == '__nightly-chestnut') {
+      deviceStage("build nightly-chestnut", "mici-chestnut-ci", [], [
+        step("build nightly-chestnut", "SCONSFLAGS=-j4 INCLUDE_BIG_MODEL=1 PANDA_DEBUG_BUILD=1 RELEASE_BRANCH=nightly-chestnut $SOURCE_DIR/tools/release/build_release.sh TestChestnutOnroad"),
+      ])
+    }
+
     if (!env.BRANCH_NAME.matches(excludeRegex)) {
     parallel (
       'onroad tests': {
@@ -251,6 +260,14 @@ node {
           step("test amp", "./openpilot/common/hardware/comma/tests/test_amplifier.py"),
         ])
       },
+      'chestnut': {
+        deviceStage("chestnut", "mici-chestnut-ci", ["UNSAFE=1", "CHESTNUT=1"], [
+          step("build", "./openpilot/selfdrive/test/chestnut.sh"),
+          step("model replay", "openpilot/selfdrive/test/process_replay/model_replay.py --chestnut"),
+          step("onroad tests", "./openpilot/selfdrive/test/test_onroad.py TestChestnutOnroad", [timeout: 120]),
+          step("test power draw", "./openpilot/selfdrive/test/test_power_draw.py"),
+        ])
+      },
 
     )
     }

SConstruct

@@ -87,7 +87,6 @@ acados_include_dirs = [
 # vendored in commaai/dependencies.
 allowed_system_libs = {
   "EGL", "GLESv2", "GL",
-  "Qt5Charts", "Qt5Core", "Qt5Gui", "Qt5Widgets",
   "dl", "drm", "gbm", "m", "pthread",
 }
 
@@ -346,6 +345,8 @@ AddPostAction(BUILD_TARGETS or [Dir('.')], prune_cache_dir)
 def check_build_product_size(target, source, env):
   limit = 50 * 1024 * 1024  # GitHub max size
   for t in target:
+    if str(t).endswith('.pkl'):  # chunked during release packaging
+      continue
     if hasattr(t, 'isfile') and t.isfile() and (size := os.path.getsize(t.abspath)) > limit:
       raise SCons.Errors.UserError(f"{t} is {size / (1024 * 1024):.1f} MiB, exceeding the {limit / (1024 * 1024):.1f} MiB limit")
 if not GetOption('extras'):

docs/CARS.md

@@ -4,7 +4,7 @@
 
 A supported vehicle is one that just works when you install a comma device. All supported cars provide a better experience than any stock system. Supported vehicles reference the US market unless otherwise specified.
 
-# 342 Supported Cars
+# 345 Supported Cars
 
 |Make|Model|Supported Package|ACC|No ACC accel below|No ALC below|Steering Torque|Resume from stop|<a href="##"><img width=2000></a>Hardware Needed<br>&nbsp;|Video|Setup Video|
 |---|---|---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
@@ -34,6 +34,7 @@ A supported vehicle is one that just works when you install a comma device. All
 |Chrysler|Pacifica Hybrid 2019-25|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Chrysler Pacifica Hybrid 2019-25">Buy Here</a></sub></details>|||
 |comma|body|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|None|<a href="https://youtu.be/VT-i3yRsX2s?t=2736" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
 |CUPRA[<sup>12</sup>](#footnotes)|Ateca 2018-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=CUPRA Ateca 2018-23">Buy Here</a></sub></details>|||
+|CUPRA|Born 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=CUPRA Born 2021-23">Buy Here</a></sub></details>|||
 |Dodge|Durango 2020-21|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Dodge Durango 2020-21">Buy Here</a></sub></details>|||
 |Ford|Bronco Sport 2021-24|Co-Pilot360 Assist+|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Ford Q3 connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Ford Bronco Sport 2021-24">Buy Here</a></sub></details>|||
 |Ford|Escape 2020-22|Co-Pilot360 Assist+|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Ford Q3 connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Ford Escape 2020-22">Buy Here</a></sub></details>|||
@@ -82,7 +83,7 @@ A supported vehicle is one that just works when you install a comma device. All
 |Honda|City (Brazil only) 2023-25|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|14 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda City (Brazil only) 2023-25">Buy Here</a></sub></details>|||
 |Honda|Civic 2016-18|Honda Sensing|openpilot|0 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Civic 2016-18">Buy Here</a></sub></details>|<a href="https://youtu.be/-IkImTe1NYE" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
 |Honda|Civic 2019-21|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|2 mph[<sup>4</sup>](#footnotes)|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Civic 2019-21">Buy Here</a></sub></details>|<a href="https://www.youtube.com/watch?v=4Iz1Mz5LGF8" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
-|Honda|Civic 2022-24|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Civic 2022-24">Buy Here</a></sub></details>|<a href="https://youtu.be/ytiOT5lcp6Q" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
+|Honda|Civic 2022-26|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Civic 2022-26">Buy Here</a></sub></details>|<a href="https://youtu.be/ytiOT5lcp6Q" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
 |Honda|Civic Hatchback 2017-18|Honda Sensing|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Civic Hatchback 2017-18">Buy Here</a></sub></details>|||
 |Honda|Civic Hatchback 2019-21|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Civic Hatchback 2019-21">Buy Here</a></sub></details>|||
 |Honda|Civic Hatchback 2022-24|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Civic Hatchback 2022-24">Buy Here</a></sub></details>|<a href="https://youtu.be/ytiOT5lcp6Q" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
@@ -98,7 +99,7 @@ A supported vehicle is one that just works when you install a comma device. All
 |Honda|Fit 2018-20|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Fit 2018-20">Buy Here</a></sub></details>|||
 |Honda|Freed 2020|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Freed 2020">Buy Here</a></sub></details>|||
 |Honda|HR-V 2019-22|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2019-22">Buy Here</a></sub></details>|||
-|Honda|HR-V 2023-25|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2023-25">Buy Here</a></sub></details>|||
+|Honda|HR-V 2023-27|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2023-27">Buy Here</a></sub></details>|||
 |Honda|Insight 2019-22|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|3 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Insight 2019-22">Buy Here</a></sub></details>|||
 |Honda|Inspire 2018|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|3 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Inspire 2018">Buy Here</a></sub></details>|||
 |Honda|N-Box 2018|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|11 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda N-Box 2018">Buy Here</a></sub></details>|||
@@ -158,7 +159,7 @@ A supported vehicle is one that just works when you install a comma device. All
 |Hyundai|Tucson Plug-in Hybrid 2024|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Hyundai N connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Hyundai Tucson Plug-in Hybrid 2024">Buy Here</a></sub></details>|||
 |Hyundai|Veloster 2019-20|Smart Cruise Control (SCC)|Stock|5 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Hyundai E connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Hyundai Veloster 2019-20">Buy Here</a></sub></details>|||
 |Jeep|Grand Cherokee 2016-18|Adaptive Cruise Control (ACC)|Stock|0 mph|9 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Jeep Grand Cherokee 2016-18">Buy Here</a></sub></details>|<a href="https://www.youtube.com/watch?v=eLR9o2JkuRk" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
-|Jeep|Grand Cherokee 2019-21|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Jeep Grand Cherokee 2019-21">Buy Here</a></sub></details>|<a href="https://www.youtube.com/watch?v=jBe4lWnRSu4" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
+|Jeep|Grand Cherokee 2019-21|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Jeep Grand Cherokee 2019-21">Buy Here</a></sub></details>|||
 |Kia|Carnival 2022-24|Smart Cruise Control (SCC)|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Hyundai A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Kia Carnival 2022-24">Buy Here</a></sub></details>|||
 |Kia|Carnival (China only) 2023|Smart Cruise Control (SCC)|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Hyundai K connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Kia Carnival (China only) 2023">Buy Here</a></sub></details>|||
 |Kia|Ceed 2019-21|Smart Cruise Control (SCC)|Stock|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Hyundai E connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Kia Ceed 2019-21">Buy Here</a></sub></details>|||
@@ -242,20 +243,20 @@ A supported vehicle is one that just works when you install a comma device. All
 |Rivian|R1T 2025|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Rivian B connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Rivian R1T 2025">Buy Here</a></sub></details>|||
 |SEAT[<sup>12</sup>](#footnotes)|Ateca 2016-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=SEAT Ateca 2016-23">Buy Here</a></sub></details>|||
 |SEAT[<sup>12</sup>](#footnotes)|Leon 2014-20|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=SEAT Leon 2014-20">Buy Here</a></sub></details>|||
-|Subaru|Ascent 2019-21|All[<sup>7</sup>](#footnotes)|openpilot available[<sup>1,8</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Ascent 2019-21">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
-|Subaru|Crosstrek 2018-19|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|openpilot available[<sup>1,8</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Crosstrek 2018-19">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|<a href="https://youtu.be/Agww7oE1k-s?t=26" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
-|Subaru|Crosstrek 2020-23|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|openpilot available[<sup>1,8</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Crosstrek 2020-23">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
+|Subaru|Ascent 2019-21|All[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Ascent 2019-21">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
+|Subaru|Crosstrek 2018-19|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Crosstrek 2018-19">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|<a href="https://youtu.be/Agww7oE1k-s?t=26" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
+|Subaru|Crosstrek 2020-23|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Crosstrek 2020-23">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
 |Subaru|Forester 2017-18|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Forester 2017-18">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
-|Subaru|Forester 2019-21|All[<sup>7</sup>](#footnotes)|openpilot available[<sup>1,8</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Forester 2019-21">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
-|Subaru|Impreza 2017-19|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|openpilot available[<sup>1,8</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Impreza 2017-19">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
-|Subaru|Impreza 2020-22|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|openpilot available[<sup>1,8</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Impreza 2020-22">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
+|Subaru|Forester 2019-21|All[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Forester 2019-21">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
+|Subaru|Impreza 2017-19|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Impreza 2017-19">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
+|Subaru|Impreza 2020-22|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Impreza 2020-22">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
 |Subaru|Legacy 2015-18|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Legacy 2015-18">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
 |Subaru|Legacy 2020-22|All[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru B connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Legacy 2020-22">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
 |Subaru|Outback 2015-17|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Outback 2015-17">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
 |Subaru|Outback 2018-19|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Outback 2018-19">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
 |Subaru|Outback 2020-22|All[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru B connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru Outback 2020-22">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
-|Subaru|XV 2018-19|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|openpilot available[<sup>1,8</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru XV 2018-19">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|<a href="https://youtu.be/Agww7oE1k-s?t=26" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
-|Subaru|XV 2020-21|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|openpilot available[<sup>1,8</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru XV 2020-21">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
+|Subaru|XV 2018-19|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru XV 2018-19">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|<a href="https://youtu.be/Agww7oE1k-s?t=26" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
+|Subaru|XV 2020-21|EyeSight Driver Assistance[<sup>7</sup>](#footnotes)|Stock|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Subaru A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Subaru XV 2020-21">Buy Here</a></sub></details><details><summary>Tools</summary><sub>- 1 Pry Tool<br>- 1 Socket Wrench 8mm or 5/16" (deep)</sub></details>|||
 |Škoda|Fabia 2022-23[<sup>15</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Škoda Fabia 2022-23">Buy Here</a></sub></details>[<sup>17</sup>](#footnotes)|||
 |Škoda|Kamiq 2021-23[<sup>13,15</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Škoda Kamiq 2021-23">Buy Here</a></sub></details>[<sup>17</sup>](#footnotes)|||
 |Škoda[<sup>12</sup>](#footnotes)|Karoq 2019-23[<sup>15</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Škoda Karoq 2019-23">Buy Here</a></sub></details>|||
@@ -267,8 +268,8 @@ A supported vehicle is one that just works when you install a comma device. All
 |Škoda[<sup>12</sup>](#footnotes)|Superb 2015-22[<sup>15</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Škoda Superb 2015-22">Buy Here</a></sub></details>|||
 |Tesla[<sup>10</sup>](#footnotes)|Model 3 (with HW3) 2019-23[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model 3 (with HW3) 2019-23">Buy Here</a></sub></details>|||
 |Tesla[<sup>10</sup>](#footnotes)|Model 3 (with HW4) 2024-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model 3 (with HW4) 2024-25">Buy Here</a></sub></details>|||
-|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW3) 2020-23[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW3) 2020-23">Buy Here</a></sub></details>|||
-|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW4) 2024-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW4) 2024-25">Buy Here</a></sub></details>|||
+|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW3) 2020-24[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW3) 2020-24">Buy Here</a></sub></details>|||
+|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW4) 2023-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW4) 2023-25">Buy Here</a></sub></details>|||
 |Toyota|Alphard 2019-20|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Alphard 2019-20">Buy Here</a></sub></details>|||
 |Toyota|Alphard Hybrid 2021|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Alphard Hybrid 2021">Buy Here</a></sub></details>|||
 |Toyota|Avalon 2016|Toyota Safety Sense P|Stock|19 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Avalon 2016">Buy Here</a></sub></details>|||
@@ -334,6 +335,8 @@ A supported vehicle is one that just works when you install a comma device. All
 |Volkswagen[<sup>12</sup>](#footnotes)|Golf R 2015-19|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Golf R 2015-19">Buy Here</a></sub></details>|||
 |Volkswagen[<sup>12</sup>](#footnotes)|Golf SportsVan 2015-20|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Golf SportsVan 2015-20">Buy Here</a></sub></details>|||
 |Volkswagen[<sup>12</sup>](#footnotes)|Grand California 2019-24|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|31 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Grand California 2019-24">Buy Here</a></sub></details>|<a href="https://youtu.be/4100gLeabmo" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
+|Volkswagen|ID.4 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2021-23">Buy Here</a></sub></details>|||
+|Volkswagen|ID.4 2024-25|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2024-25">Buy Here</a></sub></details>|||
 |Volkswagen[<sup>12</sup>](#footnotes)|Jetta 2019-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Jetta 2019-23">Buy Here</a></sub></details>|||
 |Volkswagen[<sup>12</sup>](#footnotes)|Jetta GLI 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Jetta GLI 2021-23">Buy Here</a></sub></details>|||
 |Volkswagen|Passat 2015-22[<sup>14</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Passat 2015-22">Buy Here</a></sub></details>|||
@@ -360,7 +363,7 @@ A supported vehicle is one that just works when you install a comma device. All
 <sup>6</sup>See more setup details for <a href="https://github.com/commaai/openpilot/wiki/nissan" target="_blank">Nissan</a>. <br />
 <sup>7</sup>In the non-US market, openpilot requires the car to come equipped with EyeSight with Lane Keep Assistance. <br />
 <sup>8</sup>Enabling longitudinal control (alpha) will disable all EyeSight functionality, including AEB, LDW, and RAB. <br />
-<sup>9</sup>Some 2023 model years have HW4. To check which hardware type your vehicle has, look for <b>Autopilot computer</b> under <b>Software -> Additional Vehicle Information</b> on your vehicle's touchscreen. See <a href="https://www.notateslaapp.com/news/2173/how-to-check-if-your-tesla-has-hardware-4-ai4-or-hardware-3">this page</a> for more information. <br />
+<sup>9</sup>Model years 2023 and 2024 can have either hardware type, depending on build date and factory. To check which hardware type your vehicle has, look for <b>Autopilot computer</b> under <b>Software -> Additional Vehicle Information</b> on your vehicle's touchscreen. See <a href="https://www.notateslaapp.com/news/2173/how-to-check-if-your-tesla-has-hardware-4-ai4-or-hardware-3">this page</a> for more information. <br />
 <sup>10</sup>See more setup details for <a href="https://github.com/commaai/openpilot/wiki/tesla" target="_blank">Tesla</a>. <br />
 <sup>11</sup>openpilot operates above 28mph for Camry 4CYL L, 4CYL LE and 4CYL SE which don't have Full-Speed Range Dynamic Radar Cruise Control. <br />
 <sup>12</sup>The J533 harness plugs in at the CAN gateway under the dashboard, just above the steering column. More information can be found at <a href="https://docs.howtocomma.com/docs/j533-harness-install" target="_blank">this guide</a>. <br />

docs/README.md

@@ -5,10 +5,10 @@ The site is updated on pushes to master by this [workflow](../.github/workflows/
 
 **1. Build the site**
 ``` bash
-python docs/serve.py --build
+op docs --build
 ```
 
 **2. Run the site locally** (rebuilds on change)
 ``` bash
-python docs/serve.py
+op docs
 ```

launch_chffrplus.sh

@@ -18,19 +18,21 @@ function agnos_init {
   sudo chmod 660 /dev/adsprpc-smd /dev/ion /dev/kgsl-3d0
 
   # Check if AGNOS update is required
-  if [ $(< /VERSION) != "$AGNOS_VERSION" ]; then
+  if [ "$(< /VERSION)" != "$AGNOS_VERSION" ]; then
     AGNOS_PY="$DIR/openpilot/common/hardware/comma/agnos.py"
     MANIFEST="$DIR/openpilot/system/hardware/comma/agnos.json"
-    if $AGNOS_PY --verify $MANIFEST; then
+    if "$AGNOS_PY" --verify "$MANIFEST"; then
       sudo reboot
     fi
-    $DIR/openpilot/common/hardware/comma/updater $AGNOS_PY $MANIFEST
+    while true; do
+      "$DIR/openpilot/common/hardware/comma/updater" "$AGNOS_PY" "$MANIFEST"
+    done
   fi
 }
 
 function launch {
   # Remove orphaned git lock if it exists on boot
-  [ -f "$DIR/.git/index.lock" ] && rm -f $DIR/.git/index.lock
+  [ -f "$DIR/.git/index.lock" ] && rm -f "$DIR/.git/index.lock"
 
   # Check to see if there's a valid overlay-based update available. Conditions
   # are as follows:
@@ -42,7 +44,7 @@ function launch {
   #    that completed successfully and synced to disk.
 
   if [ -f "${DIR}/.overlay_init" ]; then
-    find ${DIR}/.git -newer ${DIR}/.overlay_init | grep -q '.' 2> /dev/null
+    find "${DIR}/.git" -newer "${DIR}/.overlay_init" | grep -q '.' 2> /dev/null
     if [ $? -eq 0 ]; then
       echo "${DIR} has been modified, skipping overlay update installation"
     else
@@ -51,9 +53,9 @@ function launch {
           echo "Valid overlay update found, installing"
           LAUNCHER_LOCATION="${BASH_SOURCE[0]}"
 
-          mv $DIR /data/safe_staging/old_openpilot
-          mv "${STAGING_ROOT}/finalized" $DIR
-          cd $DIR
+          mv "$DIR" /data/safe_staging/old_openpilot
+          mv "${STAGING_ROOT}/finalized" "$DIR"
+          cd "$DIR"
 
           echo "Restarting launch script ${LAUNCHER_LOCATION}"
           unset AGNOS_VERSION
@@ -67,7 +69,7 @@ function launch {
   fi
 
   # handle pythonpath
-  ln -sfn $(pwd) /data/pythonpath
+  ln -sfn "$(pwd)" /data/pythonpath
   export PYTHONPATH="$PWD"
 
   # submodule package symlinks for PYTHONPATH imports on device.
@@ -88,7 +90,7 @@ function launch {
 
   # start manager
   cd openpilot/system/manager
-  if [ ! -f $DIR/prebuilt ]; then
+  if [ ! -f "$DIR/prebuilt" ]; then
     ./build.py
   fi
   ./manager.py

launch_env.sh

@@ -16,7 +16,7 @@ export VECLIB_MAXIMUM_THREADS=1
 export QCOM_PRIORITY=12
 
 if [ -z "$AGNOS_VERSION" ]; then
-  export AGNOS_VERSION="19.6"
+  export AGNOS_VERSION="19.7"
 fi
 
 export STAGING_ROOT="/data/safe_staging"

openpilot/cereal/custom.capnp

@@ -131,6 +131,7 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
     downloaded @2;
     cached @3;
     failed @4;
+    verifying @5;
   }
 
   struct DownloadProgress {
@@ -352,6 +353,7 @@ struct OnroadEventSP @0xda96579883444c35 {
     speedLimitPending @22;
     e2eChime @23;
     laneChangeRoadEdge @24;
+    bigModelReady @25;
   }
 }
 

openpilot/cereal/log.capnp

@@ -725,6 +725,7 @@ struct ChestnutState {
   pcieLtssm @7 :UInt8;
   supplyVoltage @8 :UInt16;  # mV
   supplyCurrent @9 :Int16;  # mA
+  supplyFault @10 :Bool;
 }
 
 struct RadarState @0x9a185389d6fdd05f {
@@ -1004,6 +1005,7 @@ struct DrivingModelData {
   frameIdExtra @1 :UInt32;
   frameDropPerc @6 :Float32;
   modelExecutionTime @7 :Float32;
+  big @8 :Bool;
 
   action @2 :ModelDataV2.Action;
 
@@ -2592,6 +2594,7 @@ struct Event {
     clocks @35 :Clocks;
     deviceState @6 :DeviceState;
     chestnutState @152 :ChestnutState;
+    chestnutGpuState @153 :ChestnutState;
     logMessage @18 :Text;
     errorLogMessage @85 :Text;
 

openpilot/cereal/services.py

@@ -25,7 +25,8 @@ _services: dict[str, tuple] = {
   "accelerometer": (True, 104., 104),
   "temperatureSensor": (True, 2., 200),
   "deviceState": (True, 2., 1),
-  "chestnutState": (True, 10., 10),
+  "chestnutState": (True, 10., 1),
+  "chestnutGpuState": (False, 10.),
   "touch": (True, 20., 1),
   "can": (True, 100., 2053, QueueSize.BIG),  # decimation gives ~3 msgs in a full segment
   "controlsState": (True, 100., 10, QueueSize.MEDIUM),

openpilot/common/esim/base.py

@@ -21,6 +21,13 @@ class Profile:
   def is_comma(self) -> bool:
     return self.provider == 'Webbing' and self.iccid.startswith('8985235')
 
+  @property
+  def display_name(self) -> str:
+    if self.is_comma:
+      return "comma prime"
+    name = self.nickname or self.provider or "<unnamed>"
+    return f"{name} (...{self.iccid[-4:]})"
+
 
 class LPABase(ABC):
   @abstractmethod

openpilot/common/esim/lpa.py

@@ -613,7 +613,7 @@ def parse_lpa_activation_code(activation_code: str) -> tuple[str, str]:
   if not activation_code.startswith("LPA:"):
     raise ValueError("Invalid activation code format")
   parts = activation_code[4:].split("$")
-  if len(parts) != 3:
+  if len(parts) != 3 or not all(parts):
     raise ValueError("Invalid activation code format")
   return parts[1], parts[2]
 

openpilot/common/file_chunker.py

@@ -24,6 +24,7 @@ def chunk_file(path, targets):
   manifest_path, *chunk_paths = targets
   actual_num_chunks = max(1, math.ceil(os.path.getsize(path) / CHUNK_SIZE))
   assert len(chunk_paths) >= actual_num_chunks, f"Allowed {len(chunk_paths)} chunks but needs at least {actual_num_chunks}, for path {path}"
+  Path(manifest_path).unlink(missing_ok=True)
   with open(path, 'rb') as f:
     for chunk_path in chunk_paths:
       with open(chunk_path, 'wb') as out:
@@ -31,14 +32,6 @@ def chunk_file(path, targets):
   Path(manifest_path).write_text(str(len(chunk_paths)))
   os.remove(path)
 
-def get_existing_chunks(path):
-  if os.path.isfile(path):
-    return [path]
-  if os.path.isfile(manifest := get_manifest_path(path)):
-    num_chunks = int(Path(manifest).read_text().strip())
-    return _chunk_paths(path, num_chunks)
-  raise FileNotFoundError(path)
-
 class ChunkStream(io.RawIOBase):
   def __init__(self, paths):
     self._paths = iter(paths)
@@ -66,11 +59,11 @@ class ChunkStream(io.RawIOBase):
 
 def open_file_chunked(path):
   manifest_path = get_manifest_path(path)
-  if os.path.isfile(manifest_path):
+  if os.path.isfile(path):
+    paths = [path]
+  elif os.path.isfile(manifest_path):
     num_chunks = int(Path(manifest_path).read_text().strip())
     paths = [get_chunk_name(path, i, num_chunks) for i in range(num_chunks)]
-  elif os.path.isfile(path):
-    paths = [path]
   else:
     raise FileNotFoundError(path)
   return io.BufferedReader(ChunkStream(paths))

openpilot/common/hardware/base.h

@@ -15,7 +15,7 @@ public:
 
   static std::string get_serial() { return "cccccc"; }
 
-  static std::map<std::string, std::string> get_init_logs() {
+  static std::map<std::string, std::string> get_init_logs(bool route_log = false) {
     return {};
   }
 

openpilot/common/hardware/base.py

@@ -145,6 +145,9 @@ class HardwareBase(ABC):
   def get_modem_temperatures(self):
     return []
 
+  def get_modem_state(self) -> dict:
+    return {}
+
   def initialize_hardware(self):
     pass
 

openpilot/common/hardware/comma/agnos.json

@@ -56,29 +56,29 @@
   },
   {
     "name": "boot",
-    "url": "https://commadist.azureedge.net/agnosupdate/boot-b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd.img.xz",
-    "hash": "b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd",
-    "hash_raw": "b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd",
+    "url": "https://commadist.azureedge.net/agnosupdate/boot-6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d.img.xz",
+    "hash": "6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d",
+    "hash_raw": "6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d",
     "size": 46897152,
     "sparse": false,
     "full_check": true,
     "has_ab": true,
-    "ondevice_hash": "6650e4c46df99ae6dfd6ee895a34b8a2a3cc490a8ce18e16cc3c451c3f822b6e"
+    "ondevice_hash": "d12e1e5b9455b62a1464558716493b33e470d7a7e88da1c4105a3b21d0961808"
   },
   {
     "name": "system",
-    "url": "https://commadist.azureedge.net/agnosupdate/system-5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3.img.xz",
-    "hash": "b134fd04e9da27fa1d359ea0f2742c216fa21a08b5c47e9be22ab3b0563d9b9b",
-    "hash_raw": "5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3",
+    "url": "https://commadist.azureedge.net/agnosupdate/system-3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f.img.xz",
+    "hash": "74ffc9c551e1f29cda897ace8a69080fe644f8039977c6885f2b48362e39b744",
+    "hash_raw": "3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f",
     "size": 4718592000,
     "sparse": true,
     "full_check": false,
     "has_ab": true,
-    "ondevice_hash": "91242772af771ae96fe2eebc105f2b80a7e1dbaaf6003c2574b62d51b806f468",
+    "ondevice_hash": "6a992680183685eea9db99d915219a37935f45989330d9b619e880450257f448",
     "alt": {
-      "hash": "5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3",
-      "url": "https://commadist.azureedge.net/agnosupdate/system-5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3.img",
+      "hash": "3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f",
+      "url": "https://commadist.azureedge.net/agnosupdate/system-3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f.img",
       "size": 4718592000
     }
   }
-]
+]

openpilot/common/hardware/comma/hardware.h

@@ -59,7 +59,7 @@ public:
     std::ofstream("/sys/class/leds/led:switch_2/brightness") << value << "\n";
   }
 
-  static std::map<std::string, std::string> get_init_logs() {
+  static std::map<std::string, std::string> get_init_logs(bool route_log = false) {
     std::map<std::string, std::string> ret = {
       {"/BUILD", util::read_file("/BUILD")},
       {"lsblk", util::check_output("lsblk -o NAME,SIZE,STATE,VENDOR,MODEL,REV,SERIAL")},
@@ -73,12 +73,14 @@ public:
     temp.erase(temp.find_last_not_of(std::string("\0\r\n", 3))+1);
     ret["boot temp"] = temp;
 
-    // TODO: log something from system and boot
-    for (std::string part : {"xbl", "abl", "aop", "devcfg", "xbl_config"}) {
-      for (std::string slot : {"a", "b"}) {
-        std::string partition = part + "_" + slot;
-        std::string hash = util::check_output("sha256sum /dev/disk/by-partlabel/" + partition);
-        ret[partition] = hash.substr(0, hash.find_first_of(" "));
+    // TODO: these are too slow to do on route log inits. need to do it async?
+    if (!route_log) {
+      for (std::string part : {"xbl", "abl", "aop", "devcfg", "xbl_config"}) {
+        for (std::string slot : {"a", "b"}) {
+          std::string partition = part + "_" + slot;
+          std::string hash = util::check_output("sha256sum /dev/disk/by-partlabel/" + partition);
+          ret[partition] = hash.substr(0, hash.find_first_of(" "));
+        }
       }
     }
 

openpilot/common/hardware/comma/modem.py

@@ -5,6 +5,7 @@ import logging
 import os
 import select
 import signal
+import string
 import struct
 import subprocess
 import tempfile
@@ -354,7 +355,7 @@ class Modem:
       imei = ""
 
     iccid = (self._atv("AT+QCCID", "+QCCID:") or "").rstrip("F")
-    if not iccid.isdigit():
+    if not all(c in string.hexdigits for c in iccid):
       iccid = ""
 
     imsi = first_line("AT+CIMI")

openpilot/common/hardware/comma/power_monitor.py

@@ -9,22 +9,25 @@ from openpilot.common.realtime import Ratekeeper
 from openpilot.common.filter_simple import FirstOrderFilter
 
 
-def read_power():
+def read_power(panda=None):
+  if panda is not None and panda.get_type() == panda.HW_TYPE_CUATRO:
+    health = panda.health()
+    return health['voltage'] * health['current'] / 1e6
   with open("/sys/bus/i2c/devices/0-0040/hwmon/hwmon1/power1_input") as f:
     return int(f.read()) / 1e6
 
-def sample_power(seconds=5) -> list[float]:
+def sample_power(seconds=5, panda=None) -> list[float]:
   rate = 123
   rk = Ratekeeper(rate, print_delay_threshold=None)
 
   pwrs = []
   for _ in range(rate*seconds):
-    pwrs.append(read_power())
+    pwrs.append(read_power(panda))
     rk.keep_time()
   return pwrs
 
-def get_power(seconds=5):
-  pwrs = sample_power(seconds)
+def get_power(seconds=5, panda=None):
+  pwrs = sample_power(seconds, panda)
   return np.mean(pwrs)
 
 def wait_for_power(min_pwr, max_pwr, min_secs_in_range, timeout):

openpilot/common/hardware/comma/updater

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3a94ab8395f20d20a9d5a2a2bacca0694f072df8421cf13adca6250d28065bdc
-size 24709205
+oid sha256:6a7adb302d378dda7b1788a841b89e4f905c872550a70a76650dcde977b4ece0
+size 24709209

openpilot/common/hardware/usb.py

@@ -4,11 +4,17 @@ from pathlib import Path
 CHESTNUT_FW_VERSION = "ed4e39b7"
 CHESTNUT_USB_IDS = ((0xADD1, 0x0001), (0x3801, 0x0001))
 CHESTNUT_ROM_USB_IDS = ((0x174C, 0x2464), (0x174C, 0x2463))
+CHESTNUT_USB_PRODUCT = f"custom {CHESTNUT_FW_VERSION}-CLEAN"
 USB_DEVICES_PATH = Path("/sys/bus/usb/devices")
 TYPEC_CC_ORIENTATION_PATH = Path("/sys/class/power_supply/usb/typec_cc_orientation")
 PRIMARY_USB_CONTROLLER = "a600000.ssusb"
 
 
+def is_chestnut_usb_id(vendor_id: int, product_id: int, include_bootloader: bool = False) -> bool:
+  ids = CHESTNUT_USB_IDS + CHESTNUT_ROM_USB_IDS if include_bootloader else CHESTNUT_USB_IDS
+  return (vendor_id, product_id) in ids
+
+
 def get_usb_topology() -> set[str]:
   try:
     return set(os.listdir(USB_DEVICES_PATH))
@@ -81,7 +87,7 @@ def set_usb_state(device_state, devices: list[dict]) -> None:
     entry.linkErrorCount = device["linkErrorCount"]
     entry.usb3Lane = device.get("usb3Lane", "unknown")
 
-    if (entry.vendorId, entry.productId) in CHESTNUT_USB_IDS:
+    if is_chestnut_usb_id(entry.vendorId, entry.productId):
       chestnut_present = True
 
   device_state.chestnutPresent = chestnut_present

openpilot/common/params_keys.h

@@ -28,6 +28,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"ControlsReady", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"CurrentBootlog", {PERSISTENT, STRING}},
     {"CurrentRoute", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
+    {"DisableDriverCameraIR", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"DisableLogging", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"DisablePowerDown", {PERSISTENT | BACKUP, BOOL}},
     {"DisableUpdates", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -59,7 +60,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"IsDriverViewEnabled", {CLEAR_ON_MANAGER_START, BOOL}},
     {"IsEngaged", {PERSISTENT, BOOL}},
     {"IsLdwEnabled", {PERSISTENT | BACKUP, BOOL}},
-    {"IsLiveStreaming", {CLEAR_ON_MANAGER_START, BOOL}},
+    {"IsLiveStreaming", {CLEAR_ON_MANAGER_START | CLEAR_ON_IGNITION_ON, BOOL}},
     {"IsMetric", {PERSISTENT | BACKUP, BOOL}},
     {"IsOffroad", {CLEAR_ON_MANAGER_START, BOOL}},
     {"IsRhdDetected", {PERSISTENT, BOOL}},
@@ -91,10 +92,16 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"ObdMultiplexingChanged", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"ObdMultiplexingEnabled", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"Offroad_CarUnrecognized", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutBranch", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutNotDetected", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutOverheated", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutPcieUnavailable", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutUncompiled", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutUpdateFailed", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutUsbSlow", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
     {"Offroad_ConnectivityNeeded", {CLEAR_ON_MANAGER_START, JSON}},
     {"Offroad_ConnectivityNeededPrompt", {CLEAR_ON_MANAGER_START, JSON}},
     {"Offroad_ExcessiveActuation", {PERSISTENT, JSON}},
-    {"Offroad_NeosUpdate", {CLEAR_ON_MANAGER_START, JSON}},
     {"Offroad_NoFirmware", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
     {"Offroad_Recalibration", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
     {"Offroad_TemperatureTooHigh", {CLEAR_ON_MANAGER_START, JSON}},
@@ -130,8 +137,8 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"UpdaterLastFetchTime", {PERSISTENT, TIME}},
     {"UptimeOffroad", {PERSISTENT, FLOAT, "0.0"}},
     {"UptimeOnroad", {PERSISTENT, FLOAT, "0.0"}},
-    {"UsbGpuActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
-    {"UsbGpuLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"ChestnutActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"ChestnutLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
     {"Version", {PERSISTENT, STRING}},
 
     // --- sunnypilot params --- //
@@ -186,7 +193,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"ShowTurnSignals", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"StandstillTimer", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"TrueVEgoUI", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"CustomButtonAction", {PERSISTENT | BACKUP, INT, "0"}},
 
     // MADS params
     {"Mads", {PERSISTENT | BACKUP, BOOL, "1"}},
@@ -196,11 +202,16 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
 
     // Model Manager params
     {"ModelManager_ActiveBundle", {PERSISTENT, JSON}},
+    {"ModelManager_ActiveBundleUSBGPU", {PERSISTENT, JSON}}, //TODO-SP: kept for migration, remove on next sync?
+    {"ModelManager_ActiveBundleChestnut", {PERSISTENT, JSON}},
+    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, JSON}},
     {"ModelManager_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
-    {"ModelManager_DownloadIndex", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, INT}},
+    {"ModelManager_DownloadRef", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
     {"ModelManager_Favs", {PERSISTENT | BACKUP, STRING}},
     {"ModelManager_LastSyncTime", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
+    {"ModelManager_LastSyncTime_Chestnut", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
     {"ModelManager_ModelsCache", {PERSISTENT | BACKUP, JSON}},
+    {"ModelManager_ModelsCache_Chestnut", {PERSISTENT | BACKUP, JSON}},
 
     // Neural Network Lateral Control
     {"NeuralNetworkLateralControl", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -243,6 +254,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
 
     // mapd
     {"MapAdvisorySpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, FLOAT}},
+    {"Mapd_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
     {"MapdVersion", {PERSISTENT, STRING}},
     {"MapSpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, FLOAT, "0.0"}},
     {"NextMapSpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, JSON}},

openpilot/common/prefix.h

@@ -27,14 +27,14 @@ public:
     auto param_path = Params().getParamPath();
     if (util::file_exists(param_path)) {
       std::string real_path = util::readlink(param_path);
-      util::check_system(util::string_format("rm %s -rf", real_path.c_str()));
+      util::check_system(util::string_format("rm -rf %s", real_path.c_str()));
       unlink(param_path.c_str());
     }
     if (getenv("COMMA_CACHE") == nullptr) {
-      util::check_system(util::string_format("rm %s -rf", Path::download_cache_root().c_str()));
+      util::check_system(util::string_format("rm -rf %s", Path::download_cache_root().c_str()));
     }
-    util::check_system(util::string_format("rm %s -rf", Path::comma_home().c_str()));
-    util::check_system(util::string_format("rm %s -rf", msgq_path.c_str()));
+    util::check_system(util::string_format("rm -rf %s", Path::comma_home().c_str()));
+    util::check_system(util::string_format("rm -rf %s", msgq_path.c_str()));
     unsetenv("OPENPILOT_PREFIX");
   }
 

openpilot/common/qrcode.py

@@ -1,16 +1,47 @@
-"""Small QR encoder for the UI's byte-mode, error-correction-level-L codes."""
+"""QR code encoding, decoding, and UI textures."""
+
+import functools
+import itertools
 
 import numpy as np
 import pyray as rl
 
 
-# Indexes are QR versions. These are the only two Reed-Solomon parameters needed
-# for error-correction level L.
-_ECC_LEN = (0, 7, 10, 15, 20, 26, 18, 20, 24, 30, 18, 20, 24, 26, 30, 22, 24, 28, 30, 28, 28)
-_NUM_BLOCKS = (0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 4, 4, 4, 4, 4, 6, 6, 6, 6, 7, 8)
+# (ec codewords per block, block count) for levels L, M, Q, H, versions 1-40
+_EC = [
+  ((7, 1), (10, 1), (13, 1), (17, 1)), ((10, 1), (16, 1), (22, 1), (28, 1)), ((15, 1), (26, 1), (18, 2), (22, 2)),
+  ((20, 1), (18, 2), (26, 2), (16, 4)), ((26, 1), (24, 2), (18, 4), (22, 4)), ((18, 2), (16, 4), (24, 4), (28, 4)),
+  ((20, 2), (18, 4), (18, 6), (26, 5)), ((24, 2), (22, 4), (22, 6), (26, 6)), ((30, 2), (22, 5), (20, 8), (24, 8)),
+  ((18, 4), (26, 5), (24, 8), (28, 8)), ((20, 4), (30, 5), (28, 8), (24, 11)), ((24, 4), (22, 8), (26, 10), (28, 11)),
+  ((26, 4), (22, 9), (24, 12), (22, 16)), ((30, 4), (24, 9), (20, 16), (24, 16)), ((22, 6), (24, 10), (30, 12), (24, 18)),
+  ((24, 6), (28, 10), (24, 17), (30, 16)), ((28, 6), (28, 11), (28, 16), (28, 19)), ((30, 6), (26, 13), (28, 18), (28, 21)),
+  ((28, 7), (26, 14), (26, 21), (26, 25)), ((28, 8), (26, 16), (30, 20), (28, 25)), ((28, 8), (26, 17), (28, 23), (30, 25)),
+  ((28, 9), (28, 17), (30, 23), (24, 34)), ((30, 9), (28, 18), (30, 25), (30, 30)), ((30, 10), (28, 20), (30, 27), (30, 32)),
+  ((26, 12), (28, 21), (30, 29), (30, 35)), ((28, 12), (28, 23), (28, 34), (30, 37)), ((30, 12), (28, 25), (30, 34), (30, 40)),
+  ((30, 13), (28, 26), (30, 35), (30, 42)), ((30, 14), (28, 28), (30, 38), (30, 45)), ((30, 15), (28, 29), (30, 40), (30, 48)),
+  ((30, 16), (28, 31), (30, 43), (30, 51)), ((30, 17), (28, 33), (30, 45), (30, 54)), ((30, 18), (28, 35), (30, 48), (30, 57)),
+  ((30, 19), (28, 37), (30, 51), (30, 60)), ((30, 19), (28, 38), (30, 53), (30, 63)), ((30, 20), (28, 40), (30, 56), (30, 66)),
+  ((30, 21), (28, 43), (30, 59), (30, 70)), ((30, 22), (28, 45), (30, 62), (30, 74)), ((30, 24), (28, 47), (30, 65), (30, 77)),
+  ((30, 25), (28, 49), (30, 68), (30, 81)),
+]
 
-# 15 format-info bits for level L (01) with mask 0: ((0x08 << 10) | bch_remainder) ^ 0x5412
-_FORMAT_BITS = 0b111011111000100
+# GF(256) with the QR polynomial x^8 + x^4 + x^3 + x^2 + 1: powers of alpha and their logs
+_EXP = [1]
+for _ in range(254):
+  _EXP.append(_EXP[-1] << 1 ^ (0x11D if _EXP[-1] & 0x80 else 0))
+_LOG = {v: i for i, v in enumerate(_EXP)}
+
+
+def _bch_format(data: int) -> int:
+  v = data << 10
+  for shift in range(14, 9, -1):
+    if v >> shift & 1:
+      v ^= 0x537 << (shift - 10)
+  return (data << 10 | v) ^ 0x5412
+
+
+# 15-bit format info indexed by (level bits << 3 | mask). Level bits: L=01, M=00, Q=11, H=10.
+_FORMATS = [_bch_format(d) for d in range(32)]
 
 
 def _raw_modules(version: int) -> int:
@@ -21,8 +52,24 @@ def _raw_modules(version: int) -> int:
   return result - (36 if version >= 7 else 0)
 
 
+def _block_lengths(version: int, level: int) -> list[int]:
+  """Data codewords per Reed-Solomon block. The last blocks may be one longer."""
+  ec, nblocks = _EC[version - 1][level]
+  total = _raw_modules(version) // 8 - ec * nblocks
+  return [total // nblocks + (i >= nblocks - total % nblocks) for i in range(nblocks)]
+
+
+def _interleaved(version: int, level: int) -> list[tuple[int, int]]:
+  """(block, index within block) of each transmitted codeword: data column-major, then ECC column-major."""
+  ec, nblocks = _EC[version - 1][level]
+  lens = _block_lengths(version, level)
+  data = [(b, i) for i in range(max(lens)) for b in range(nblocks) if i < lens[b]]
+  ecc = [(b, lens[b] + i) for i in range(ec) for b in range(nblocks)]
+  return data + ecc
+
+
 def _capacity(version: int) -> int:
-  return _raw_modules(version) // 8 - _ECC_LEN[version] * _NUM_BLOCKS[version]
+  return sum(_block_lengths(version, 0))
 
 
 def _append_bits(bits: list[int], value: int, length: int) -> None:
@@ -49,37 +96,18 @@ def _data_codewords(data: bytes, version: int) -> bytes:
 def _codewords(data: bytes, version: int) -> bytes:
   """Split data codewords into Reed-Solomon blocks and interleave data + ECC."""
   data = _data_codewords(data, version)
-  num_blocks = _NUM_BLOCKS[version]
-  ecc_len = _ECC_LEN[version]
-  raw_codewords = _raw_modules(version) // 8
-  short_len = raw_codewords // num_blocks
-  num_short = num_blocks - raw_codewords % num_blocks
-  divisor = _divisor(ecc_len)
-  blocks: list[tuple[bytes, bytes]] = []
+  divisor = _divisor(_EC[version - 1][0][0])
+  blocks = []
   offset = 0
-  for i in range(num_blocks):
-    length = short_len - ecc_len + (0 if i < num_short else 1)
+  for length in _block_lengths(version, 0):
     block = data[offset:offset + length]
-    blocks.append((block, _remainder(block, divisor)))
+    blocks.append(block + _remainder(block, divisor))
     offset += length
-  result = bytearray()
-  for i in range(short_len - ecc_len + 1):
-    for block, _ in blocks:
-      result.extend(block[i:i + 1])
-  for i in range(ecc_len):
-    for _, ecc in blocks:
-      result.append(ecc[i])
-  return bytes(result)
+  return bytes(blocks[b][i] for b, i in _interleaved(version, 0))
 
 
 def _multiply(x: int, y: int) -> int:
-  result = 0
-  for _ in range(8):
-    result = (result << 1) ^ (0x11D if result & 0x80 else 0)
-    if y & 0x80:
-      result ^= x
-    y <<= 1
-  return result
+  return _EXP[(_LOG[x] + _LOG[y]) % 255] if x and y else 0
 
 
 def _divisor(degree: int) -> bytes:
@@ -108,7 +136,7 @@ def _alignment_positions(version: int) -> list[int]:
   if version == 1:
     return []
   count = version // 7 + 2
-  step = ((version * 4 + count * 2 + 1) // (count * 2 - 2)) * 2
+  step = (version * 8 + count * 3 + 5) // (count * 4 - 4) * 2
   return [6] + [version * 4 + 10 - step * i for i in range(count - 1)][::-1]
 
 
@@ -171,7 +199,7 @@ class _Qr:
 
   def _format(self) -> None:
     for i in range(15):
-      bit = ((_FORMAT_BITS >> i) & 1) != 0
+      bit = ((_FORMATS[1 << 3 | 0] >> i) & 1) != 0  # level L, mask 0
       y_pos = i if i < 6 else i + 1 if i < 8 else self.size - 15 + i
       self._set_function(8, y_pos, bit)
       x_pos = self.size - 1 - i if i < 8 else 15 - i if i < 9 else 14 - i
@@ -216,3 +244,496 @@ def make_texture(data: str, inverted: bool = False) -> rl.Texture:
   rl_image.mipmaps = 1
   rl_image.format = rl.PixelFormat.PIXELFORMAT_UNCOMPRESSED_R8G8B8A8
   return rl.load_texture_from_image(rl_image)
+
+
+# ---- Symbol structure for decoding ----
+
+
+class QRError(Exception):
+  pass
+
+
+_LEVELS = (1, 0, 3, 2)  # format info level bits -> column in _EC
+
+_MASKS = [
+  lambda i, j: (i + j) % 2 == 0,
+  lambda i, j: i % 2 == 0,
+  lambda i, j: j % 3 == 0,
+  lambda i, j: (i + j) % 3 == 0,
+  lambda i, j: (i // 2 + j // 3) % 2 == 0,
+  lambda i, j: (i * j) % 2 + (i * j) % 3 == 0,
+  lambda i, j: ((i * j) % 2 + (i * j) % 3) % 2 == 0,
+  lambda i, j: ((i + j) % 2 + (i * j) % 3) % 2 == 0,
+]
+
+_ALIGNMENT = np.ones((5, 5), dtype=bool)
+_ALIGNMENT[1:4, 1:4] = False
+_ALIGNMENT[2, 2] = True
+
+
+def _gf_inv(a: int) -> int:
+  return _EXP[-_LOG[a] % 255]
+
+
+@functools.lru_cache
+def _data_coords(version: int) -> tuple[np.ndarray, np.ndarray]:
+  """(rows, cols) of the data and error correction modules in placement order: two-column zigzag from the right."""
+  dim = version * 4 + 17
+  func = np.zeros((dim, dim), dtype=bool)  # finder, timing, alignment, format, and version modules
+  func[:9, :9] = func[:9, dim - 8:] = func[dim - 8:, :9] = True
+  func[6, :] = func[:, 6] = True
+  positions = _alignment_positions(version)
+  for r, c in itertools.product(positions, positions):
+    if (r, c) not in ((6, 6), (6, dim - 7), (dim - 7, 6)):
+      func[r - 2:r + 3, c - 2:c + 3] = True
+  if version >= 7:
+    func[:6, dim - 11:dim - 8] = func[dim - 11:dim - 8, :6] = True
+  ys = np.arange(dim)
+  rows, cols = [], []
+  # the vertical timing column is skipped, so the pairs left of it start at odd columns
+  for i, right in enumerate(col if col > 6 else col - 1 for col in range(dim - 1, 0, -2)):
+    r = np.repeat(ys[::-1] if i % 2 == 0 else ys, 2)
+    c = np.tile((right, right - 1), dim)
+    keep = ~func[r, c]
+    rows.append(r[keep])
+    cols.append(c[keep])
+  return np.concatenate(rows), np.concatenate(cols)
+
+
+# ---- Matrix decoding ----
+
+
+def _poly_eval(p: list[int], x: int) -> int:
+  # p is highest degree first
+  y = 0
+  for c in p:
+    y = _multiply(y, x) ^ c
+  return y
+
+
+_EXP_TABLE = np.array(_EXP)
+_LOG_TABLE = np.array([_LOG.get(v, 0) for v in range(256)])
+
+
+def _syndromes(msg: list[int], nsym: int) -> list[int]:
+  """syn[i] = msg(alpha^i), msg highest degree first."""
+  m = np.array(msg)
+  exponents = np.arange(nsym)[:, None] * (len(msg) - 1 - np.arange(len(msg)))
+  return np.bitwise_xor.reduce(_EXP_TABLE[(_LOG_TABLE[m] + exponents) % 255] * (m != 0), axis=1).tolist()
+
+
+def _rs_correct(msg: list[int], nsym: int) -> list[int]:
+  """Corrects up to nsym // 2 errors in a Reed-Solomon codeword, in place."""
+  n = len(msg)
+  syn = _syndromes(msg, nsym)
+  if not any(syn):
+    return msg
+
+  # Berlekamp-Massey, sigma is lowest degree first
+  sigma, prev, L, m, b = [1], [1], 0, 1, 1
+  for r in range(nsym):
+    d = syn[r]
+    for i in range(1, L + 1):
+      d ^= _multiply(sigma[i], syn[r - i])
+    if d == 0:
+      m += 1
+      continue
+    coef = _multiply(d, _gf_inv(b))
+    shifted = [0] * m + prev
+    saved = sigma[:]
+    sigma = sigma + [0] * max(0, len(shifted) - len(sigma))
+    for i, c in enumerate(shifted):
+      sigma[i] ^= _multiply(coef, c)
+    if 2 * L <= r:
+      L, prev, b, m = r + 1 - L, saved, d, 1
+    else:
+      m += 1
+  sigma = sigma[:L + 1]
+  if 2 * L > nsym:
+    raise QRError("too many errors")
+
+  # Chien search: codeword position p has locator alpha^(n-1-p)
+  positions = [p for p in range(n) if _poly_eval(sigma[::-1], _EXP[(p - n + 1) % 255]) == 0]
+  if len(positions) != L:
+    raise QRError("error locator mismatch")
+
+  # solve syn[i] = sum_k e_k * X_k^i for the magnitudes e_k
+  xlog = [(n - 1 - p) % 255 for p in positions]
+  A = [[_EXP[(xlog[k] * i) % 255] for k in range(L)] + [syn[i]] for i in range(L)]
+  for col in range(L):
+    piv = next((r for r in range(col, L) if A[r][col]), None)
+    if piv is None:
+      raise QRError("singular")
+    A[col], A[piv] = A[piv], A[col]
+    inv = _gf_inv(A[col][col])
+    A[col] = [_multiply(inv, v) for v in A[col]]
+    for r in range(L):
+      if r != col and A[r][col]:
+        f = A[r][col]
+        A[r] = [a ^ _multiply(f, c) for a, c in zip(A[r], A[col], strict=True)]
+  for k, p in enumerate(positions):
+    msg[p] ^= A[k][L]
+
+  if any(_syndromes(msg, nsym)):
+    raise QRError("uncorrectable")
+  return msg
+
+
+def _read_format(m: np.ndarray) -> int:
+  """Returns the closest format info (level bits << 3 | mask) from either copy."""
+  dim = m.shape[0]
+  copies = ([(8, i) for i in range(6)] + [(8, 7), (8, 8), (7, 8)] + [(5 - i, 8) for i in range(6)],
+            [(dim - 1 - i, 8) for i in range(7)] + [(8, dim - 8 + i) for i in range(8)])  # (row, col), msb first
+  candidates = []
+  for coords in copies:
+    bits = int("".join(str(int(m[r, c])) for r, c in coords), 2)
+    candidates += [((bits ^ f).bit_count(), i) for i, f in enumerate(_FORMATS)]
+  distance, fmt = min(candidates)
+  if distance > 3:
+    raise QRError("bad format info")
+  return fmt
+
+
+_ALNUM = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ $%*+-./:"
+
+_ECI_ENCODINGS = {
+  0: "cp437", 2: "cp437", 1: "iso8859-1", 3: "iso8859-1",
+  **{i + 2: f"iso8859-{i}" for i in range(2, 17) if i != 12},
+  20: "shift_jis", 21: "cp1250", 22: "cp1251", 23: "cp1252", 24: "cp1256",
+  25: "utf-16-be", 26: "utf-8", 27: "ascii", 170: "ascii", 28: "big5", 29: "gb18030", 30: "euc_kr",
+}
+
+
+class _Bits:
+  def __init__(self, data: list[int]):
+    self._value = int.from_bytes(bytes(data), "big")
+    self.remaining = len(data) * 8
+
+  def read(self, n: int) -> int:
+    if n > self.remaining:
+      raise QRError("bitstream underflow")
+    self.remaining -= n
+    return self._value >> self.remaining & (1 << n) - 1
+
+  def read_below(self, n: int, limit: int) -> int:
+    v = self.read(n)
+    if v >= limit:
+      raise QRError("value out of range")
+    return v
+
+
+def _parse_data(data: list[int], version: int) -> str:
+  bits = _Bits(data)
+  out: list[str] = []
+  encoding = None
+  band = 0 if version <= 9 else 1 if version <= 26 else 2
+  while bits.remaining >= 4:
+    mode = bits.read(4)
+    if mode == 0:
+      break
+    if mode == 7:  # ECI character set assignment
+      first = bits.read(8)
+      extra = 0 if first < 0x80 else 8 if first < 0xC0 else 16 if first < 0xE0 else -1  # 1, 2, or 3 byte assignment
+      if extra < 0:
+        raise QRError("bad ECI assignment")
+      assignment = (first & 0x7F >> extra // 8) << extra | bits.read(extra)
+      encoding = _ECI_ENCODINGS.get(assignment)
+      if encoding is None:
+        raise QRError(f"unsupported ECI assignment {assignment}")
+    elif mode == 1:
+      n = bits.read((10, 12, 14)[band])
+      while n > 0:
+        k = min(n, 3)  # 3 digits in 10 bits, the last 2 or 1 in 7 or 4
+        out.append(f"{bits.read_below((4, 7, 10)[k - 1], 10 ** k):0{k}d}")
+        n -= k
+    elif mode == 2:
+      n = bits.read((9, 11, 13)[band])
+      while n > 0:
+        k = min(n, 2)  # 2 characters in 11 bits, a last one in 6
+        v = bits.read_below((6, 11)[k - 1], 45 ** k)
+        out.append(_ALNUM[v // 45] * (k - 1) + _ALNUM[v % 45])
+        n -= k
+    elif mode == 4:
+      n = bits.read((8, 16, 16)[band])
+      segment = bytes(bits.read(8) for _ in range(n))
+      try:
+        out.append(segment.decode(encoding or "utf-8"))
+      except UnicodeDecodeError as e:
+        if encoding is not None:
+          raise QRError("invalid ECI byte segment") from e
+        out.append(segment.decode("latin-1"))
+    elif mode == 8:
+      n = bits.read((8, 10, 12)[band])
+      for _ in range(n):
+        v = bits.read(13)
+        c = (v // 0xC0) << 8 | v % 0xC0
+        c += 0x8140 if c < 0x1F00 else 0xC140
+        try:
+          out.append(c.to_bytes(2, "big").decode("shift_jis"))
+        except UnicodeDecodeError as e:
+          raise QRError("invalid Kanji character") from e
+    else:
+      raise QRError(f"unsupported mode {mode}")
+  return "".join(out)
+
+
+def decode_matrix(m: np.ndarray) -> str:
+  """Decodes a square boolean module matrix (True = dark) without a quiet zone."""
+  dim = m.shape[0]
+  if m.shape != (dim, dim) or dim % 4 != 1 or not 21 <= dim <= 177:
+    raise QRError("bad matrix size")
+  version = (dim - 17) // 4
+
+  fmt = _read_format(m)
+  level = _LEVELS[fmt >> 3]
+  rows, cols = _data_coords(version)
+  bits = m[rows, cols] ^ _MASKS[fmt & 7](rows, cols)
+  codewords = np.packbits(bits[:len(bits) // 8 * 8]).tolist()
+
+  ec, _ = _EC[version - 1][level]
+  lens = _block_lengths(version, level)
+  blocks = [[0] * (n + ec) for n in lens]
+  for (b, i), codeword in zip(_interleaved(version, level), codewords, strict=True):
+    blocks[b][i] = codeword
+
+  data: list[int] = []
+  for block, n in zip(blocks, lens, strict=True):
+    data += _rs_correct(block, ec)[:n]
+  return _parse_data(data, version)
+
+
+# ---- Image decoding ----
+
+
+def _box_sums(a: np.ndarray, radii: tuple[int, ...]) -> list[np.ndarray]:
+  """Sums over (2r + 1)^2 neighborhoods of the last two axes, edge padded, from one integral image."""
+  P = max(radii)
+  lead = [(0, 0)] * (a.ndim - 2)
+  cs = np.pad(np.cumsum(np.cumsum(np.pad(a, lead + [(P, P), (P, P)], mode="edge"), -2), -1), lead + [(1, 0), (1, 0)])
+  H, W = a.shape[-2:]
+  out = []
+  for r in radii:
+    lo, hi = P - r, P + r + 1
+    out.append(cs[..., hi:hi + H, hi:hi + W] - cs[..., lo:lo + H, hi:hi + W] - cs[..., hi:hi + H, lo:lo + W] + cs[..., lo:lo + H, lo:lo + W])
+  return out
+
+
+def _binarize(gray: np.ndarray) -> np.ndarray:
+  """Adaptive threshold: each pixel against the mean of the surrounding tiles that have contrast."""
+  h, w = gray.shape
+  if h < 21 or w < 21:
+    raise QRError("image too small")
+  B = max(8, min(h, w) // 128 * 2)
+  H, W = -(-h // B), -(-w // B)
+  padded = np.pad(gray, ((0, H * B - h), (0, W * B - w)), mode="edge")
+  # block statistics from a subsample are plenty
+  sub = np.ascontiguousarray(padded[::2, ::2].reshape(H, B // 2, W, B // 2).transpose(0, 2, 1, 3)).reshape(H, W, -1)
+  blocks = sub.sum(axis=2, dtype=np.uint32) / sub.shape[2]
+  known = sub.max(axis=2) - sub.min(axis=2) >= 32
+  # Flat tiles cannot estimate their own threshold: use the tiles with contrast nearby, then
+  # further out, then the global midrange. A flat tile is then all dark or all light.
+  est = np.full((H, W), (blocks.min() + blocks.max()) / 2)
+  filled = np.zeros((H, W), dtype=bool)
+  for total, count in _box_sums(np.stack((known * blocks, known.astype(float))), (2, 6)):
+    fill = ~filled & (count > 0)
+    est[fill] = total[fill] / count[fill]
+    filled |= fill
+  thr = np.where(known, np.minimum(est, 254) + 1, np.where(blocks <= est, 255, 0)).astype(np.uint8)
+  return (padded.reshape(H, B, W, B) < thr[:, None, :, None]).reshape(H * B, W * B)[:h, :w]
+
+
+class _Runs:
+  """Run-length table of a padded, flattened binary image with a per-pixel run index."""
+
+  def __init__(self, padded: np.ndarray):
+    self.flat = padded.ravel()
+    self.lines, self.stride = padded.shape
+    change = self.flat[1:] != self.flat[:-1]
+    self.starts = np.concatenate(([0], np.flatnonzero(change) + 1))
+    self.lengths = np.diff(np.append(self.starts, self.flat.size)).astype(np.int32)
+
+  def run_at(self, line: np.ndarray, pos: np.ndarray) -> np.ndarray:
+    """Index of the run containing the pixel at `pos` along `line`."""
+    return np.searchsorted(self.starts, line * self.stride + pos + 1, side="right") - 1
+
+  @staticmethod
+  def _match(lengths: list[np.ndarray], ratios: tuple[int, ...]) -> tuple[np.ndarray, np.ndarray]:
+    """Checks windows of runs against the ratios, given the length of each run. Returns (ok, module size)."""
+    S = sum(ratios)
+    total = sum(lengths[1:], start=lengths[0])
+    ok = total >= 2 * S  # modules need to be at least 2 px
+    for L, r in zip(lengths, ratios, strict=True):
+      ok &= np.abs(2 * S * L - 2 * r * total) <= r * total  # integer form of |L - r * total / S| <= r * total / (2 * S)
+    return ok, total / S
+
+  def scan(self, ratios: tuple[int, ...]) -> np.ndarray:
+    """Returns the indices of all dark runs starting a window of runs matching the ratios."""
+    n = len(ratios)
+    N = len(self.lengths) - n + 1
+    if N <= 0:
+      return np.zeros(0, dtype=int)
+    ok, _ = self._match([self.lengths[k:N + k] for k in range(n)], ratios)
+    ok &= self.flat[self.starts[:N]]
+    first = np.flatnonzero(ok)
+    return first[self.starts[first] // self.stride == self.starts[first + n - 1] // self.stride]
+
+  def check(self, first: np.ndarray, ratios: tuple[int, ...]) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+    """Checks the run windows starting at run index `first`. Returns (ok, center position along the line, module size)."""
+    n, half = len(ratios), len(ratios) // 2
+    ok = (first >= 0) & (first + n <= len(self.starts))
+    idx = np.clip(first[:, None] + np.arange(n), 0, len(self.starts) - 1)
+    matched, module = self._match([self.lengths[idx[:, k]] for k in range(n)], ratios)
+    ok &= matched & self.flat[self.starts[idx[:, 0]]]
+    ok &= self.starts[idx[:, 0]] // self.stride == self.starts[idx[:, -1]] // self.stride
+    center = self.starts[idx[:, half]] % self.stride - 1 + self.lengths[idx[:, half]] / 2
+    return ok, center, module
+
+
+def _find_patterns(binary: np.ndarray, ratios: tuple[int, ...]) -> list[tuple[float, float, float]]:
+  """Finds dark/light run patterns with the given module ratios. Returns (x, y, module size)."""
+  half = len(ratios) // 2
+  step = 2  # the center rows of a 2 px finder pattern still get scanned twice
+  rows_t = _Runs(np.pad(binary[::step], ((0, 0), (1, 1))))
+  first = rows_t.scan(ratios)
+  if len(first) == 0:
+    return []
+  _, cx, hmod = rows_t.check(first, ratios)
+  row = rows_t.starts[first] // rows_t.stride * step
+
+  xi = cx.astype(int)
+  xs, col = np.unique(xi, return_inverse=True)
+  cols_t = _Runs(np.pad(binary[:, xs].T, ((0, 0), (1, 1))))
+  ok, cy, vmod = cols_t.check(cols_t.run_at(col, row) - half, ratios)
+  ok &= (0.5 <= vmod / hmod) & (vmod / hmod <= 2)
+  line = np.clip(np.rint(cy / step), 0, rows_t.lines - 1).astype(int)
+  ok2, cx2, hmod2 = rows_t.check(rows_t.run_at(line, xi) - half, ratios)
+  ok &= ok2 & (0.5 <= hmod2 / vmod) & (hmod2 / vmod <= 2)
+
+  found: list[list[float]] = []  # [x, y, module, count]
+  for x, y, module in zip(cx2[ok], cy[ok], (hmod2[ok] + vmod[ok]) / 2, strict=True):
+    for f in found:
+      if abs(f[0] - x) <= f[2] and abs(f[1] - y) <= f[2] and 0.5 <= f[2] / module <= 2:
+        c = f[3]
+        f[0], f[1], f[2], f[3] = (f[0] * c + x) / (c + 1), (f[1] * c + y) / (c + 1), (f[2] * c + module) / (c + 1), c + 1
+        break
+    else:
+      found.append([x, y, module, 1])
+  found.sort(key=lambda f: -f[3])
+  return [(f[0], f[1], f[2]) for f in found if f[3] >= 2]
+
+
+def _pick_finders(patterns: list[tuple[float, float, float]]) -> tuple[np.ndarray, np.ndarray, np.ndarray, float]:
+  """Returns (top-left, top-right, bottom-left) centers and the module size of the most square-looking triple."""
+  best = None
+  for a, b, c in itertools.combinations(patterns[:10], 3):
+    mods = sorted((a[2], b[2], c[2]))
+    if mods[2] / mods[0] > 1.5:
+      continue
+    pts = [np.array(p[:2]) for p in (a, b, c)]
+    d = [np.linalg.norm(pts[(i + 1) % 3] - pts[(i + 2) % 3]) for i in range(3)]
+    tl = int(np.argmax(d))  # opposite the hypotenuse
+    p1, p2 = pts[(tl + 1) % 3], pts[(tl + 2) % 3]
+    v1, v2 = p1 - pts[tl], p2 - pts[tl]
+    n1, n2 = np.linalg.norm(v1), np.linalg.norm(v2)
+    if n1 == 0 or n2 == 0:
+      continue
+    cos = abs(np.dot(v1, v2)) / (n1 * n2)
+    if cos > 0.35 or not 0.6 <= n1 / n2 <= 1.6:
+      continue
+    score = cos + abs(np.log(n1 / n2)) + np.log(mods[2] / mods[0])
+    if best is not None and score >= best[0]:
+      continue
+    if v1[0] * v2[1] - v1[1] * v2[0] < 0:
+      p1, p2 = p2, p1
+    best = (score, pts[tl], p1, p2, float(sum(mods) / 3))
+  if best is None:
+    raise QRError("no finder patterns")
+  return best[1:]
+
+
+def _perspective(src: np.ndarray, dst: np.ndarray) -> np.ndarray:
+  """Homography mapping the four src points onto the four dst points."""
+  A = [row for (x, y), (u, v) in zip(src, dst, strict=True)
+       for row in ([x, y, 1, 0, 0, 0, -u * x, -u * y], [0, 0, 0, x, y, 1, -v * x, -v * y])]
+  try:
+    h = np.linalg.solve(np.array(A, dtype=float), np.asarray(dst, dtype=float).ravel())
+  except np.linalg.LinAlgError as e:
+    raise QRError("degenerate geometry") from e
+  return np.append(h, 1).reshape(3, 3)
+
+
+def _transform(H: np.ndarray, pts: np.ndarray) -> np.ndarray:
+  p = np.column_stack((pts, np.ones(len(pts)))) @ H.T
+  return p[:, :2] / p[:, 2:3]
+
+
+def _match_alignment(binary: np.ndarray, est: np.ndarray, offs: np.ndarray, r: int, module: float) -> np.ndarray | None:
+  h, w = binary.shape
+  dy = np.arange(max(0, int(est[1]) - r), min(h, int(est[1]) + r)) - est[1]
+  dx = np.arange(max(0, int(est[0]) - r), min(w, int(est[0]) + r)) - est[0]
+  if len(dy) == 0 or len(dx) == 0:
+    return None
+  y = np.rint(est[1] + dy[:, None, None] + offs[None, None, :, 1]).astype(int)
+  x = np.rint(est[0] + dx[None, :, None] + offs[None, None, :, 0]).astype(int)
+  valid = ((y >= 0) & (y < h) & (x >= 0) & (x < w)).all(axis=2)
+  samples = binary[np.clip(y, 0, h - 1), np.clip(x, 0, w - 1)]
+  score = np.where(valid, (samples == _ALIGNMENT.ravel()).sum(axis=2), 0)
+  if score.max() < 23:
+    return None
+  hits = np.argwhere(score == score.max())
+  centers = np.column_stack((est[0] + dx[hits[:, 1]], est[1] + dy[hits[:, 0]]))
+  closest = centers[np.argmin(np.linalg.norm(centers - est, axis=1))]
+  return centers[np.linalg.norm(centers - closest, axis=1) <= module / 2].mean(axis=0)
+
+
+def _locate_alignment(binary: np.ndarray, H: np.ndarray, center: float, module: float) -> np.ndarray | None:
+  """Template matches the 5x5 alignment pattern around its position estimated from H."""
+  grid = np.mgrid[-2:3, -2:3].reshape(2, -1).T[:, ::-1] + center  # (25, 2) module coords (x, y)
+  pts = _transform(H, grid)
+  # the affine estimate can be off in both position and local scale under perspective
+  for radius in (2, 4, 8, 16):
+    for scale in (1.0, 0.8, 1.25, 0.65, 1.5):
+      found = _match_alignment(binary, pts[12], (pts - pts[12]) * scale, int(module * radius), module)
+      if found is not None:
+        return found
+  return None
+
+
+def _sample(binary: np.ndarray, tl: np.ndarray, tr: np.ndarray, bl: np.ndarray, module: float, dim: int, use_alignment: bool) -> np.ndarray:
+  src = np.array([(3.5, 3.5), (dim - 3.5, 3.5), (3.5, dim - 3.5), (dim - 3.5, dim - 3.5)])
+  dst = np.array([tl, tr, bl, tr + bl - tl])
+  H = _perspective(src, dst)
+  if use_alignment and dim > 21:
+    align = _locate_alignment(binary, H, dim - 6.5, module)
+    if align is not None:
+      src[3], dst[3] = (dim - 6.5, dim - 6.5), align
+      H = _perspective(src, dst)
+
+  rows, cols = np.mgrid[0:dim, 0:dim]
+  pts = _transform(H, np.column_stack((cols.ravel() + 0.5, rows.ravel() + 0.5)))
+  xy = np.rint(pts).astype(int)
+  h, w = binary.shape
+  if (xy < 0).any() or (xy[:, 0] >= w).any() or (xy[:, 1] >= h).any():
+    raise QRError("code extends outside image")
+  return binary[xy[:, 1], xy[:, 0]].reshape(dim, dim)
+
+
+def decode(gray: np.ndarray) -> str | None:
+  """Decodes the QR code in a 2D uint8 grayscale image. Modules need to be at least 2 px.
+  Returns None if nothing could be decoded."""
+  try:
+    binary = _binarize(gray)
+    tl, tr, bl, module = _pick_finders(_find_patterns(binary, (1, 1, 3, 1, 1)))
+  except QRError:
+    return None
+
+  d = (np.linalg.norm(tr - tl) + np.linalg.norm(bl - tl)) / 2
+  dim = int(round((d / module + 7 - 17) / 4)) * 4 + 17
+  dims = [cand for cand in (dim, dim - 4, dim + 4) if 21 <= cand <= 177]
+  for cand, use_alignment, transpose in itertools.product(dims, (True, False), (False, True)):
+    try:
+      m = _sample(binary, tl, tr, bl, module, cand, use_alignment)
+      return decode_matrix(m.T if transpose else m)
+    except QRError:
+      pass
+  return None

openpilot/common/tests/test_qrcode.py

@@ -0,0 +1,178 @@
+import hashlib
+import math
+from pathlib import Path
+
+import numpy as np
+
+from openpilot.common import qrcode as qr
+from openpilot.common.test import OpenpilotTestCase
+
+LPA = "LPA:1$rsp.truphone.com$QRF-BETTERROAMING-PMRDGIR2EARDEIT5"
+
+
+# Matrices generated with python-qrcode 8.2, covering all versions and EC levels.
+# Packed fixtures keep the decoder tests independent of our encoder.
+FIXTURES = {}
+for path in Path(__file__).with_name("fixtures").glob("qrcode_*.npz"):
+  with np.load(path) as fixtures:
+    FIXTURES.update({key: fixtures[key] for key in fixtures.files})
+
+
+def fixture(key: str) -> np.ndarray:
+  bits = np.unpackbits(FIXTURES[key])
+  size = math.isqrt(len(bits))
+  return bits[:size * size].reshape(size, size).astype(bool)
+
+
+def render(matrix: np.ndarray, box: int = 6, border: int = 4) -> np.ndarray:
+  img = np.repeat(np.repeat(np.pad(matrix, border), box, axis=0), box, axis=1)
+  return np.where(img, 0, 255).astype(np.uint8)
+
+
+def make(data: str, version: int | None = None, level: int = 0, box: int = 6, border: int = 4):
+  matrix = fixture(hashlib.sha256(f"{version}:{level}:{data}".encode()).hexdigest())
+  return matrix, render(matrix, box, border)
+
+
+def warp(img: np.ndarray, H: np.ndarray) -> np.ndarray:
+  """Bilinear resampling through the output -> input homography H, white outside the image."""
+  h, w = img.shape
+  rows, cols = np.mgrid[0:h, 0:w]
+  pts = qr._transform(H, np.column_stack((cols.ravel() + 0.5, rows.ravel() + 0.5))) - 0.5
+  x0, y0 = np.floor(pts[:, 0]).astype(int), np.floor(pts[:, 1]).astype(int)
+  fx, fy = pts[:, 0] - x0, pts[:, 1] - y0
+  padded = np.pad(img.astype(float), 1, constant_values=255)
+
+  def at(y, x):
+    return padded[np.clip(y + 1, 0, h + 1), np.clip(x + 1, 0, w + 1)]
+
+  out = at(y0, x0) * (1 - fx) * (1 - fy) + at(y0, x0 + 1) * fx * (1 - fy) + at(y0 + 1, x0) * (1 - fx) * fy + at(y0 + 1, x0 + 1) * fx * fy
+  return np.clip(out, 0, 255).astype(np.uint8).reshape(h, w)
+
+
+def rotate(img: np.ndarray, angle: float) -> np.ndarray:
+  h, w = img.shape
+  t = np.radians(angle)
+  R = np.array([[np.cos(t), -np.sin(t)], [np.sin(t), np.cos(t)]])
+  center = np.array([w / 2, h / 2])
+  corners = np.array([(0, 0), (w, 0), (w, h), (0, h)], dtype=float)
+  return warp(img, qr._perspective((corners - center) @ R.T + center, corners))
+
+
+class TestQRCode(OpenpilotTestCase):
+  def test_alignment_positions(self):
+    assert qr._alignment_positions(7) == [6, 22, 38]
+    assert qr._alignment_positions(32) == [6, 34, 60, 86, 112, 138]
+    assert qr._alignment_positions(40) == [6, 30, 58, 86, 114, 142, 170]
+
+  def test_all_versions(self):
+    for version in range(1, 41):
+      for level in range(4):
+        with self.subTest(version=version, level=level):
+          data = "".join(chr(ord("a") + i % 26) for i in range(version))
+          matrix, img = make(data, version, level, box=3)
+          assert qr.decode_matrix(matrix) == data
+          assert qr.decode(img) == data
+
+  def test_modes(self):
+    for data in ["0123456789012345", "HELLO WORLD $1.50", LPA, "こんにちは", "ünïcødé", "mixed 123 ABC xyz"]:
+      with self.subTest(data=data):
+        matrix, img = make(data)
+        assert qr.decode_matrix(matrix) == data
+        assert qr.decode(img) == data
+
+  def test_error_correction(self):
+    matrix, _ = make(LPA, level=2)
+    rng = np.random.default_rng(0)
+    flipped = matrix.copy()
+    for r, c in rng.integers(9, matrix.shape[0] - 9, size=(40, 2)):
+      flipped[r, c] ^= True
+    assert qr.decode_matrix(flipped) == LPA
+
+  def test_large_modules(self):
+    for data in ["0123456789012345", "HELLO WORLD $1.50", LPA, "mixed 123 ABC xyz"]:
+      for box in [16, 20, 24, 32]:
+        for dark, light in [(0, 255), (60, 200), (140, 250)]:
+          with self.subTest(data=data, box=box, dark=dark):
+            _, img = make(data, box=box)
+            img = np.where(img == 0, dark, light).astype(np.uint8)
+            assert qr.decode(img) == data
+
+  def test_image_edges(self):
+    # a code touching the image edge must not lose the rows and columns left over from tiling
+    matrix, _ = make(LPA)
+    for size in (200, 203):
+      with self.subTest(size=size):
+        img = np.full((size, size), 255, dtype=np.uint8)
+        code = render(matrix, box=5, border=0)
+        img[size - code.shape[0]:, size - code.shape[1]:] = code
+        assert qr.decode(img) == LPA
+
+  def test_eci(self):
+    # qrcode_eci.npz: packed Segno 1.6.6 matrices, generated with mode='byte',
+    # eci=True, micro=False and the named encoding. Mixed also includes numeric,
+    # alphanumeric, and Kanji segments after changing the byte encoding twice.
+    cases = {
+      "iso8859-5": "Привет", "utf-16-be": "héllo", "utf-8": "こんにちは",
+      "shift_jis": "日本語", "cp1251": "Привет", "iso8859-1": "héllo",
+      "mixed": "hélloПривет日本語123ABC漢字",
+    }
+    for encoding, expected in cases.items():
+      with self.subTest(encoding=encoding):
+        matrix = fixture(encoding)
+        assert qr.decode_matrix(matrix) == expected
+        assert qr.decode(render(matrix)) == expected
+
+  def test_parse_data(self):
+    def parse(stream: str) -> str:
+      stream += '0' * (-len(stream) % 8)
+      return qr._parse_data([int(stream[i:i + 8], 2) for i in range(0, len(stream), 8)], 1)
+
+    def eci(assignment: str, payload: bytes = b'A') -> str:
+      return parse('0111' + assignment + '0100' + f'{len(payload):08b}' + ''.join(f'{b:08b}' for b in payload) + '0000')
+
+    # ASCII assignment 170 uses the two-byte ECI representation.
+    assert eci('1000000010101010') == 'A'
+    for assignment in ['00001110', '1000001111100111', '110000010000000000000000', '11100000']:
+      with self.subTest(assignment=assignment), self.assertRaises(qr.QRError):
+        eci(assignment)
+    with self.assertRaises(qr.QRError):
+      eci('00011010', b'\xff')  # Invalid UTF-8 must not fall back to Latin-1.
+
+    # out-of-range numeric, alphanumeric, and Kanji values are format errors, not crashes
+    for stream in ['0001' + '0000000011' + '1111111111', '0001' + '0000000010' + '1111111',
+                   '0010' + '000000010' + '11111111111', '0010' + '000000001' + '111111',
+                   '1000' + '00000001' + '0000000111111']:
+      with self.subTest(stream=stream), self.assertRaises(qr.QRError):
+        parse(stream)
+
+  def test_rotation(self):
+    for angle in [0, 90, 180, 270, 25, 110]:
+      with self.subTest(angle=angle):
+        _, img = make(LPA, box=8, border=12)
+        assert qr.decode(rotate(img, angle)) == LPA
+
+  def test_mirrored(self):
+    _, img = make(LPA)
+    assert qr.decode(img[:, ::-1]) == LPA
+
+  def test_perspective_and_noise(self):
+    _, img = make(LPA, box=10, border=8)
+    h, w = img.shape
+    corners = np.array([(40, 60), (w - 20, 30), (w - 60, h - 40), (30, h - 90)])
+    arr = warp(img, qr._perspective(corners, np.array([(0, 0), (w, 0), (w, h), (0, h)]))).astype(float)
+    rng = np.random.default_rng(1)
+    arr = arr * 0.6 + 60 + rng.normal(0, 12, arr.shape)  # low contrast + noise
+    # uneven lighting
+    arr += np.linspace(-40, 40, w)[None, :]
+    assert qr.decode(np.clip(arr, 0, 255).astype(np.uint8)) == LPA
+
+  def test_no_code(self):
+    rng = np.random.default_rng(2)
+    assert qr.decode(rng.integers(0, 256, size=(240, 320), dtype=np.uint8)) is None
+    assert qr.decode(np.full((240, 320), 200, dtype=np.uint8)) is None
+
+  def test_encoder_roundtrip(self):
+    for version in range(1, 21):
+      with self.subTest(version=version):
+        assert qr.decode_matrix(np.array(qr._Qr(version, b"hello").modules)) == "hello"

openpilot/common/version.py

@@ -16,6 +16,15 @@ MASTER_SP_BRANCHES = ['master']
 RELEASE_BRANCHES = ['release-tizi-staging', 'release-mici-staging', 'release-tizi', 'release-mici', 'nightly']
 TESTED_BRANCHES = RELEASE_BRANCHES + ['devel-staging', 'nightly-dev'] + RELEASE_SP_BRANCHES + TESTED_SP_BRANCHES
 
+CHESTNUT_BRANCHES = {
+  "staging": "staging-chestnut",
+  "dev": "dev-chestnut",
+  "release-mici": "release-chestnut",
+  "release-tizi": "release-chestnut",
+  "release-mici-staging": "release-chestnut-staging",
+  "release-tizi-staging": "release-chestnut-staging",
+}
+
 SP_BRANCH_MIGRATIONS = {
   ("tici", "staging-c3-new"): "staging-tici",
   ("tici", "dev-c3-new"): "staging-tici",

openpilot/selfdrive/assets/icons_mici/chestnut_orange.png

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bf97a6738b294ac0aed9b2d075916cee0b7d3215bcd23381760900ede6a92748
+size 13256

openpilot/selfdrive/assets/icons_mici/egpu_crossed.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8a8c5fece2a1c7587feb41cbe04c6aee08e768ecd9b5d00da6af9832a4ccc842
-size 2034

openpilot/selfdrive/assets/icons_mici/egpu_gray.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7409c53d7c72681c24982fd83b56ce70f80797c9c0f936d9296a5c18557ac472
-size 7279

openpilot/selfdrive/assets/icons_mici/egpu_orange.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:58bd6155433f623b1f75d134bd8ca4745d9aa71f6767eb807cdbcf7deb3089a1
-size 10876

openpilot/selfdrive/assets/icons_mici/settings/software.png

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c4c38772e6080aa4b8bf5212d3619e949775468c64f3edb88a1a426d767c38d2
-size 1579
+oid sha256:190e196eba6feffec125ac66cf7e77620b759e346fa69b80e3a3884a5694cb15
+size 3225

openpilot/selfdrive/assets/icons_mici/usb.png

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07bda2fe5d6be0b2854044053c384fe002e96406da119863a443b9344258b500
+size 1544

openpilot/selfdrive/assets/prep-svg.sh

@@ -23,8 +23,8 @@ done
 
 # sudo apt install inkscape
 
-for svg in $(find $DIR -type f | grep svg$); do
-  bunx svgo $svg --multipass --pretty --indent 2
+for svg in $(find "$DIR" -type f | grep svg$); do
+  bunx svgo "$svg" --multipass --pretty --indent 2
 
   # convert to PNG
   png="${svg%.svg}.png"

openpilot/selfdrive/car/card.py

@@ -186,9 +186,6 @@ class Car:
     # card is driven by can recv, expected at 100Hz
     self.rk = Ratekeeper(100, print_delay_threshold=None)
 
-    # log fingerprint in sentry
-    sunnypilot_interfaces.log_fingerprint(self.CP)
-
   def state_update(self) -> tuple[car.CarState, custom.CarStateSP, structs.RadarDataT | None]:
     """carState update loop, driven by can"""
 

openpilot/selfdrive/controls/lib/longcontrol.py

@@ -44,8 +44,7 @@ class LongControl:
     self.CP = CP
     self.CP_SP = CP_SP
     self.long_control_state = LongCtrlState.off
-    self.pid = PIDController((CP.longitudinalTuning.kpBP, CP.longitudinalTuning.kpV),
-                             (CP.longitudinalTuning.kiBP, CP.longitudinalTuning.kiV),
+    self.pid = PIDController(0.0, (CP.longitudinalTuning.kiBP, CP.longitudinalTuning.kiV),
                              rate=1 / DT_CTRL)
     self.last_output_accel = 0.0
 

openpilot/selfdrive/controls/lib/longitudinal_mpc_lib/SConscript

@@ -35,6 +35,7 @@ build_files = [f'{gen}/acados_solver_long.c'] + casadi_model + casadi_cost_y + c
 
 # extra generated files used to trigger a rebuild
 generated_files = [
+  'acados_ocp_long.json',
   f'{gen}/Makefile',
 
   f'{gen}/main_long.c',

openpilot/selfdrive/controls/lib/longitudinal_planner.py

@@ -49,9 +49,8 @@ def get_cruise_accel(e2e, v_cruise, v_ego, a_cruise_prev, angle_steers, CP, dt,
       max_accel = min(max_accel, coast_limit)
 
   target_accel = np.clip(v_cruise - v_ego, A_CRUISE_MIN, max_accel)
-  if not e2e:
-    j_cruise = np.interp(v_ego, A_CRUISE_MAX_BP, J_CRUISE_VALS)
-    target_accel = float(np.clip(target_accel, a_cruise_prev - j_cruise * dt, a_cruise_prev + j_cruise * dt))
+  j_cruise = np.interp(v_ego, A_CRUISE_MAX_BP, J_CRUISE_VALS)
+  target_accel = float(np.clip(target_accel, a_cruise_prev - j_cruise * dt, a_cruise_prev + j_cruise * dt))
 
   return target_accel
 
@@ -65,10 +64,9 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     self.dt = dt
     self.allow_throttle = True
 
-    self.a_desired = init_a
     self.v_desired_filter = FirstOrderFilter(init_v, 2.0, self.dt)
-    self.a_cruise = 0.0
-    self.output_a_target = 0.0
+    self.a_cruise = init_a
+    self.output_a_target = init_a
     self.output_should_stop = False
 
     self.v_desired_trajectory = np.zeros(CONTROL_N)
@@ -105,7 +103,8 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
 
     if reset_state:
       self.v_desired_filter.x = v_ego
-      self.a_desired = np.clip(sm['carState'].aEgo, ACCEL_MIN, ACCEL_MAX)
+      self.output_a_target = np.clip(sm['carState'].aEgo, ACCEL_MIN, ACCEL_MAX)
+      self.a_cruise = self.output_a_target
 
     # Prevent divergence, smooth in current v_ego
     self.v_desired_filter.x = max(0.0, self.v_desired_filter.update(v_ego))
@@ -113,11 +112,11 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     # No change cost when user is controlling the speed, or when standstill
     prev_accel_constraint = not (reset_state or sm['carState'].standstill)
 
-    # Get new v_cruise and a_desired from Smart Cruise Control and Speed Limit Assist
-    v_cruise, self.a_desired = LongitudinalPlannerSP.update_targets(self, sm, self.v_desired_filter.x, self.a_desired, v_cruise)
+    # Get new v_cruise and a_target from Smart Cruise Control and Speed Limit Assist
+    v_cruise, self.output_a_target = LongitudinalPlannerSP.update_targets(self, sm, self.v_desired_filter.x, self.output_a_target, v_cruise)
 
     self.mpc.set_weights(prev_accel_constraint, personality=sm['selfdriveState'].personality)
-    self.mpc.set_cur_state(self.v_desired_filter.x, self.a_desired)
+    self.mpc.set_cur_state(self.v_desired_filter.x, self.output_a_target)
     self.mpc.update(sm['radarState'], personality=sm['selfdriveState'].personality)
 
     self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
@@ -130,7 +129,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
       cloudlog.info("FCW triggered")
 
     # Save starting point for next iteration
-    a_prev = self.a_desired
+    a_prev = self.output_a_target
 
     action_t =  self.CP.longitudinalActuatorDelay + DT_MDL
     output_a_target_mpc = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
@@ -155,7 +154,6 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     self.output_should_stop = any(should_stop for _, _, should_stop in candidates)
     self.output_a_target = np.clip(output_a_target, ACCEL_MIN, ACCEL_MAX)
 
-    self.a_desired = float(self.output_a_target)
     self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.output_a_target + a_prev) / 2.0
 
   def publish(self, sm, pm):

openpilot/selfdrive/locationd/locationd.py

@@ -278,12 +278,12 @@ def main():
   estimator = LocationEstimator(DEBUG)
 
   filter_initialized = False
-  critcal_services = ["accelerometer", "gyroscope", "cameraOdometry"]
+  critical_services = ["accelerometer", "gyroscope", "cameraOdometry"]
   observation_input_invalid = defaultdict(int)
 
-  input_invalid_limit = {s: round(INPUT_INVALID_LIMIT * (SERVICE_LIST[s].frequency / 20.)) for s in critcal_services}
-  input_invalid_threshold = {s: input_invalid_limit[s] - 0.5 for s in critcal_services}
-  input_invalid_decay = {s: calculate_invalid_input_decay(input_invalid_limit[s], INPUT_INVALID_RECOVERY, SERVICE_LIST[s].frequency) for s in critcal_services}
+  input_invalid_limit = {s: round(INPUT_INVALID_LIMIT * (SERVICE_LIST[s].frequency / 20.)) for s in critical_services}
+  input_invalid_threshold = {s: input_invalid_limit[s] - 0.5 for s in critical_services}
+  input_invalid_decay = {s: calculate_invalid_input_decay(input_invalid_limit[s], INPUT_INVALID_RECOVERY, SERVICE_LIST[s].frequency) for s in critical_services}
 
   initial_pose_data = params.get("LocationFilterInitialState")
   if initial_pose_data is not None:
@@ -313,7 +313,7 @@ def main():
         if valid:
           t = log_mono_time * 1e-9
           res = estimator.handle_log(t, which, msg)
-          if which not in critcal_services:
+          if which not in critical_services:
             continue
 
           if res == HandleLogResult.TIMING_INVALID:
@@ -328,7 +328,7 @@ def main():
       filter_initialized = sm.all_checks() and sensor_all_checks(acc_msgs, gyro_msgs, sensor_valid, sensor_recv_time, sensor_alive, SIMULATION)
 
     if sm.updated["cameraOdometry"]:
-      critical_service_inputs_valid = all(observation_input_invalid[s] < input_invalid_threshold[s] for s in critcal_services)
+      critical_service_inputs_valid = all(observation_input_invalid[s] < input_invalid_threshold[s] for s in critical_services)
       inputs_valid = sm.all_valid() and critical_service_inputs_valid
       sensors_valid = sensor_all_checks(acc_msgs, gyro_msgs, sensor_valid, sensor_recv_time, sensor_alive, SIMULATION)
 

openpilot/selfdrive/modeld/SConscript

@@ -1,92 +1,45 @@
 import glob
-import json
 import os
 import time
 from SCons.Script import Action, Value
-from openpilot.common.file_chunker import chunk_file, get_chunk_targets, get_existing_chunks
 from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
 from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE, DM_INPUT_SIZE
-from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.selfdrive.modeld.helpers import TG_INPUT_DEVICES_PATH, usbgpu_present, modeld_pkl_path
+from openpilot.selfdrive.modeld.helpers import chestnut_present
+from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
 
 
-CAMERA_CONFIGS = [
-  (_ar_ox_fisheye.width, _ar_ox_fisheye.height),  # tici: 1928x1208
-  (_os_fisheye.width, _os_fisheye.height),        # mici: 1344x760
-]
-
 Import('env', 'arch')
-chunker_file = File("#openpilot/common/file_chunker.py")
 lenv = env.Clone()
+lenv.PrependENVPath('PYTHONPATH', Dir('#tinygrad_repo').abspath)
 
 tinygrad_root = env.Dir("#").abspath
 tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=tinygrad_root)
                   if 'pycache' not in x and os.path.isfile(os.path.join(tinygrad_root, x))]
 
-def estimate_pickle_max_size(onnx_size):
-  return 1.2 * onnx_size  + 10 * 1024 * 1024  # 20% + 10MB is plenty
+camera_configs = [(c.width, c.height) for c in (_ar_ox_fisheye, _os_fisheye)]
 
 if arch == 'comma_arm64':
-  tg_backend = 'QCOM'
-  tg_flags = f'DEV={tg_backend} IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1'
+  tg_flags = 'DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1'
 else:
-  tg_backend = 'CPU'
-  tg_flags = f'DEV=CPU' if arch == 'Darwin' else 'DEV=CPU:LLVM'
+  # JIT=2 disables graph batching, which produces incorrect outputs after buffers change.
+  tg_flags = 'DEV=METAL JIT=2' if arch == 'Darwin' else 'DEV=CPU:LLVM'
 
-tg_devices = { # which device to put jit inputs to at runtime
-  'openpilot.selfdrive.modeld.modeld': {
-    'default': {'WARP_DEV': tg_backend, 'QUEUE_DEV': tg_backend},
-    'usbgpu': {'WARP_DEV': tg_backend, 'QUEUE_DEV': 'AMD'}
-  },
-  'openpilot.selfdrive.modeld.dmonitoringmodeld': {
-    'default': {'DEV': tg_backend}
-  },
-}
-
-USBGPU = usbgpu_present()
-if USBGPU:
-  usbgpu_tg_flags = f'DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV={tg_backend} FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2'
+CHESTNUT = chestnut_present()
+if CHESTNUT:
+  chestnut_tg_flags = 'DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32'
   # the USB+AMD GPU takes an exclusive flock; serialize all targets that touch it
-  usbgpu_lock = File("models/.usb_gpu.lock").abspath
-
-def write_tg_devices(target, source, env):
-  with open(str(target[0]), "w") as f:
-    json.dump(tg_devices, f)
-    f.write("\n")
-
-tg_devices_node = lenv.Command(
-  str(TG_INPUT_DEVICES_PATH),
-  [Value(tg_devices)],
-  write_tg_devices,
-)
+  chestnut_lock = File("models/.chestnut.lock").abspath
 
 # tinygrad calls brew which needs a $HOME in the env
 mac_brew_string = f'HOME={os.path.expanduser("~")}' if arch == 'Darwin' else ''
 
-modeld_dir = Dir("#openpilot/selfdrive/modeld").abspath
-compile_modeld_script = [
-  File(f"{modeld_dir}/compile_modeld.py"),
-  File(f"{modeld_dir}/get_model_metadata.py"),
-  File("#openpilot/system/camerad/cameras/nv12_info.py"),
-  File("#openpilot/common/hardware/hw.py"),
-]
-model_w, model_h = MEDMODEL_INPUT_SIZE
-frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
+warp_deps = [File("#openpilot/system/camerad/cameras/nv12_info.py")]
+compiler = Dir('#tinygrad_repo/examples/openpilot').abspath
+# CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
+taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
 
-for usbgpu in [False, True] if USBGPU else [False]:
-  target_pkl_path = File(modeld_pkl_path(usbgpu)).abspath
-  # BIG_INTO_SMALL=1 builds the default target from the big model, e.g. to test it without a USB GPU
-  file_prefix, cmd_flags = ('big_', usbgpu_tg_flags) if usbgpu else ('big_' if os.getenv('BIG_INTO_SMALL') else '', tg_flags)
-  driving_onnx_deps = get_existing_chunks(File(f"models/{file_prefix}driving_supercombo.onnx").abspath)
-  camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in CAMERA_CONFIGS)
-  cmd = (f'{cmd_flags} {mac_brew_string} python3 {modeld_dir}/compile_modeld.py '
-        f'--model-size {model_w}x{model_h} '
-        f'--camera-resolutions {camera_res_args} '
-        f'--onnx {File(f"models/{file_prefix}driving_supercombo.onnx").abspath} '
-        f'--output {target_pkl_path} --frame-skip {frame_skip}')
-  onnx_sizes_sum = sum(os.path.getsize(f) for f in driving_onnx_deps)
-  chunk_targets = get_chunk_targets(target_pkl_path, estimate_pickle_max_size(onnx_sizes_sum))
-  def do_compile(target, source, env, command=cmd, pkl=target_pkl_path, chunks=chunk_targets):
+def chestnut_action(command):
+  def do_compile(target, source, env):
     from openpilot.system.hardware.chestnut.flash import link_up
     # chestnut can enumerate before its PCIe link is up due to varying 12V power behavior across cars
     for _ in range(10):
@@ -94,50 +47,44 @@ for usbgpu in [False, True] if USBGPU else [False]:
         break
       time.sleep(1)
     else:
-      print("Chestnut not ready, skipping big model build")
+      print("Chestnut not ready, skipping warp build")
       return
-    if ret := env.Execute(command):
-      return ret
-    chunk_file(pkl, chunks)
-  def do_chunk(target, source, env, pkl=target_pkl_path, chunks=chunk_targets):
-    chunk_file(pkl, chunks)
-  actions = Action(do_compile, "  [USBGPU] $TARGET") if usbgpu else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
-  node = lenv.Command(
-    chunk_targets,
-    tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
-    actions,
-  )
-  if usbgpu:
-    lenv.SideEffect(usbgpu_lock, node)
+    return env.Execute(command)
+  return Action(do_compile, "  [CHESTNUT] $TARGET")
 
-# get model metadata
-fn = File(f"models/dmonitoring_model").abspath
-script_files = [File(Dir("#openpilot/selfdrive/modeld").File("get_model_metadata.py").abspath)]
-cmd = f'{tg_flags} {mac_brew_string} python3 {Dir("#openpilot/selfdrive/modeld").abspath}/get_model_metadata.py {fn}.onnx'
-lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files + script_files + [tg_devices_node], cmd)
+def compile_model(onnx_path, pkl_path):
+  onnx_path, target_pkl_path = File(onnx_path).abspath, File(pkl_path).abspath
+  cmd = (f'{tg_flags} {mac_brew_string} {taskset}python3 "{compiler}/compile_onnx.py" '
+         f'"{onnx_path}" "{target_pkl_path}" --device-input "*" --out-of-band --benchmark-runs 1')
+  lenv.Command(
+    target_pkl_path,
+    tinygrad_files + [onnx_path, Value(cmd)],
+    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')
+
+model_w, model_h = MEDMODEL_INPUT_SIZE
+for chestnut in [False, True] if CHESTNUT else [False]:
+  file_prefix, cmd_flags = ('big_', chestnut_tg_flags) if chestnut else ('', tg_flags)
+  for cam_w, cam_h in camera_configs:
+    warp_pkl_path = File(f"models/{file_prefix}driving_warp_{cam_w}x{cam_h}_tinygrad.pkl").abspath
+    stride, y_height, uv_height, _ = get_nv12_info(cam_w, cam_h)
+    cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 "{compiler}/compile_warp.py" '
+           f'--frame {cam_w},{cam_h},{stride},{y_height},{uv_height},{stride * (y_height + uv_height)} '
+           f'--warp-to {model_w}x{model_h} --layout yuv420 --frames 2 '
+           f'--output {warp_pkl_path}')
+    action = chestnut_action(cmd) if chestnut else cmd
+    node = lenv.Command(warp_pkl_path, tinygrad_files + warp_deps + [Value(cmd)], action)
+    if chestnut:
+      lenv.SideEffect(chestnut_lock, node)
 
 dm_w, dm_h = DM_INPUT_SIZE
-compile_dm_warp_script = [File(f"{modeld_dir}/compile_dm_warp.py")]
-for cam_w, cam_h in CAMERA_CONFIGS:
+for cam_w, cam_h in camera_configs:
   dm_pkl_path = File(f"models/dm_warp_{cam_w}x{cam_h}_tinygrad.pkl").abspath
-  cmd = (f'{tg_flags} {mac_brew_string} python3 {modeld_dir}/compile_dm_warp.py '
-         f'--camera-resolution {cam_w}x{cam_h} --warp-to {dm_w}x{dm_h} '
-         f'--output {dm_pkl_path}')
-  lenv.Command(dm_pkl_path, tinygrad_files + compile_dm_warp_script + compile_modeld_script + [tg_devices_node], cmd)
-
-def tg_compile(flags, model_name):
-  pythonpath_string = 'PYTHONPATH="${PYTHONPATH}:' + env.Dir("#tinygrad_repo").abspath + '"'
-  fn = File(f"models/{model_name}").abspath
-  pkl = fn + "_tinygrad.pkl"
-  onnx_path = fn + ".onnx"
-  chunk_targets = get_chunk_targets(pkl, estimate_pickle_max_size(os.path.getsize(onnx_path)))
-  def do_chunk(target, source, env):
-    chunk_file(pkl, chunk_targets)
-  return lenv.Command(
-    chunk_targets,
-    [onnx_path] + tinygrad_files + [Value(chunk_targets), chunker_file, tg_devices_node],
-    [f'{pythonpath_string} {flags} python3 {Dir("#tinygrad_repo").abspath}/examples/openpilot/compile3.py {fn}.onnx {pkl}',
-     Action(do_chunk, "  [CHUNK] $TARGET")],
-  )
-
-tg_compile(tg_flags, 'dmonitoring_model')
+  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" '
+         f'--frame {cam_w},{cam_h},{stride},{y_height},{uv_height},{frame_size} --warp-to {dm_w}x{dm_h} '
+         f'--layout luma --border-fill 16 --transform-device NPY --output {dm_pkl_path}')
+  lenv.Command(dm_pkl_path, tinygrad_files + warp_deps + [Value(cmd)], cmd)

openpilot/selfdrive/modeld/compile_dm_warp.py

@@ -1,56 +0,0 @@
-#!/usr/bin/env python3
-import argparse
-import pickle
-import time
-
-from tinygrad.tensor import Tensor
-from tinygrad.device import Device
-from tinygrad.engine.jit import TinyJit
-
-from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
-from openpilot.selfdrive.modeld.compile_modeld import NV12Frame, warp_perspective_tinygrad, _parse_size
-
-
-def make_warp_dm(nv12: NV12Frame, dm_w, dm_h):
-  cam_w, cam_h, stride, _, _, _ = nv12
-  stride_pad = stride - cam_w
-
-  def warp_dm(input_frame, M_inv):
-    M_inv = M_inv.to(Device.DEFAULT).realize()
-    return warp_perspective_tinygrad(input_frame[:cam_h*stride], M_inv,
-                                     (dm_w, dm_h), (cam_h, cam_w), stride_pad, border_fill_val=16).reshape(-1, dm_h * dm_w) # Y
-  return warp_dm
-
-
-def compile_dm_warp(nv12: NV12Frame, dm_w, dm_h, pkl_path):
-  print(f"Compiling DM warp for {nv12.width}x{nv12.height} -> {dm_w}x{dm_h}...")
-
-  warp_dm_jit = TinyJit(make_warp_dm(nv12, dm_w, dm_h), prune=True)
-
-  for i in range(10):
-    frame = Tensor.randint(nv12.size, low=0, high=256, dtype='uint8').realize()
-    M_inv = Tensor(Tensor.randn(3, 3).mul(8).realize().numpy(), device='NPY')
-    Device.default.synchronize()
-    st = time.perf_counter()
-    warp_dm_jit(frame, M_inv).realize()
-    mt = time.perf_counter()
-    Device.default.synchronize()
-    et = time.perf_counter()
-    print(f"  [{i+1}/10] enqueue {(mt-st)*1e3:6.2f} ms -- total {(et-st)*1e3:6.2f} ms")
-
-  with open(pkl_path, "wb") as f:
-    pickle.dump(warp_dm_jit, f)
-  print(f"  Saved to {pkl_path}")
-
-
-if __name__ == "__main__":
-  p = argparse.ArgumentParser()
-  p.add_argument('--camera-resolution', type=_parse_size, required=True, help='camera resolution WxH')
-  p.add_argument('--warp-to', type=_parse_size, required=True, help='DM input WxH')
-  p.add_argument('--output', required=True)
-  args = p.parse_args()
-
-  cam_w, cam_h = args.camera_resolution
-  nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-  dm_w, dm_h = args.warp_to
-  compile_dm_warp(nv12, dm_w, dm_h, args.output)

openpilot/selfdrive/modeld/compile_modeld.py

@@ -1,319 +0,0 @@
-#!/usr/bin/env python3
-import argparse
-import atexit
-import math
-import os
-import tempfile
-import time
-import shutil
-from functools import partial
-from collections import namedtuple
-
-import numpy as np
-
-from openpilot.selfdrive.modeld.helpers import dump_oob, load_oob
-
-def _patch_tinygrad_fetch_fw():
-  import hashlib
-  import pathlib
-  import zstandard
-  from tinygrad import helpers
-  _orig = helpers.fetch_fw
-  def fetch_fw(path, name, sha256):
-    p = pathlib.Path(f"/lib/firmware/{path}/{name}.zst")
-    if p.is_file():
-      blob = zstandard.ZstdDecompressor().stream_reader(p.read_bytes()).read()
-      if hashlib.sha256(blob).hexdigest() == sha256:
-        return blob
-    return _orig(path, name, sha256)
-  helpers.fetch_fw = fetch_fw
-_patch_tinygrad_fetch_fw()
-
-
-from tinygrad.tensor import Tensor
-from tinygrad.helpers import Context
-from tinygrad.device import Device
-from tinygrad.engine.jit import TinyJit
-
-
-NV12Frame = namedtuple("NV12Frame", ['width', 'height', 'stride', 'y_height', 'uv_height', 'size'])
-WARP_INPUTS = ['tfm', 'big_tfm']
-POLICY_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']
-
-UV_SCALE_MATRIX = np.array([[0.5, 0, 0], [0, 0.5, 0], [0, 0, 1]], dtype=np.float32)
-UV_SCALE_MATRIX_INV = np.linalg.inv(UV_SCALE_MATRIX)
-
-WARP_DEV = os.getenv('WARP_DEV')
-
-
-def make_random_images(keys, shape, device=None):
-  return {k: Tensor.randint(shape, low=0, high=256, dtype='uint8', device=device).realize() for k in keys}
-
-
-def warp_perspective_tinygrad(src_flat, M_inv, dst_shape, src_shape, stride_pad, border_fill_val=None):
-  w_dst, h_dst = dst_shape
-  h_src, w_src = src_shape
-
-  x = Tensor.arange(w_dst).reshape(1, w_dst).expand(h_dst, w_dst).reshape(-1)
-  y = Tensor.arange(h_dst).reshape(h_dst, 1).expand(h_dst, w_dst).reshape(-1)
-
-  # inline 3x3 matmul as elementwise to avoid reduce op (enables fusion with gather)
-  src_x = M_inv[0, 0] * x + M_inv[0, 1] * y + M_inv[0, 2]
-  src_y = M_inv[1, 0] * x + M_inv[1, 1] * y + M_inv[1, 2]
-  src_w = M_inv[2, 0] * x + M_inv[2, 1] * y + M_inv[2, 2]
-
-  src_x = src_x / src_w
-  src_y = src_y / src_w
-
-  x_round = Tensor.round(src_x)
-  y_round = Tensor.round(src_y)
-  x_nn_clipped = x_round.clip(0, w_src - 1).cast('int')
-  y_nn_clipped = y_round.clip(0, h_src - 1).cast('int')
-  idx = y_nn_clipped * (w_src + stride_pad) + x_nn_clipped
-  sampled = src_flat[idx]
-
-  if border_fill_val is None:
-    return sampled
-
-  in_bounds = ((x_round >= 0) & (x_round <= w_src - 1) &
-               (y_round >= 0) & (y_round <= h_src - 1)).cast(sampled.dtype)
-  return sampled * in_bounds + Tensor(border_fill_val, dtype=sampled.dtype) * (1 - in_bounds)
-
-
-def frames_to_tensor(frames):
-  H = (frames.shape[0] * 2) // 3
-  W = frames.shape[1]
-  in_img1 = Tensor.cat(frames[0:H:2, 0::2],
-                       frames[1:H:2, 0::2],
-                       frames[0:H:2, 1::2],
-                       frames[1:H:2, 1::2],
-                       frames[H:H+H//4].reshape((H//2, W//2)),
-                       frames[H+H//4:H+H//2].reshape((H//2, W//2)), dim=0).reshape((6, H//2, W//2))
-  return in_img1
-
-
-def make_frame_prepare(nv12: NV12Frame, model_w, model_h):
-  cam_w, cam_h, stride, y_height, uv_height, _ = nv12
-  uv_offset = stride * y_height
-  stride_pad = stride - cam_w
-
-  def frame_prepare_tinygrad(input_frame, M_inv):
-    # UV_SCALE @ M_inv @ UV_SCALE_INV simplifies to elementwise scaling
-    M_inv_uv = M_inv * Tensor([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]], device=WARP_DEV)
-    # deinterleave NV12 UV plane (UVUV... -> separate U, V)
-    uv = input_frame[uv_offset:uv_offset + uv_height * stride].reshape(uv_height, stride)
-    with Context(SPLIT_REDUCEOP=0):
-      y = warp_perspective_tinygrad(input_frame[:cam_h*stride],
-                                    M_inv, (model_w, model_h),
-                                    (cam_h, cam_w), stride_pad).realize()
-      u = warp_perspective_tinygrad(uv[:cam_h//2, :cam_w:2].flatten(),
-                                    M_inv_uv, (model_w//2, model_h//2),
-                                    (cam_h//2, cam_w//2), 0).realize()
-      v = warp_perspective_tinygrad(uv[:cam_h//2, 1:cam_w:2].flatten(),
-                                    M_inv_uv, (model_w//2, model_h//2),
-                                    (cam_h//2, cam_w//2), 0).realize()
-    yuv = y.cat(u).cat(v).reshape((model_h * 3 // 2, model_w))
-    tensor = frames_to_tensor(yuv)
-    return tensor
-  return frame_prepare_tinygrad
-
-
-def make_warp_input_queues(vision_input_shapes, frame_skip, device):
-  img = vision_input_shapes['img']  # (1, 12, 128, 256)
-  n_frames = img[1] // 6
-  img_buf_shape = (frame_skip * (n_frames - 1) + 1, 6, img[2], img[3])
-
-  npy = {
-    'tfm': np.zeros((3, 3), dtype=np.float32),
-    'big_tfm': np.zeros((3, 3), dtype=np.float32),
-  }
-  input_queues = {
-    'img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
-    'big_img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
-    **{k: Tensor(v, device='NPY').realize() for k, v in npy.items()},
-  }
-  return input_queues, npy
-
-
-def get_policy_npy_shapes(input_shapes):
-  dp = input_shapes['desire_pulse']  # (1, 25, 8)
-  tc = input_shapes['traffic_convention']  # (1, 2)
-  at = input_shapes['action_t']  # (1, 2)
-  fb = input_shapes['features_buffer']  # (1, 24, 512)
-  # TODO prev_feat shouldn't exist and be handled inside the JIT, but corrupt on QCOM for now
-  shapes = {'desire': (dp[2],), 'traffic_convention': tuple(tc), 'action_t': tuple(at), 'prev_feat': (fb[0], fb[2])}
-  return shapes, [math.prod(s) for s in shapes.values()]
-
-
-def make_input_queues(input_shapes, frame_skip, device):
-  input_queues, npy = make_warp_input_queues(input_shapes, frame_skip, device)
-
-  fb = input_shapes['features_buffer']  # (1, 24, 512), past features only; the model appends the current frame's feature
-  dp = input_shapes['desire_pulse']  # (1, 25, 8)
-
-  shapes, sizes = get_policy_npy_shapes(input_shapes)
-  packed_npy_inputs = np.zeros(sum(sizes), dtype=np.float32)
-  # views into the packed inputs, to be refilled at runtime
-  npy.update({k: v.reshape(s) for (k, s), v in zip(shapes.items(), np.split(packed_npy_inputs, np.cumsum(sizes[:-1])), strict=True)})
-  input_queues.update({
-    'feat_q': Tensor(np.zeros((frame_skip * fb[1], fb[0], fb[2]), dtype=np.float32), device=device).contiguous().realize(),
-    'desire_q': Tensor(np.zeros((frame_skip * dp[1], dp[0], dp[2]), dtype=np.float32), device=device).contiguous().realize(),
-    'packed_npy_inputs': Tensor(packed_npy_inputs, device='NPY').realize(),
-  })
-  return input_queues, npy
-
-
-def shift_and_sample(buf, new_val, sample_fn):
-  buf.assign(buf[1:].cat(new_val, dim=0).contiguous())
-  return sample_fn(buf)
-
-
-def sample_skip(buf, frame_skip):
-  return buf[::frame_skip].contiguous().flatten(0, 1).unsqueeze(0)
-
-
-def sample_desire(buf, frame_skip):
-  return buf.reshape(-1, frame_skip, *buf.shape[1:]).max(1).flatten(0, 1).unsqueeze(0)
-
-
-def make_warp(nv12, model_w, model_h, frame_skip):
-  frame_prepare = make_frame_prepare(nv12, model_w, model_h)
-
-  def warp(tfm, big_tfm, frame, big_frame):
-    tfm = tfm.to(WARP_DEV)
-    big_tfm = big_tfm.to(WARP_DEV)
-    Tensor.realize(tfm, big_tfm)
-
-    warped_frame = frame_prepare(frame, tfm).unsqueeze(0)
-    warped_big_frame = frame_prepare(big_frame, big_tfm).unsqueeze(0)
-    return Tensor.cat(warped_frame, warped_big_frame)
-
-  return warp
-
-
-def make_run_policy(model_runner, model_metadata, frame_skip):
-  sample_desire_fn = partial(sample_desire, frame_skip=frame_skip)
-  sample_skip_fn = partial(sample_skip, frame_skip=frame_skip)
-  npy_shapes, npy_sizes = get_policy_npy_shapes(model_metadata['input_shapes'])
-
-  def run_policy(warped, img_q, big_img_q, feat_q, desire_q, packed_npy_inputs):
-    packed_npy_inputs = packed_npy_inputs.to(Device.DEFAULT)
-    warped = warped.to(Device.DEFAULT)
-    Tensor.realize(packed_npy_inputs, warped)
-
-    img = shift_and_sample(img_q, warped[0:1], sample_skip_fn)
-    big_img = shift_and_sample(big_img_q, warped[1:2], sample_skip_fn)
-
-    desire, traffic_convention, action_t, prev_feat = (t.reshape(s) for t, s in zip(packed_npy_inputs.split(npy_sizes), npy_shapes.values(), strict=True))
-    desire_buf = shift_and_sample(desire_q, desire.reshape(1, 1, -1), sample_desire_fn)
-    feat_buf = shift_and_sample(feat_q, prev_feat.reshape(1, 1, -1), sample_skip_fn)
-
-    inputs = {
-      'img': img,
-      'big_img': big_img,
-      'features_buffer': feat_buf,
-      'desire_pulse': desire_buf,
-      'traffic_convention': traffic_convention,
-      'action_t': action_t,
-    }
-    out = next(iter(model_runner(inputs).values())).cast('float32')
-    return out,
-  return run_policy
-
-
-def compile_jit(jit, make_random_inputs, input_keys, make_queues):
-  SEED = 42
-  def random_inputs_run(fn, seed, test_val=None, test_buffers=None, expect_match=True):
-    input_queues, npy = make_queues(Device.DEFAULT)
-    rng = np.random.default_rng(seed)
-    Tensor.manual_seed(seed)
-
-    testing = test_val is not None or test_buffers is not None
-    n_runs = 1 if testing else 3
-
-    for i in range(n_runs):
-      for v in npy.values():
-        v[:] = rng.standard_normal(v.shape).astype(v.dtype)
-      Device.default.synchronize()
-      random_inputs = make_random_inputs()
-      st = time.perf_counter()
-      outs = fn(**{k: input_queues[k] for k in input_keys}, **random_inputs)
-      mt = time.perf_counter()
-      Device.default.synchronize()
-      et = time.perf_counter()
-      print(f"  [{i+1}/{n_runs}] enqueue {(mt-st)*1e3:6.2f} ms -- total {(et-st)*1e3:6.2f} ms")
-
-      if i == 0:
-        val = [np.copy(v.numpy()) for v in outs]
-        buffers = [np.copy(v.numpy().copy()) for v in input_queues.values()]
-
-    if test_val is not None:
-      match = all(np.array_equal(a, b) for a, b in zip(val, test_val, strict=True))
-      assert match == expect_match, f"outputs {'differ from' if expect_match else 'match'} baseline (seed={seed})"
-    if test_buffers is not None:
-      match = all(np.array_equal(a, b) for a, b in zip(buffers, test_buffers, strict=True))
-      assert match == expect_match, f"buffers {'differ from' if expect_match else 'match'} baseline (seed={seed})"
-    return val, buffers
-
-  print('capture + replay')
-  test_val, test_buffers = random_inputs_run(jit, SEED)
-  print('pickle round trip')
-  with tempfile.TemporaryFile(dir=".") as f:
-    dump_oob(jit, f)
-    f.seek(0)
-    jit = load_oob(f)
-  random_inputs_run(jit, SEED, test_val, test_buffers, expect_match=True)
-  random_inputs_run(jit, SEED+1, test_val, test_buffers, expect_match=False)
-  return jit
-
-
-def _parse_size(s):
-  w, h = s.lower().split('x')
-  return int(w), int(h)
-
-
-def read_file_chunked_to_disk(path):
-  from openpilot.common.file_chunker import open_file_chunked
-  tmp_path = f'{path}.unchunked'
-  with open(tmp_path, 'wb') as f, open_file_chunked(path) as src:
-    shutil.copyfileobj(src, f)
-  atexit.register(lambda: os.path.exists(tmp_path) and os.remove(tmp_path))
-  return tmp_path
-
-
-if __name__ == "__main__":
-  from tinygrad.nn.onnx import OnnxRunner
-  from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
-  from openpilot.selfdrive.modeld.get_model_metadata import make_metadata_dict
-  p = argparse.ArgumentParser()
-  p.add_argument('--model-size', type=_parse_size, required=True, help='model input WxH')
-  p.add_argument('--camera-resolutions', type=_parse_size, nargs='+', required=True,
-                 help='camera resolutions WxH (one or more)')
-  p.add_argument('--onnx', required=True)
-  p.add_argument('--output', required=True)
-  p.add_argument('--frame-skip', type=int, required=True)
-  args = p.parse_args()
-
-  model_path = read_file_chunked_to_disk(args.onnx)
-  model_w, model_h = args.model_size
-
-  model_runner = OnnxRunner(model_path)
-  out = {'metadata': make_metadata_dict(model_path)}
-
-  run_policy_jit = TinyJit(make_run_policy(model_runner, out['metadata'], args.frame_skip), prune=True)
-
-  make_policy_queues = partial(make_input_queues, out['metadata']['input_shapes'], args.frame_skip)
-  make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, *out['metadata']['input_shapes']['img'][2:]), device=WARP_DEV)
-  out['run_policy'] = compile_jit(run_policy_jit, make_random_model_inputs, POLICY_INPUTS,
-                                  make_policy_queues)
-
-  for cam_w, cam_h in args.camera_resolutions:
-    nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-    make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=nv12.size, device=WARP_DEV)
-    warp = TinyJit(make_warp(nv12, model_w, model_h, args.frame_skip), prune=True)
-    make_warp_queues = partial(make_warp_input_queues, out['metadata']['input_shapes'], args.frame_skip)
-    out[(cam_w,cam_h)] = compile_jit(warp, make_random_warp_inputs, WARP_INPUTS, make_warp_queues)
-
-  with open(args.output, "wb") as f:
-    dump_oob(out, f)
-  print(f"Saved JITs to {args.output} ({os.path.getsize(args.output) / 1e6:.2f} MB)")

openpilot/selfdrive/modeld/dmonitoringmodeld.py

@@ -1,6 +1,7 @@
 #!/usr/bin/env python3
 import os
-from openpilot.selfdrive.modeld.helpers import MODELS_DIR, get_tg_input_devices
+import base64
+from openpilot.selfdrive.modeld.helpers import MODELS_DIR, load_oob
 from tinygrad.tensor import Tensor
 import time
 import pickle
@@ -18,10 +19,8 @@ from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
 from openpilot.common.file_chunker import open_file_chunked
 from openpilot.selfdrive.modeld.parse_model_outputs import sigmoid, safe_exp
 
-PROCESS_NAME = "openpilot.selfdrive.modeld.dmonitoringmodeld"
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
 MODEL_PKL_PATH = MODELS_DIR / 'dmonitoring_model_tinygrad.pkl'
-METADATA_PATH = MODELS_DIR / 'dmonitoring_model_metadata.pkl'
 
 
 class ModelState:
@@ -29,11 +28,10 @@ class ModelState:
   output: np.ndarray
 
   def __init__(self, cam_w: int, cam_h: int):
-    self.DEV = get_tg_input_devices(PROCESS_NAME, usbgpu=False)['DEV']
-    with open(METADATA_PATH, 'rb') as f:
-      model_metadata = pickle.load(f)
-      self.input_shapes = model_metadata['input_shapes']
-      self.output_slices = model_metadata['output_slices']
+    jits = load_oob(open_file_chunked(MODEL_PKL_PATH))
+    self.DEV = jits['input_specs']['input_img'][2]
+    self.input_shapes = jits['metadata']['input_shapes']
+    self.output_slices = pickle.loads(base64.b64decode(jits['metadata']['metadata']['output_slices']))
 
     self.numpy_inputs = {
       'calib': np.zeros(self.input_shapes['calib'], dtype=np.float32),
@@ -42,16 +40,19 @@ class ModelState:
     self.warp_inputs_np = {'transform': np.zeros((3,3), dtype=np.float32)}
     self.warp_inputs = {k: Tensor(v, device='NPY') for k,v in self.warp_inputs_np.items()}
     self.frame_buf_params = get_nv12_info(cam_w, cam_h)
-    self.tensor_inputs = {k: Tensor(v, device='NPY').realize() for k,v in self.numpy_inputs.items()}
+    self.tensor_inputs = {k: Tensor(v, device=self.DEV).realize() for k,v in self.numpy_inputs.items()}
+    self.calib_host = Tensor(self.numpy_inputs['calib'], device='NPY')._buffer()
     self._blob_cache : dict[int, Tensor] = {}
-    self.model_run = pickle.load(open_file_chunked(str(MODEL_PKL_PATH)))
+    self.model_run = jits['run']
+    self.outputs = {name: Tensor(np.zeros(shape, dtype=dtype), device=device).realize() for name, (shape, dtype, device) in jits['output_specs'].items()}
     with open(MODELS_DIR / f'dm_warp_{cam_w}x{cam_h}_tinygrad.pkl', "rb") as f:
-      self.image_warp = pickle.load(f)
+      self.image_warp = pickle.load(f)['run']
 
   def run(self, buf: VisionBuf, calib: np.ndarray, transform: np.ndarray) -> tuple[np.ndarray, float]:
     self.numpy_inputs['calib'][0,:] = calib
 
     t1 = time.perf_counter()
+    self.tensor_inputs['calib']._buffer().copy_from(self.calib_host)
 
     ptr = np.frombuffer(buf.data, dtype=np.uint8).ctypes.data
     # There is a ringbuffer of imgs, just cache tensors pointing to all of them
@@ -59,9 +60,10 @@ class ModelState:
       self._blob_cache[ptr] = Tensor.from_blob(ptr, (self.frame_buf_params[3],), dtype='uint8', device=self.DEV)
 
     self.warp_inputs_np['transform'][:] = transform[:]
-    self.tensor_inputs['input_img'] = self.image_warp(self._blob_cache[ptr], self.warp_inputs['transform'])
+    self.tensor_inputs['input_img'] = self.image_warp(input_frame=self._blob_cache[ptr], M_inv=self.warp_inputs['transform'])
 
-    output = self.model_run(**self.tensor_inputs).numpy().flatten()
+    self.model_run(output_buffers=self.outputs, **self.tensor_inputs)
+    output = self.outputs['outputs'].numpy().astype(np.float32).reshape(-1)
 
     t2 = time.perf_counter()
     return output, t2 - t1

openpilot/selfdrive/modeld/fill_model_msg.py

@@ -64,6 +64,7 @@ def fill_driving_model_data(msg: capnp._DynamicStructBuilder, modelv2_send: capn
   driving_model_data.frameIdExtra = modelV2.frameIdExtra
   driving_model_data.frameDropPerc = modelV2.frameDropPerc
   driving_model_data.modelExecutionTime = modelV2.modelExecutionTime
+  driving_model_data.big = modelV2.big
   driving_model_data.action = modelV2.action
   driving_model_data.meta.laneChangeState = modelV2.meta.laneChangeState
   driving_model_data.meta.laneChangeDirection = modelV2.meta.laneChangeDirection

openpilot/selfdrive/modeld/get_model_metadata.py

@@ -1,55 +0,0 @@
-#!/usr/bin/env python3
-import sys
-import pathlib
-import codecs
-import pickle
-from typing import Any
-
-from tinygrad.nn.onnx import OnnxPBParser
-
-
-class MetadataOnnxPBParser(OnnxPBParser):
-  def _parse_ModelProto(self) -> dict:
-    obj: dict[str, Any] = {"graph": {"input": [], "output": []}, "metadata_props": []}
-    for fid, wire_type in self._parse_message(self.reader.len):
-      match fid:
-        case 7:
-          obj["graph"] = self._parse_GraphProto()
-        case 14:
-          obj["metadata_props"].append(self._parse_StringStringEntryProto())
-        case _:
-          self.reader.skip_field(wire_type)
-    return obj
-
-
-def get_name_and_shape(value_info: dict[str, Any]) -> tuple[str, tuple[int, ...]]:
-  shape = tuple(int(dim) if isinstance(dim, int) else 0 for dim in value_info["parsed_type"].shape)
-  name = value_info["name"]
-  return name, shape
-
-
-def get_metadata_value_by_name(model: dict[str, Any], name: str) -> str | Any:
-  for prop in model["metadata_props"]:
-    if prop["key"] == name:
-      return prop["value"]
-  return None
-
-
-def make_metadata_dict(model_path):
-  model = MetadataOnnxPBParser(model_path).parse()
-  output_slices = get_metadata_value_by_name(model, 'output_slices')
-  assert output_slices is not None, 'output_slices not found in metadata'
-  return {
-    'model_checkpoint': get_metadata_value_by_name(model, 'model_checkpoint'),
-    'output_slices': pickle.loads(codecs.decode(output_slices.encode(), "base64")),
-    'input_shapes': dict(get_name_and_shape(x) for x in model["graph"]["input"]),
-    'output_shapes': dict(get_name_and_shape(x) for x in model["graph"]["output"]),
-  }
-
-
-if __name__ == "__main__":
-  model_path = pathlib.Path(sys.argv[1])
-  metadata_path = model_path.parent / (model_path.stem + '_metadata.pkl')
-  with open(metadata_path, 'wb') as f:
-    pickle.dump(make_metadata_dict(model_path), f)
-  print(f'saved metadata to {metadata_path}')

openpilot/selfdrive/modeld/helpers.py

@@ -1,60 +1,40 @@
 import io
-import json
 import pickle
-import shutil
 import struct
-import tempfile
 from pathlib import Path
 
 from openpilot.common.file_chunker import get_manifest_path
-from openpilot.common.hardware.usb import CHESTNUT_FW_VERSION, CHESTNUT_USB_IDS, USB_DEVICES_PATH
+from openpilot.common.hardware.usb import CHESTNUT_USB_PRODUCT, USB_DEVICES_PATH, is_chestnut_usb_id
 
 MODELS_DIR = Path(__file__).resolve().parent / 'models'
-TG_INPUT_DEVICES_PATH = MODELS_DIR / 'tg_input_devices.json'
 
 
-def get_tg_input_devices(process_name: str, usbgpu: bool):
-  with open(TG_INPUT_DEVICES_PATH) as f:
-    return json.load(f)[process_name]['default' if not usbgpu else 'usbgpu']
-
-def modeld_pkl_path(usbgpu: bool):
-  prefix = 'big_' if usbgpu else ''
+def modeld_pkl_path(chestnut: bool):
+  prefix = 'big_' if chestnut else ''
   return MODELS_DIR / f'{prefix}driving_tinygrad.pkl'
 
-def dump_oob(obj, f):
-  with tempfile.TemporaryFile(dir=".") as tmp:
-    def buffer_callback(pb: pickle.PickleBuffer):
-      m = pb.raw()
-      tmp.write(struct.pack('<q', m.nbytes))
-      tmp.write(m)
-      pb.release() # keep peak ram at ~1 buffer
-    stream = io.BytesIO()
-    pickle.Pickler(stream, protocol=5, buffer_callback=buffer_callback).dump(obj)
-    opcodes = stream.getvalue()
-    f.write(struct.pack('<q', len(opcodes)))
-    f.write(opcodes)
-    tmp.seek(0)
-    shutil.copyfileobj(tmp, f)
-
 def load_oob(f):
   opcodes = f.read(struct.unpack('<q', f.read(8))[0])
   def buffers():
     while (h := f.read(8)):
       pb = pickle.PickleBuffer(bytearray(struct.unpack('<q', h)[0]))
-      f.readinto(pb)
+      if f.readinto(pb) != pb.raw().nbytes:
+        raise EOFError("incomplete model buffer")
       yield pb
   return pickle.load(io.BytesIO(opcodes), buffers=buffers())
 
-def usbgpu_present() -> bool:
+def chestnut_present() -> bool:
   for d in USB_DEVICES_PATH.glob("*"):
     try:
       usb_id = (int((d / "idVendor").read_text(), 16), int((d / "idProduct").read_text(), 16))
       product = (d / "product").read_text().strip()
-      if usb_id in CHESTNUT_USB_IDS and product == f"custom {CHESTNUT_FW_VERSION}-CLEAN":
+      if is_chestnut_usb_id(*usb_id) and product == CHESTNUT_USB_PRODUCT:
         return True
     except Exception:
       pass
   return False
 
-def usbgpu_compiled() -> bool:
-  return Path(get_manifest_path(modeld_pkl_path(usbgpu=True))).is_file()
+def chestnut_compiled() -> bool:
+  path = modeld_pkl_path(chestnut=True)
+  return (path.is_file() or Path(get_manifest_path(path)).is_file()) and all(
+    (MODELS_DIR / f'big_driving_warp_{size}_tinygrad.pkl').is_file() for size in ('1344x760', '1928x1208'))

openpilot/selfdrive/modeld/modeld.py

@@ -1,10 +1,17 @@
 #!/usr/bin/env python3
+from collections.abc import Callable
+import base64
+import ctypes
 from functools import cached_property
 import os
-os.environ['GMMU'] = '0' # for usbgpu fast loading, noop for qcom
+os.environ['GMMU'] = '0' # for chestnut fast loading, noop for qcom
+from tinygrad.device import Buffer, Device
+from tinygrad.dtype import DType, dtypes
 from tinygrad.tensor import Tensor
-from tinygrad.device import Device
-import struct
+from tinygrad.helpers import round_up
+from tinygrad.uop.ops import UOp
+import math
+import pickle
 import threading
 import time
 import numpy as np
@@ -26,17 +33,11 @@ from openpilot.common.transformations.model import get_warp_matrix
 from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
 from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan, should_stop, smooth_value, get_curvature_from_plan
 from openpilot.selfdrive.modeld.parse_model_outputs import Parser
-from openpilot.selfdrive.modeld.compile_modeld import make_input_queues, WARP_INPUTS, POLICY_INPUTS
 from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_driving_model_data, fill_pose_msg, PublishState
 from openpilot.common.file_chunker import open_file_chunked
 from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
-from openpilot.selfdrive.modeld.helpers import usbgpu_present, usbgpu_compiled, modeld_pkl_path, get_tg_input_devices, load_oob
+from openpilot.selfdrive.modeld.helpers import MODELS_DIR, chestnut_present, chestnut_compiled, modeld_pkl_path, load_oob
 
-from openpilot.sunnypilot.livedelay.helpers import get_lat_delay
-from openpilot.sunnypilot.modeld_v2.modeld_base import ModelStateBase
-from openpilot.sunnypilot.selfdrive.controls.lib.relc import RoadEdgeLaneChangeController
-
-PROCESS_NAME = "openpilot.selfdrive.modeld.modeld"
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
 
 LAT_SMOOTH_SECONDS = 0.0
@@ -73,8 +74,8 @@ def get_action_from_model(model_output: dict[str, np.ndarray], prev_action: log.
                                 shouldStop=bool(stop))
 
 
-class ChestnutState:
-  # only modeld can access chestnut
+class ChestnutGpuState:
+  # GPU metrics require modeld's GPU context
   def __init__(self, pm: PubMaster, big: bool):
     self.pm = pm
     self.big = big
@@ -88,14 +89,16 @@ class ChestnutState:
     return smu._send_msg(smu.smu_mod.PPSMC_MSG_GetPptLimit, 0, read_back_arg=True, timeout=100)
 
   def send(self) -> None:
-    msg = messaging.new_message('chestnutState')
-    state = msg.chestnutState
+    msg = messaging.new_message('chestnutGpuState')
+    state = msg.chestnutGpuState
     self.sends += 1
     if self.big and "AMD" in Device._opened_devices and self.sends % 100 == 1:
       try:
         smu = Device["AMD"].iface.dev_impl.smu
+        metrics_t = smu.smu_mod.SmuMetricsExternal_t
         smu._send_msg(smu.smu_mod.PPSMC_MSG_TransferTableSmu2Dram, smu.smu_mod.TABLE_SMU_METRICS, timeout=100)
-        metrics = smu.read_table(smu.smu_mod.SmuMetricsExternal_t, smu.smu_mod.TABLE_SMU_METRICS).SmuMetrics
+        metrics_buf = bytearray(smu.adev.vram.view(smu.driver_table_paddr, ctypes.sizeof(metrics_t))[:])
+        metrics = metrics_t.from_buffer(metrics_buf).SmuMetrics
         self.metrics = {'tempC': metrics.AvgTemperature[smu.smu_mod.TEMP_HOTSPOT],
                         'memoryTempC': metrics.AvgTemperature[smu.smu_mod.TEMP_MEM],
                         'powerDrawW': metrics.AverageSocketPower,
@@ -113,19 +116,8 @@ class ChestnutState:
       for k, v in self.metrics.items():
         setattr(state, k, v)
 
-    asm_valid = False
-    if "AMD" in Device._opened_devices:
-      try:
-        # ASM runs on USB-C power, these still read without a gpu
-        asm = Device["AMD"].iface.pci_dev.usb
-        state.pcieLtssm = asm.read(0xB450, 1)[0]
-        state.supplyVoltage, state.supplyCurrent = struct.unpack('<Hh', bytes(asm.usb.control_read(0xC0, 5))[:4])
-        asm_valid = True
-      except Exception:
-        pass
-
-    msg.valid = asm_valid and (not self.big or self.valid)
-    self.pm.send('chestnutState', msg)
+    msg.valid = not self.big or (self.valid and bool(self.metrics))
+    self.pm.send('chestnutGpuState', msg)
 
 
 class FrameMeta:
@@ -138,45 +130,64 @@ class FrameMeta:
       self.frame_id, self.timestamp_sof, self.timestamp_eof = vipc.frame_id, vipc.timestamp_sof, vipc.timestamp_eof
 
 
-class ModelState(ModelStateBase):
+def input_view(buffer: Buffer, shape: tuple[int, ...], dtype: DType, offset: int) -> Tensor:
+  view = buffer.view(math.prod(shape), dtype, offset).ensure_allocated()
+  return Tensor(UOp.from_buffer(view)).reshape(shape)
+
+
+class ModelState:
   prev_desire: np.ndarray  # for tracking the rising edge of the pulse
 
-  def __init__(self, cam_w: int, cam_h: int, usbgpu: bool):
-    ModelStateBase.__init__(self)
-    input_devices = get_tg_input_devices(PROCESS_NAME, usbgpu)
-    self.WARP_DEV, self.QUEUE_DEV = input_devices['WARP_DEV'], input_devices['QUEUE_DEV']
-    jits = load_oob(open_file_chunked(modeld_pkl_path(usbgpu)))
-    metadata = jits['metadata']
-    self.input_shapes = metadata['input_shapes']
-    self.vision_input_names = [k for k in self.input_shapes if 'img' in k]
-    self.output_slices = metadata['output_slices']
+  def __init__(self, cam_w: int, cam_h: int, chestnut: bool):
+    jits = load_oob(open_file_chunked(modeld_pkl_path(chestnut)))
+    self.model_device = jits['input_specs']['new_img'][2]
+    self.input_shapes = {name: (shape, np.dtype(dtype)) for name, (shape, dtype, _) in jits['input_specs'].items()}
+    self.state_pairs = {name: f'next_{name}' for name in self.input_shapes if f'next_{name}' in jits['metadata']['output_shapes']}
+    self.vision_input_names = ('img', 'big_img')
+    self.output_slices = pickle.loads(base64.b64decode(jits['metadata']['metadata']['output_slices']))
 
     self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32)
-    self.usbgpu = usbgpu
+    self.chestnut = chestnut
 
-    self.frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
-    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
-    self.full_frames: dict[str, Tensor] = {}
-    self._blob_cache: dict[tuple[str, int], Tensor] = {}
+    stride, y_height, uv_height, _ = get_nv12_info(cam_w, cam_h)
+    self.frame_copy_size = stride * (y_height + uv_height)
+    self.pack_inputs()
+    with open(MODELS_DIR / f'{"big_" if chestnut else ""}driving_warp_{cam_w}x{cam_h}_tinygrad.pkl', 'rb') as f:
+      self.run_warp = pickle.load(f)['run']
+    self.run_model = jits['run']
+    self.outputs = {name: Tensor(np.zeros(shape, dtype=dtype), device=device).realize() for name, (shape, dtype, device) in jits['output_specs'].items()}
+    for name, next_name in self.state_pairs.items():
+      state = self.input_queues[name]
+      self.outputs[next_name] = input_view(state._buffer(), state.shape, state.dtype, 0)
     self.parser = Parser()
-    self.frame_buf_params = {k: get_nv12_info(cam_w, cam_h) for k in ('img', 'big_img')}
-    self.run_policy = jits['run_policy']
-    self.warp = jits[(cam_w,cam_h)]
+
+  def pack_inputs(self) -> None:
+    # Pack host inputs into one upload to reduce USB transfer overhead for the eGPU.
+    self.input_queues = {name: Tensor(np.zeros(shape, dtype=dtype), device=self.model_device).realize()
+                         for name, (shape, dtype) in self.input_shapes.items() if name in self.state_pairs}
+    shapes = {'tfm': (2, 3, 3)} | {name: shape for name, (shape, _) in self.input_shapes.items()
+                                   if name not in self.state_pairs and name != 'new_img'}
+    npy_size = sum(round_up(math.prod(shape) * 4, 128) for shape in shapes.values())
+    self.packed_input = np.zeros(npy_size + 2 * self.frame_copy_size, dtype=np.uint8)
+    self.input_host = Tensor(self.packed_input, device='NPY')._buffer()
+    self.input_device = Tensor(self.packed_input, device=self.model_device)._buffer()
+    self.npy = {}
+    offset = 0
+    for name, shape in shapes.items():
+      self.npy[name] = np.ndarray(shape, dtype=np.float32, buffer=self.packed_input, offset=offset)
+      self.input_queues[name] = input_view(self.input_device, shape, dtypes.float32, offset)
+      offset += round_up(self.npy[name].nbytes, 128)
+    self.frames = self.packed_input[npy_size:].reshape(2, self.frame_copy_size)
+    self.warp_inputs = {'input_frame': input_view(self.input_device, self.frames.shape, dtypes.uint8, npy_size), 'M_inv': self.input_queues.pop('tfm')}
 
   def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]:
-    parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in output_slices.items()}
-    return parsed_model_outputs
+    return {k: model_outputs[np.newaxis, v] for k,v in output_slices.items()}
 
   def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray],
-          inputs: dict[str, np.ndarray]) -> dict[str, np.ndarray] | None:
-    for key in bufs.keys():
-      ptr = np.frombuffer(bufs[key].data, dtype=np.uint8).ctypes.data
-      yuv_size = self.frame_buf_params[key][3]
-      # There is a ringbuffer of imgs, just cache tensors pointing to all of them
-      cache_key = (key, ptr)
-      if cache_key not in self._blob_cache:
-        self._blob_cache[cache_key] = Tensor.from_blob(ptr, (yuv_size,), dtype='uint8', device=self.WARP_DEV)
-      self.full_frames[key] = self._blob_cache[cache_key]
+          inputs: dict[str, np.ndarray], after_enqueue: Callable[[], None] | None = None) -> dict[str, np.ndarray]:
+    for i, key in enumerate(self.vision_input_names):
+      np.copyto(self.frames[i], np.frombuffer(bufs[key].data, dtype=np.uint8, count=self.frame_copy_size))
+      self.npy['tfm'][i] = transforms[key]
 
     # Model decides when action is completed, so desire input is just a pulse triggered on rising edge
     inputs['desire_pulse'][0] = 0
@@ -184,46 +195,41 @@ class ModelState(ModelStateBase):
     self.prev_desire[:] = inputs['desire_pulse']
     self.npy['traffic_convention'][:] = inputs['traffic_convention']
     self.npy['action_t'][:] = inputs['action_t']
-    self.npy['tfm'][:,:] = transforms['img'][:,:]
-    self.npy['big_tfm'][:,:] = transforms['big_img'][:,:]
 
-    warped = self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames['img'], big_frame=self.full_frames['big_img'])
-
-    outs, = self.run_policy(
-      **{k: self.input_queues[k] for k in POLICY_INPUTS if k in self.input_queues}, warped=warped
-    )
-    model_output = outs.numpy()[0]
-    if self.usbgpu and not np.all(np.isfinite(model_output)):
-      # TODO remove with prev_feat
-      cloudlog.error("model output not finite, dropping frame")
-      return None
+    self.input_device.copy_from(self.input_host)
+    self.input_queues['new_img'] = self.run_warp(**self.warp_inputs)
+    self.run_model(output_buffers=self.outputs, **self.input_queues)
+    if after_enqueue is not None:
+      after_enqueue()
+    model_output = self.outputs['outputs'].numpy()[0]
+    if self.chestnut and not np.all(np.isfinite(model_output)):
+      raise RuntimeError("model output not finite")
     outputs_dict = self.parser.parse_outputs(self.slice_outputs(model_output, self.output_slices))
-    self.npy['prev_feat'][:] = model_output[self.output_slices['hidden_state']]
 
     if SEND_RAW_PRED:
       outputs_dict['raw_pred'] = model_output.copy()
     return outputs_dict
 
   def warmup(self) -> None:
-    dummy_frames = {k: np.zeros(self.frame_buf_params[k][3], dtype=np.uint8) for k in self.vision_input_names}
+    dummy_frames = {k: np.zeros(self.frame_copy_size, dtype=np.uint8) for k in self.vision_input_names}
     eye = np.eye(3, dtype=np.float32)
     dims = {'desire_pulse': ModelConstants.DESIRE_LEN, 'traffic_convention': 2, 'action_t': 2}
     self.run(dummy_frames, dict.fromkeys(self.vision_input_names, eye), {k: np.zeros(v, dtype=np.float32) for k, v in dims.items()})
-    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
+    self.packed_input[:] = 0
+    for key in self.state_pairs:
+      self.input_queues[key].assign(0).realize()
     self.prev_desire[:] = 0
-    self.full_frames.clear()
-    self._blob_cache.clear()
 
 
 def main(demo=False):
   cloudlog.warning("modeld init")
 
-  USBGPU = usbgpu_present() and usbgpu_compiled()
-  if USBGPU:
+  CHESTNUT = chestnut_present() and chestnut_compiled()
+  if CHESTNUT:
     os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
   params = Params()
-  params.put_bool("UsbGpuLoading", USBGPU)
-  params.remove("UsbGpuActive")
+  params.put_bool("ChestnutLoading", CHESTNUT)
+  params.remove("ChestnutActive")
 
   config_realtime_process(7, 54)
 
@@ -253,7 +259,7 @@ def main(demo=False):
   st = time.monotonic()
   cloudlog.warning("loading model")
   model = None
-  if USBGPU:
+  if CHESTNUT:
     big_model = None
     def load_big():
       nonlocal big_model
@@ -267,23 +273,22 @@ def main(demo=False):
     loader.start()
     loader.join(BIG_MODEL_TIMEOUT)
     model = big_model
-    params.put_bool("UsbGpuActive", model is not None)
+    params.put_bool("ChestnutActive", model is not None)
 
-  small_model = ModelState(vipc_client_main.width, vipc_client_main.height, False) if model is None or USBGPU else None
+  small_model = ModelState(vipc_client_main.width, vipc_client_main.height, False) if model is None or CHESTNUT else None
   if model is None:
     model = small_model
-  params.put_bool("UsbGpuLoading", False)
-  assert model is not None
+  params.put_bool("ChestnutLoading", False)
   cloudlog.warning(f"models loaded in {time.monotonic() - st:.1f}s, modeld starting")
 
   # messaging
-  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if USBGPU else [])
+  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry"] + (["chestnutGpuState"] if CHESTNUT else [])
   pm = PubMaster(pub_socks)
   sm = SubMaster(["deviceState", "carState", "narrowRoadCameraState", "extrinsicsCalibration", "driverMonitoringState", "carControl", "lateralDelay"])
 
   publish_state = PublishState()
   params = Params()
-  chestnut_state = ChestnutState(pm, model.usbgpu) if USBGPU else None
+  chestnut_state = ChestnutGpuState(pm, model.chestnut) if CHESTNUT else None
 
   # setup filter to track dropped frames
   frame_dropped_filter = FirstOrderFilter(0., 10., 1. / ModelConstants.MODEL_RUN_FREQ)
@@ -310,7 +315,6 @@ def main(demo=False):
   prev_action = log.ModelDataV2.Action()
 
   DH = DesireHelper()
-  RELC = RoadEdgeLaneChangeController()
 
   while True:
     # Keep receiving frames until we are at least 1 frame ahead of previous extra frame
@@ -350,7 +354,6 @@ def main(demo=False):
     is_rhd = sm["driverMonitoringState"].isRHD
     frame_id = sm["narrowRoadCameraState"].frameId
     v_ego = max(sm["carState"].vEgo, 0.)
-    model.lat_delay = get_lat_delay(params, sm["lateralDelay"].lateralDelay)
     lat_delay = sm["lateralDelay"].lateralDelay + 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)
@@ -393,14 +396,15 @@ def main(demo=False):
 
     mt1 = time.perf_counter()
     try:
-      model_output = model.run(bufs, transforms, inputs)
+      send_chestnut = (chestnut_state is not None and
+                       run_count % round(ModelConstants.MODEL_RUN_FREQ / SERVICE_LIST['chestnutGpuState'].frequency) == 0)
+      model_output = model.run(bufs, transforms, inputs, chestnut_state.send if send_chestnut else None)
     except Exception:
-      if not params.get_bool("UsbGpuActive"):
+      if not params.get_bool("ChestnutActive"):
         raise
       # fallback to small model
       cloudlog.exception("big model failed, fall back to small")
-      params.put_bool("UsbGpuActive", False)
-      assert small_model is not None
+      params.put_bool("ChestnutActive", False)
       model = small_model
       if chestnut_state is not None:
         chestnut_state.big = False
@@ -419,7 +423,7 @@ def main(demo=False):
       fill_model_msg(modelv2_send, model_output, action,
                      publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
                      frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, extrinsics_calibration_seen)
-      modelv2_send.modelV2.big = model.usbgpu
+      modelv2_send.modelV2.big = model.chestnut
 
       desire_state = modelv2_send.modelV2.meta.desireState
       l_lane_change_prob = desire_state[log.Desire.laneChangeLeft]
@@ -429,22 +433,13 @@ def main(demo=False):
       modelv2_send.modelV2.meta.laneChangeState = DH.lane_change_state
       modelv2_send.modelV2.meta.laneChangeDirection = DH.lane_change_direction
 
-      mdv2sp_send = messaging.new_message('modelDataV2SP')
-      left_edge, right_edge = RELC.update_and_fill(modelv2_send.modelV2, mdv2sp_send.modelDataV2SP, v_ego)
-      mdv2sp_send.modelDataV2SP.laneTurnDirection = DH.lane_turn_direction
-
       fill_driving_model_data(drivingdata_send, modelv2_send)
       fill_pose_msg(posenet_send, model_output, meta_main.frame_id, vipc_dropped_frames, meta_main.timestamp_eof, extrinsics_calibration_seen)
       pm.send('modelV2', modelv2_send)
       pm.send('drivingModelData', drivingdata_send)
       pm.send('cameraOdometry', posenet_send)
-      pm.send('modelDataV2SP', mdv2sp_send)
     last_vipc_frame_id = meta_main.frame_id
 
-    if chestnut_state is not None and run_count % round(ModelConstants.MODEL_RUN_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0:
-      chestnut_state.send()
-
-
 if __name__ == "__main__":
   try:
     import argparse

openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:10926f2c0911821ca0e72439c1c3bf3ec11f0a08789aa14b7ee8f25379b2afa4
-size 1753235978

openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:76cc0a9bc3af7a318889483dcbe126337f8d338f5abcbe664a8988c9b18b6639
+size 776634338

openpilot/selfdrive/modeld/models/driving_supercombo.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:659727c4d4839adc4992a254409a54259a8756a743f2d567bf5fdc6579f8009b
-size 60881999
+oid sha256:65a08adc31d5c456219687d99b7bf5e44d61dae2d49ea67850e76105c7248cce
+size 60918562

openpilot/selfdrive/pandad/__init__.py

@@ -1,3 +1 @@
-from openpilot.selfdrive.pandad.pandad_api_impl import can_list_to_can_capnp, can_capnp_to_list
-assert can_list_to_can_capnp
-assert can_capnp_to_list
+from openpilot.selfdrive.pandad.pandad_api_impl import can_list_to_can_capnp as can_list_to_can_capnp, can_capnp_to_list as can_capnp_to_list

openpilot/selfdrive/pandad/pandad.cc

@@ -123,22 +123,22 @@ void fill_panda_state(cereal::PandaState::Builder &ps, cereal::PandaState::Panda
   ps.setUptime(health.uptime_pkt);
   ps.setSafetyTxBlocked(health.safety_tx_blocked_pkt);
   ps.setSafetyRxInvalid(health.safety_rx_invalid_pkt);
-  ps.setIgnitionLine(health.ignition_line_pkt);
-  ps.setIgnitionCan(health.ignition_can_pkt);
-  ps.setControlsAllowed(health.controls_allowed_pkt);
+  ps.setIgnitionLine((health.flags_pkt & HEALTH_FLAG_IGNITION_LINE) != 0U);
+  ps.setIgnitionCan((health.flags_pkt & HEALTH_FLAG_IGNITION_CAN) != 0U);
+  ps.setControlsAllowed((health.flags_pkt & HEALTH_FLAG_CONTROLS_ALLOWED) != 0U);
   ps.setTxBufferOverflow(health.tx_buffer_overflow_pkt);
   ps.setRxBufferOverflow(health.rx_buffer_overflow_pkt);
   ps.setPandaType(hw_type);
   ps.setSafetyModel(cereal::CarParams::SafetyModel(health.safety_mode_pkt));
   ps.setSafetyParam(health.safety_param_pkt);
   ps.setFaultStatus(cereal::PandaState::FaultStatus(health.fault_status_pkt));
-  ps.setPowerSaveEnabled((bool)(health.power_save_enabled_pkt));
-  ps.setHeartbeatLost((bool)(health.heartbeat_lost_pkt));
+  ps.setPowerSaveEnabled((health.flags_pkt & HEALTH_FLAG_POWER_SAVE_ENABLED) != 0U);
+  ps.setHeartbeatLost((health.flags_pkt & HEALTH_FLAG_HEARTBEAT_LOST) != 0U);
   ps.setAlternativeExperience(health.alternative_experience_pkt);
   ps.setHarnessStatus(cereal::PandaState::HarnessStatus(health.car_harness_status_pkt));
-  ps.setInterruptLoad(health.interrupt_load_pkt);
+  ps.setInterruptLoad(health.interrupt_load_pkt / 255.0f);
   ps.setFanPower(health.fan_power);
-  ps.setSafetyRxChecksInvalid((bool)(health.safety_rx_checks_invalid_pkt));
+  ps.setSafetyRxChecksInvalid((health.flags_pkt & HEALTH_FLAG_SAFETY_RX_CHECKS_INVALID) != 0U);
   ps.setSpiErrorCount(health.spi_error_count_pkt);
   ps.setSbu1Voltage(health.sbu1_voltage_mV / 1000.0f);
   ps.setSbu2Voltage(health.sbu2_voltage_mV / 1000.0f);
@@ -198,10 +198,10 @@ std::optional<bool> send_panda_states(PubMaster *pm, Panda *panda, bool is_onroa
   }
 
   if (spoofing_started) {
-    health.ignition_line_pkt = 1;
+    health.flags_pkt |= HEALTH_FLAG_IGNITION_LINE;
   }
 
-  bool ignition_local = ((health.ignition_line_pkt != 0) || (health.ignition_can_pkt != 0)) && !always_offroad;
+  bool ignition_local = ((health.flags_pkt & (HEALTH_FLAG_IGNITION_LINE | HEALTH_FLAG_IGNITION_CAN)) != 0U) && !always_offroad;
 
   // Make sure CAN buses are live: safety_setter_thread does not work if Panda CAN are silent and there is only one other CAN node
   if (health.safety_mode_pkt == (uint8_t)(cereal::CarParams::SafetyModel::SILENT)) {
@@ -209,7 +209,7 @@ std::optional<bool> send_panda_states(PubMaster *pm, Panda *panda, bool is_onroa
   }
 
   bool power_save_desired = !ignition_local;
-  if (health.power_save_enabled_pkt != power_save_desired) {
+  if (((health.flags_pkt & HEALTH_FLAG_POWER_SAVE_ENABLED) != 0U) != power_save_desired) {
     panda->set_power_saving(power_save_desired);
   }
 
@@ -342,8 +342,8 @@ void process_peripheral_state(Panda *panda, PubMaster *pm, bool no_fan_control,
       }
     }
 
-    // Disable IR on input timeout
-    if (nanos_since_boot() - last_cabin_camera_t > 1e9) {
+    // Disable IR on input timeout or when requested offroad.
+    if (nanos_since_boot() - last_cabin_camera_t > 1e9 || (!is_onroad && params.getBool("DisableDriverCameraIR"))) {
       ir_pwr = 0;
     }
 

openpilot/selfdrive/pandad/tests/test_pandad_spi.py

@@ -102,7 +102,6 @@ class TestBoarddSpi(OpenpilotTestCase):
         edt = 1e3 / SERVICE_LIST[service].frequency
         assert edt*0.9 < np.mean(dts) < edt*1.1
         assert np.max(dts) < edt*8
-        assert np.min(dts) < edt
         assert len(dts) >= ((et-0.5)*SERVICE_LIST[service].frequency*0.8)
 
     with subtests.test(msg="CAN traffic"):

openpilot/selfdrive/selfdrived/alerts_offroad.json

@@ -17,8 +17,32 @@
     "severity": 1,
     "_comment": "Set extra field to the failed reason."
   },
-  "Offroad_NeosUpdate": {
-    "text": "An update to your device's operating system is downloading in the background. You will be prompted to update when it's ready to install.",
+  "Offroad_ChestnutBranch": {
+    "text": "Chestnut detected! Switch to the %1 branch to use chestnut-class models.",
+    "severity": -1
+  },
+  "Offroad_ChestnutNotDetected": {
+    "text": "Chestnut not detected. Check USB and 12V connections.",
+    "severity": 0
+  },
+  "Offroad_ChestnutOverheated": {
+    "text": "Chestnut overheated. Ensure good airflow. Current GPU temperature is %1.",
+    "severity": 0
+  },
+  "Offroad_ChestnutPcieUnavailable": {
+    "text": "%1",
+    "severity": 0
+  },
+  "Offroad_ChestnutUncompiled": {
+    "text": "Chestnut model not compiled. Keep ignition on and reboot the comma.",
+    "severity": 0
+  },
+  "Offroad_ChestnutUpdateFailed": {
+    "text": "Chestnut update failed. Check the USB cable.",
+    "severity": 0
+  },
+  "Offroad_ChestnutUsbSlow": {
+    "text": "Chestnut USB link is slow. Check the USB cable. The current speed is %1.",
     "severity": 0
   },
   "Offroad_UnregisteredHardware": {

openpilot/selfdrive/selfdrived/events.py

@@ -234,7 +234,8 @@ EVENTS: dict[int, dict[str, Alert | AlertCallbackType]] = {
   },
 
   EventName.bigModelFailed: {
-    ET.PERMANENT: NormalPermanentAlert("Big Model Failed ", "Restart the car to retry,\nnow driving on small model", duration=20.),
+    ET.SOFT_DISABLE: soft_disable_alert("Big Model Failed"),
+    ET.PERMANENT: NormalPermanentAlert("Big Model Failed ", "Restart the car to retry,\nsmall model is still available", duration=20.),
   },
 
   EventName.lateralManeuver: {

openpilot/selfdrive/selfdrived/selfdrived.py

@@ -195,17 +195,18 @@ class SelfdriveD(CruiseHelper):
       self.events.add(EventName.joystickDebug)
       self.startup_event = None
 
-    loading = self.params.get_bool("UsbGpuLoading")
+    loading = self.params.get_bool("ChestnutLoading")
     if self.big_model_loading and not loading:
       self.big_model_ready_t = time.monotonic()
+      self.events_sp.add(custom.OnroadEventSP.EventName.bigModelReady)
     self.big_model_loading = loading
     if self.big_model_loading:
       self.events.add(EventName.bigModelLoading)
 
-    big_active = self.params.get("UsbGpuActive")
-    usbgpu_present = self.sm['deviceState'].chestnutPresent
+    big_active = self.params.get("ChestnutActive")
+    chestnut_present = self.sm['deviceState'].chestnutPresent
     model_unavailable = big_active is True and self.sm.seen['modelV2'] and not self.sm.alive['modelV2']
-    big_failed = big_active is False or model_unavailable or (self.big_model_active and not usbgpu_present)
+    big_failed = big_active is False or model_unavailable or (self.big_model_active and not chestnut_present)
     if big_failed and not self.big_model_failed:
       self.events.add(EventName.bigModelFailed)
     self.big_model_failed = big_failed
@@ -337,7 +338,7 @@ class SelfdriveD(CruiseHelper):
       device_motion = Pose.from_device_motion(self.sm['deviceMotion'])
       self.calibrated_pose = self.pose_calibrator.build_calibrated_pose(device_motion)
 
-    if self.calibrated_pose is not None:
+    if self.calibrated_pose is not None and not self.CP.notCar:
       excessive_actuation = self.excessive_actuation_check.update(self.sm, CS, self.calibrated_pose)
       if not self.excessive_actuation and excessive_actuation is not None:
         set_offroad_alert("Offroad_ExcessiveActuation", True, extra_text=str(excessive_actuation))
@@ -397,6 +398,9 @@ class SelfdriveD(CruiseHelper):
     # All events here should at least have NO_ENTRY and SOFT_DISABLE.
     num_events = len(self.events)
 
+    if self.big_model_active and big_failed:
+      self.events.add(EventName.bigModelFailed)
+
     not_running = {p.name for p in self.sm['managerState'].processes if not p.running and p.shouldBeRunning}
     if self.sm.recv_frame['managerState'] and len(not_running):
       if not_running != self.not_running_prev:
@@ -449,11 +453,12 @@ class SelfdriveD(CruiseHelper):
       self.logged_comm_issue = None
 
     if not self.CP.notCar and not big_model_settling:  # localization has nothing to work with during the load
-      if not self.sm['deviceMotion'].posenetOK:
+      # the defaults of a message that was never received are not a localizer failure
+      if self.sm.seen['deviceMotion'] and not self.sm['deviceMotion'].posenetOK:
         self.events.add(EventName.posenetInvalid)
-      if not self.sm['deviceMotion'].inputsOK:
+      if self.sm.seen['deviceMotion'] and not self.sm['deviceMotion'].inputsOK:
         self.events.add(EventName.locationdTemporaryError)
-      if (not self.sm['vehicleParameters'].valid and cal_status == log.ExtrinsicsCalibration.Status.calibrated and
+      if (self.sm.seen['vehicleParameters'] and not self.sm['vehicleParameters'].valid and cal_status == log.ExtrinsicsCalibration.Status.calibrated and
           not TESTING_CLOSET and (not SIMULATION or REPLAY)):
         self.events.add(EventName.paramsdTemporaryError)
 

openpilot/selfdrive/test/chestnut.sh

@@ -0,0 +1,6 @@
+#!/usr/bin/env bash
+set -e
+
+sudo python3 openpilot/system/hardware/chestnut/flash.py
+
+SCONSFLAGS="-j4" ./openpilot/system/manager/build.py

openpilot/selfdrive/test/process_replay/migration.py

@@ -152,7 +152,7 @@ def migrate_drivingModelData(msgs):
   add_ops = []
   for _, msg in msgs:
     dmd = messaging.new_message('drivingModelData', valid=msg.valid, logMonoTime=msg.logMonoTime)
-    for field in ["frameId", "frameIdExtra", "frameDropPerc", "modelExecutionTime", "action"]:
+    for field in ["frameId", "frameIdExtra", "frameDropPerc", "modelExecutionTime", "big", "action"]:
       setattr(dmd.drivingModelData, field, getattr(msg.modelV2, field))
     for meta_field in ["laneChangeState", "laneChangeState"]:
       setattr(dmd.drivingModelData.meta, meta_field, getattr(msg.modelV2.meta, meta_field))

openpilot/selfdrive/test/process_replay/model_replay.py

@@ -20,11 +20,13 @@ from openpilot.tools.lib.framereader import FrameReader
 from openpilot.tools.lib.logreader import LogReader, save_log
 from openpilot.tools.lib.github_utils import GithubUtils
 
-TEST_ROUTE = "8494c69d3c710e81|000001d4--2648a9a404"
-SEGMENT = 4
+TEST_ROUTE = "98395b7c5b27882e|0000002b--2686b5a2d0"
+SEGMENT = 1
 START_FRAME = 0
 END_FRAME = 60
 
+CHESTNUT = "--chestnut" in sys.argv
+
 SEND_EXTRA_INPUTS = bool(int(os.getenv("SEND_EXTRA_INPUTS", "0")))
 
 DATA_TOKEN = os.getenv("CI_ARTIFACTS_TOKEN","")
@@ -33,13 +35,13 @@ MODEL_REPLAY_BUCKET="model_replay_master"
 GITHUB = GithubUtils(API_TOKEN, DATA_TOKEN)
 
 EXEC_TIMINGS = [
-  # model, instant max, average max
-  ("modelV2", 0.05, 0.028),
-  ("driverStateV2", 0.05, 0.018),
+  # model, instant max, average max, chestnut average max
+  ("modelV2", 0.05, 0.03, 0.05),
+  ("driverStateV2", 0.05, 0.018, 0.018),
 ]
 
 def get_log_fn(test_route, ref="master"):
-  return f"{test_route}_model_tici_{ref}.zst"
+  return f"{test_route}_model_{'chestnut' if CHESTNUT else 'tici'}_{ref}.zst"
 
 def plot(proposed, master, title, tmp):
   proposed = list(proposed)
@@ -169,11 +171,15 @@ def model_replay(lr, frs):
   dmonitoringmodeld_msgs = replay_process(dmonitoringmodeld, dmodeld_logs, frs)
 
   msgs = modeld_msgs + dmonitoringmodeld_msgs
+  chestnut = any(m.modelV2.big for m in modeld_msgs if m.which() == "modelV2")
+  if CHESTNUT:
+    assert chestnut and all(m.modelV2.big for m in modeld_msgs if m.which() == "modelV2"), "Chestnut replay must run the big model without fallback"
 
   header = ['model', 'max instant', 'max instant allowed', 'average', 'max average allowed', 'test result']
   rows = []
   timings_ok = True
-  for (s, instant_max, avg_max) in EXEC_TIMINGS:
+  for (s, instant_max, avg_max, chestnut_avg_max) in EXEC_TIMINGS:
+    avg_max = chestnut_avg_max if chestnut else avg_max
     ts = [getattr(m, s).modelExecutionTime for m in msgs if m.which() == s]
     # TODO some init can happen in first iteration
     ts = ts[1:]
@@ -283,7 +289,8 @@ if __name__ == "__main__":
       diff_short, diff_long, failed = format_diff(results, log_paths, 'master')
 
       if "CI" in os.environ:
-        comment_replay_report(log_msgs, cmp_log, log_msgs)
+        if not CHESTNUT:
+          comment_replay_report(log_msgs, cmp_log, log_msgs)
         failed = False
         print(diff_long)
       print('-------------\n'*5)

openpilot/selfdrive/test/process_replay/process_replay.py

@@ -17,7 +17,7 @@ from openpilot.common.hardware.hw import Paths
 import openpilot.cereal.messaging as messaging
 from opendbc.car.structs import car
 from openpilot.cereal.services import SERVICE_LIST
-from msgq.visionipc import VisionIpcServer, get_endpoint_name as vipc_get_endpoint_name
+from msgq.visionipc import VisionIpcClient, VisionIpcServer, get_endpoint_name as vipc_get_endpoint_name
 from opendbc.car.can_definitions import CanData
 from opendbc.car.car_helpers import get_car, interfaces
 from openpilot.common.params import Params
@@ -210,6 +210,7 @@ class ProcessContainer:
         stride, y_height, _, yuv_size = get_nv12_info(frame_size[0], frame_size[1])
         vipc_server.create_buffers_with_sizes(meta.stream, 2, frame_size[0], frame_size[1], yuv_size, stride, stride * y_height)
     vipc_server.start_listener()
+    VisionIpcClient.available_streams("camerad", block=True)
 
     self.vipc_server = vipc_server
     self.cfg.vision_pubs = [meta.camera_state for meta in streams_metas if meta.camera_state in self.cfg.vision_pubs]

openpilot/selfdrive/test/process_replay/test_processes.py

@@ -7,7 +7,7 @@ import traceback
 from collections import defaultdict
 from tqdm import tqdm
 from typing import Any
-from opendbc.car.car_helpers import interface_names
+from opendbc.car.car_helpers import interface_names, interfaces
 from openpilot.common.git import get_commit
 from openpilot.tools.lib.openpilotci import get_url
 from openpilot.selfdrive.test.process_replay.compare_logs import compare_logs, format_diff
@@ -64,7 +64,8 @@ segments = [
 ]
 
 # dashcamOnly makes don't need to be tested until a full port is done
-excluded_interfaces = ["mock", "body", "psa"]
+excluded_interfaces = {brand for brand, platforms in interface_names.items()
+                       if all(interfaces[platform].get_non_essential_params(platform).dashcamOnly for platform in platforms)} | {"body"}
 
 BASE_URL = "https://raw.githubusercontent.com/sunnypilot/ci-artifacts/refs/heads/process-replay/"
 REF_COMMIT_FN = os.path.join(PROC_REPLAY_DIR, "ref_commit")

openpilot/selfdrive/test/scons_build_test.sh

@@ -3,7 +3,7 @@ set -e
 
 SCRIPT_DIR=$(dirname "$0")
 BASEDIR=$(realpath "$SCRIPT_DIR/../../../")
-cd $BASEDIR
+cd "$BASEDIR"
 
 # tests that our build system's dependencies are configured properly,
 # needs a machine with lots of cores
@@ -11,7 +11,7 @@ cd $BASEDIR
 # helpful commands:
 # scons -Q --tree=derived
 
-cd $BASEDIR/opendbc_repo/
+cd "$BASEDIR/opendbc_repo/"
 scons --clean
 scons --no-cache --random
 if ! scons -q; then

openpilot/selfdrive/test/setup_device_ci.sh

@@ -29,7 +29,7 @@ if [ -d /data/safe_staging/ ]; then
 fi
 
 CONTINUE_PATH="/data/continue.sh"
-tee $CONTINUE_PATH << EOF
+tee "$CONTINUE_PATH" << EOF
 #!/usr/bin/env bash
 
 sudo abctl --set_success
@@ -54,13 +54,18 @@ done
 
 sleep infinity
 EOF
-chmod +x $CONTINUE_PATH
+chmod +x "$CONTINUE_PATH"
 
 export GIT_LFS_SKIP_SMUDGE=1
 pull_lfs() {
-  # The big driving model is not used on these devices yet. Keep its pointer in
-  # the worktree, but don't download or copy the 1.8 GB LFS object.
-  LFS_EXCLUDE="openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
+  if [ -n "${CHESTNUT:-}" ]
+  then
+    git lfs pull --exclude=''
+    return
+  fi
+
+  # Keep the precompiled big model as a pointer on devices without Chestnut.
+  LFS_EXCLUDE="openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl"
 
   git config --local lfs.fetchexclude "$LFS_EXCLUDE"
   git lfs pull --exclude="$LFS_EXCLUDE"
@@ -81,16 +86,16 @@ pull_lfs() {
 safe_checkout() {
   # completely clean TEST_DIR
 
-  cd $SOURCE_DIR
+  cd "$SOURCE_DIR"
 
   # cleanup orphaned locks
   find .git -type f -name "*.lock" -exec rm {} +
 
   git reset --hard
-  git fetch --no-tags --no-recurse-submodules -j4 --verbose --depth 1 origin $GIT_COMMIT
+  git fetch --no-tags --no-recurse-submodules -j4 --verbose --depth 1 origin "$GIT_COMMIT"
   find . -maxdepth 1 -not -path './.git' -not -name '.' -not -name '..' -exec rm -rf '{}' \;
-  git reset --hard $GIT_COMMIT
-  git checkout $GIT_COMMIT
+  git reset --hard "$GIT_COMMIT"
+  git checkout "$GIT_COMMIT"
   git clean -xdff
   git submodule sync
   git submodule foreach --recursive "git reset --hard && git clean -xdff"
@@ -100,22 +105,22 @@ safe_checkout() {
   pull_lfs
 
   echo "git checkout done, t=$SECONDS"
-  du -hs $SOURCE_DIR $SOURCE_DIR/.git
+  du -hs "$SOURCE_DIR" "$SOURCE_DIR/.git"
 
-  rsync -a --delete $SOURCE_DIR $TEST_DIR
+  rsync -a --delete "$SOURCE_DIR" "$TEST_DIR"
 }
 
 unsafe_checkout() {( set -e
   # checkout directly in test dir, leave old build products
 
-  cd $TEST_DIR
+  cd "$TEST_DIR"
 
   # cleanup orphaned locks
   find .git -type f -name "*.lock" -exec rm {} +
 
-  git fetch --no-tags --no-recurse-submodules -j8 --verbose --depth 1 origin $GIT_COMMIT
-  git checkout --force --no-recurse-submodules $GIT_COMMIT
-  git reset --hard $GIT_COMMIT
+  git fetch --no-tags --no-recurse-submodules -j8 --verbose --depth 1 origin "$GIT_COMMIT"
+  git checkout --force --no-recurse-submodules "$GIT_COMMIT"
+  git reset --hard "$GIT_COMMIT"
   git clean -dff
   git submodule sync
   git submodule foreach --recursive "git reset --hard && git clean -df"
@@ -129,7 +134,7 @@ export GIT_PACK_THREADS=8
 
 # set up environment
 if [ ! -d "$SOURCE_DIR" ]; then
-  git clone https://github.com/commaai/openpilot.git $SOURCE_DIR
+  git clone https://github.com/commaai/openpilot.git "$SOURCE_DIR"
 fi
 
 if [ ! -z "$UNSAFE" ]; then
@@ -146,7 +151,7 @@ else
 fi
 
 # submodule package symlinks for PYTHONPATH imports on device (same as launch_chffrplus.sh)
-cd $TEST_DIR
+cd "$TEST_DIR"
 ln -sfn msgq_repo/msgq msgq
 ln -sfn opendbc_repo/opendbc opendbc
 ln -sfn rednose_repo/rednose rednose

openpilot/selfdrive/test/test_onroad.py

@@ -20,8 +20,12 @@ from openpilot.common.basedir import BASEDIR
 from openpilot.common.timeout import Timeout
 from openpilot.common.params import Params
 from openpilot.selfdrive.selfdrived.events import EVENTS, ET
-from openpilot.selfdrive.test.helpers import set_params_enabled, release_only
+from openpilot.selfdrive.test.helpers import set_params_enabled, release_only, processes_context, log_collector
+from openpilot.common.hardware import HARDWARE
 from openpilot.common.hardware.hw import Paths
+from openpilot.common.mock import mock_messages
+from opendbc.car.car_helpers import get_demo_car_params
+from openpilot.selfdrive.modeld.helpers import chestnut_present, chestnut_compiled
 from openpilot.tools.lib.logreader import LogReader
 from openpilot.tools.lib.log_time_series import msgs_to_time_series
 
@@ -67,7 +71,7 @@ PROCS = {
   "openpilot.selfdrive.pandad.pandad": 0,
   "openpilot.system.loggerd.uploader": 15.0,
   "openpilot.system.loggerd.deleter": 1.0,
-  "./pandad": 19.0,
+  "./pandad": 40.0,
   "openpilot.system.qcomgpsd.qcomgpsd": 1.0,
   "openpilot.common.hardware.comma.modem": 10.0,
 }
@@ -107,6 +111,10 @@ def cputime_total(ct):
 class TestOnroad(OpenpilotTestCase):
   COMMA_HARDWARE_TEST = True
 
+  def setUp(self):
+    # Hardware setup is handled once for the full onroad test in setup_class.
+    unittest.TestCase.setUp(self)
+
   @classmethod
   def setup_class(cls):
     if "DEBUG" in os.environ:
@@ -332,26 +340,34 @@ class TestOnroad(OpenpilotTestCase):
             assert np.all(eof_sof_diff < 50*1e6)
 
         first_fid = {min(self.ts[c]['frameId']) for c in cams}
-        assert len(first_fid) == 1, "Cameras don't start on same frame ID"
-        if cam.endswith('CameraState'):
+        if cams[0].endswith('CameraState'):
           # camerad guarantees that all cams start on frame ID 0
           # (note loggerd also needs to start up fast enough to catch it)
-          assert next(iter(first_fid)) < 100, "Cameras start on frame ID too high"
+          assert min(first_fid) < 100, "Cameras start on frame ID too high"
+        else:
+          # encoderd synchronizes all camera encoders to the same starting frame
+          assert len(first_fid) == 1, "Camera encoders don't start on same frame ID"
 
         # we don't do a full segment rotation, so these might not match exactly
         last_fid = {max(self.ts[c]['frameId']) for c in cams}
         assert max(last_fid) - min(last_fid) < 10
 
-        start, end = min(first_fid), min(last_fid)
-        for i in range(end-start):
+        timestamps = {
+          cam: dict(zip(self.ts[cam]['frameId'], self.ts[cam]['timestampSof'], strict=True))
+          for cam in cams
+        }
+        common_frame_ids = set.intersection(*(set(ts) for ts in timestamps.values()))
+        assert common_frame_ids, "Cameras have no overlapping frame IDs"
+
+        for frame_id in sorted(common_frame_ids):
           # road and wide cameras (first two) should be synced within 2ms
-          ts = {c: round(self.ts[c]['timestampSof'][i]/1e6, 1) for c in cams[:2]}
-          diff = (max(ts.values()) - min(ts.values()))
-          assert diff < 2, f"Cameras not synced properly: frame_id={start+i}, {diff=:.1f}ms, {ts=}"
+          ts = {cam: timestamps[cam][frame_id] / 1e6 for cam in cams[:2]}
+          diff = max(ts.values()) - min(ts.values())
+          assert diff < 2, f"Cameras not synced properly: {frame_id=}, {diff=:.1f}ms, {ts=}"
 
           # cabin camera should be staggered ~25ms from road camera
-          offset_ms = abs(self.ts[cams[2]]['timestampSof'][i] - self.ts[cams[0]]['timestampSof'][i]) / 1e6
-          assert 20 < offset_ms < 30, f"cabin camera stagger out of range at frame {start+i}: {offset_ms:.1f}ms"
+          offset_ms = abs(timestamps[cams[2]][frame_id] - timestamps[cams[0]][frame_id]) / 1e6
+          assert 20 < offset_ms < 30, f"cabin camera stagger out of range at frame {frame_id}: {offset_ms:.1f}ms"
 
   def test_camera_encoder_matches(self, subtests):
     # sanity check that the frame metadata is consistent with the encoded frames
@@ -445,5 +461,43 @@ class TestOnroad(OpenpilotTestCase):
            f"Not engageable for whole segment:\n- selfdriveState.engageable: {Counter(eng)}\n- No entry events: {no_entries}"
 
 
+@unittest.skipUnless(HARDWARE.get_device_type() == "mici", "requires MICI")
+class TestChestnutOnroad(OpenpilotTestCase):
+  COMMA_HARDWARE_TEST = True
+
+  @mock_messages(['deviceMotion'])
+  def test_camera_models(self, subtests):
+    assert chestnut_present() and chestnut_compiled()
+    Params().put("CarParams", get_demo_car_params().to_bytes(), block=True)
+    services = ['narrowRoadCameraState', 'wideRoadCameraState', 'cabinCameraState', 'modelV2', 'driverStateV2']
+    sm = messaging.SubMaster(services)
+    pm = messaging.PubMaster(['deviceState'])
+    device_state = messaging.new_message('deviceState')
+    device_state.deviceState.deviceType = HARDWARE.get_device_type()
+    device_state_bytes = device_state.to_bytes()
+    with processes_context(['camerad', 'calibrationd', 'modeld', 'dmonitoringmodeld']):
+      with Timeout(60, "camera models didn't start"):
+        while not all(sm.seen.values()) or not sm.valid['modelV2']:
+          pm.send('deviceState', device_state_bytes)
+          sm.update(1000)
+      with log_collector(services) as (logs, _):
+        time.sleep(TEST_DURATION)
+
+    msgs = {s: [m for m in logs if m.which() == s] for s in services}
+    for service, messages in msgs.items():
+      with subtests.test(service=service):
+        expected = TEST_DURATION * SERVICE_LIST[service].frequency
+        assert np.isclose(len(messages), expected, rtol=0.05, atol=2), f"{service}: expected {expected}, got {len(messages)}"
+        assert all(m.valid for m in messages)
+        frame_ids = [getattr(m, service).frameId for m in messages]
+        assert np.all(np.diff(frame_ids) > 0), f"{service}: repeated or reordered frames"
+
+    camera_frames = {m.narrowRoadCameraState.frameId for m in msgs['narrowRoadCameraState']}
+    model_frames = {m.modelV2.frameId for m in msgs['modelV2']}
+    assert len(camera_frames & model_frames) >= TEST_DURATION * SERVICE_LIST['modelV2'].frequency * 0.9
+    assert all(m.modelV2.big for m in msgs['modelV2']), "Chestnut fell back to the small model"
+    assert all(np.isfinite(m.modelV2.position.x).all() for m in msgs['modelV2'])
+
+
 if __name__ == "__main__":
   unittest.main()

openpilot/selfdrive/test/test_power_draw.py

@@ -5,6 +5,8 @@ import time
 import unittest
 import numpy as np
 from dataclasses import dataclass
+from panda import Panda
+from openpilot.common.hardware import HARDWARE
 from openpilot.common.test import OpenpilotTestCase
 from openpilot.common.utils import tabulate
 
@@ -14,11 +16,14 @@ from opendbc.car.car_helpers import get_demo_car_params
 from openpilot.common.mock import mock_messages
 from openpilot.common.params import Params
 from openpilot.common.hardware.comma.power_monitor import get_power
+from openpilot.selfdrive.modeld.helpers import chestnut_present
 from openpilot.system.manager.process_config import managed_processes
 from openpilot.system.manager.manager import manager_cleanup
 
 SAMPLE_TIME = 2       # seconds to sample power
 MAX_WARMUP_TIME = 30  # seconds to wait for SAMPLE_TIME consecutive valid samples
+MICI = HARDWARE.get_device_type() == "mici"
+CHESTNUT = chestnut_present()
 
 @dataclass
 class Proc:
@@ -33,9 +38,10 @@ class Proc:
     return '+'.join(self.procs)
 
 
+# MICI readings exclude the separately powered Chestnut GPU.
 PROCS = [
-  Proc(['camerad'], 1.65, atol=0.4, msgs=['narrowRoadCameraState', 'wideRoadCameraState', 'cabinCameraState']),
-  Proc(['modeld'], 1.5, atol=0.2, msgs=['modelV2']),
+  Proc(['camerad'], 0.85 if MICI else 1.65, atol=0.4, msgs=['narrowRoadCameraState', 'wideRoadCameraState', 'cabinCameraState']),
+  Proc(['modeld'], 0.45 if MICI and CHESTNUT else 1.5, atol=0.2, msgs=['modelV2']),
   Proc(['dmonitoringmodeld'], 0.65, atol=0.35, msgs=['driverStateV2']),
   Proc(['encoderd'], 0.23, msgs=[]),
 ]
@@ -46,6 +52,13 @@ class TestPowerDraw(OpenpilotTestCase):
 
   def setup_method(self):
     Params().put("CarParams", get_demo_car_params().to_bytes(), block=True)
+    self.panda = None
+    if MICI:
+      HARDWARE.reset_internal_panda()
+      self.addCleanup(HARDWARE.reset_internal_panda)
+      Panda.wait_for_panda(None, 30)
+      self.panda = Panda(cli=False)
+      self.addCleanup(self.panda.close)
 
   def teardown_method(self):
     manager_cleanup()
@@ -78,7 +91,7 @@ class TestPowerDraw(OpenpilotTestCase):
     start_time = time.monotonic()
 
     while (time.monotonic() - start_time) < MAX_WARMUP_TIME:
-      power = get_power(1)
+      power = get_power(1, self.panda)
       iteration_msg_counts = {}
       for msg,sock in socks.items():
         iteration_msg_counts[msg] = len(messaging.drain_sock_raw(sock))
@@ -97,7 +110,7 @@ class TestPowerDraw(OpenpilotTestCase):
 
   @mock_messages(['deviceMotion'])
   def test_camera_procs(self, subtests):
-    baseline = get_power()
+    baseline = get_power(panda=self.panda)
 
     prev = baseline
     used = {}

openpilot/selfdrive/ui/body/layouts/onroad.py

@@ -1,7 +1,7 @@
 import time
 import pyray as rl
 
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.selfdrive.ui.ui_state import ui_state
@@ -26,8 +26,8 @@ class BodyLayout(Widget):
     self._last_input_time = time.monotonic()
     self._was_active = False
     self._offroad_label = UnifiedLabel("turn on ignition to use", 95 if gui_app.big_ui() else 45, FontWeight.DISPLAY,
-                                       alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                                       alignment=TextAlignment.CENTER,
+                                       alignment_vertical=TextAlignmentVertical.MIDDLE)
 
   def draw_dot_grid(self, rect: rl.Rectangle, dots: list[tuple[int, int]], color: rl.Color):
     spacing = min(rect.height / GRID_ROWS, rect.width / GRID_COLS)

openpilot/selfdrive/ui/layouts/home.py

@@ -8,7 +8,7 @@ from openpilot.selfdrive.ui.widgets.exp_mode_button import ExperimentalModeButto
 from openpilot.selfdrive.ui.widgets.prime import PrimeWidget
 from openpilot.selfdrive.ui.widgets.setup import SetupWidget
 from openpilot.system.ui.lib.text_measure import measure_text_cached
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos, TextAlignment
 from openpilot.system.ui.lib.multilang import tr, trn
 from openpilot.system.ui.widgets.label import gui_label
 from openpilot.system.ui.widgets import Widget
@@ -178,7 +178,7 @@ class HomeLayout(Widget):
 
     version_rect = rl.Rectangle(self.header_rect.x + self.header_rect.width - version_text_width, self.header_rect.y,
                                 version_text_width, self.header_rect.height)
-    gui_label(version_rect, self._version_text, 48, rl.WHITE, alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
+    gui_label(version_rect, self._version_text, 48, rl.WHITE, alignment=TextAlignment.RIGHT)
 
   def _render_home_content(self):
     self._render_left_column()

openpilot/selfdrive/ui/layouts/main.py

@@ -3,7 +3,6 @@ from enum import IntEnum
 import openpilot.cereal.messaging as messaging
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.widgets import Widget
-from openpilot.selfdrive.ui.sunnypilot.custom_button import CustomButtonAction, handle_custom_button
 from openpilot.selfdrive.ui.layouts.sidebar import Sidebar, SIDEBAR_WIDTH
 from openpilot.selfdrive.ui.layouts.home import HomeLayout
 from openpilot.selfdrive.ui.layouts.settings.settings import SettingsLayout, PanelType
@@ -28,7 +27,6 @@ class MainLayout(Widget):
     super().__init__()
 
     self._pm = messaging.PubMaster(['bookmarkButton', 'userBookmark'])
-    self._custom_button_sock = messaging.sub_sock('carState')
 
     self._sidebar = Sidebar()
     self._current_mode = MainState.HOME
@@ -42,10 +40,6 @@ class MainLayout(Widget):
       MainState.SETTINGS: SettingsLayout(),
       MainState.ONROAD: AugmentedRoadView(),
     }
-    self._custom_button_callbacks = {
-      CustomButtonAction.BOOKMARK: self._on_bookmark_clicked,
-      CustomButtonAction.CYCLE_UI: self._cycle_ui,
-    }
 
     self._sidebar_rect = rl.Rectangle(0, 0, 0, 0)
     self._content_rect = rl.Rectangle(0, 0, 0, 0)
@@ -61,7 +55,6 @@ class MainLayout(Widget):
       gui_app.push_widget(self._onboarding_window)
 
   def _render(self, _):
-    handle_custom_button(messaging.drain_sock(self._custom_button_sock), ui_state.params, self._custom_button_callbacks)
     self._handle_onroad_transition()
     self._render_main_content()
 
@@ -121,18 +114,6 @@ class MainLayout(Widget):
   def _on_settings_clicked(self):
     self.open_settings(PanelType.DEVICE)
 
-  def _show_onroad(self):
-    self._set_current_layout(MainState.ONROAD)
-    self._sidebar.set_visible(False)
-
-  def _cycle_ui(self):
-    if self._current_mode == MainState.ONROAD and not self._sidebar.is_visible:
-      self._sidebar.set_visible(True)
-    elif self._current_mode == MainState.SETTINGS:
-      self._show_onroad()
-    else:
-      self._on_settings_clicked()
-
   def _on_bookmark_clicked(self):
     for service in ('bookmarkButton', 'userBookmark'):
       msg = messaging.new_message(service, valid=True)

openpilot/selfdrive/ui/layouts/onboarding.py

@@ -5,7 +5,7 @@ from enum import IntEnum
 
 import pyray as rl
 from openpilot.common.basedir import BASEDIR
-from openpilot.system.ui.lib.application import FontWeight, gui_app
+from openpilot.system.ui.lib.application import FontWeight, TextAlignment, gui_app
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.button import Button, ButtonStyle
@@ -115,9 +115,9 @@ class TermsPage(Widget):
     self._on_accept = on_accept
     self._on_decline = on_decline
 
-    self._title = Label(tr("Welcome to sunnypilot"), font_size=90, font_weight=FontWeight.BOLD, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT)
+    self._title = Label(tr("Welcome to sunnypilot"), font_size=90, font_weight=FontWeight.BOLD, text_alignment=TextAlignment.LEFT)
     self._desc = Label(tr("You must accept the Terms of Service to use sunnypilot. Read the latest terms at https://sunnypilot.ai/terms before continuing."),
-                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT)
+                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=TextAlignment.LEFT)
 
     self._decline_btn = Button(tr("Decline"), click_callback=on_decline)
     self._accept_btn = Button(tr("Agree"), button_style=ButtonStyle.PRIMARY, click_callback=on_accept)
@@ -150,7 +150,7 @@ class DeclinePage(Widget):
   def __init__(self, back_callback=None):
     super().__init__()
     self._text = Label(tr("You must accept the Terms of Service in order to use sunnypilot."),
-                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT)
+                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=TextAlignment.LEFT)
     self._back_btn = Button(tr("Back"), click_callback=back_callback)
     self._uninstall_btn = Button(tr("Decline, uninstall sunnypilot"), button_style=ButtonStyle.DANGER,
                                  click_callback=self._on_uninstall_clicked)

openpilot/selfdrive/ui/layouts/settings/software.py

@@ -199,6 +199,9 @@ class SoftwareLayout(Widget):
         selection = self._branch_dialog.selection
         ui_state.params.put("UpdaterTargetBranch", selection, block=True)
         self._branch_btn.action_item.set_value(selection)
+        self._download_btn.action_item.set_enabled(False)
+        self._waiting_for_updater = True
+        self._waiting_start_ts = time.monotonic()
         subprocess.run("pkill -SIGUSR1 -f openpilot.system.updated.updated", shell=True)
       self._branch_dialog = None
 

openpilot/selfdrive/ui/layouts/sidebar.py

@@ -168,9 +168,16 @@ class Sidebar(Widget, SidebarSP):
     # Home/Flag button
     flag_pressed = mouse_down and rl.check_collision_point_rec(mouse_pos, HOME_BTN)
     button_img = self._flag_img if ui_state.started else self._home_img
+    button_pos = rl.Vector2(HOME_BTN.x, HOME_BTN.y)
+    icon_opacity = 1.0
+
+    if gui_app.sunnypilot_ui():
+      button_img, button_pos, icon_opacity = SidebarSP._get_home_icon(self, button_img)
 
     tint = Colors.BUTTON_PRESSED if (ui_state.started and flag_pressed) else Colors.BUTTON_NORMAL
-    rl.draw_texture_ex(button_img, rl.Vector2(HOME_BTN.x, HOME_BTN.y), 0.0, 1.0, tint)
+    if icon_opacity < 1.0:
+      tint = rl.Color(tint[0], tint[1], tint[2], int(255 * icon_opacity))
+    rl.draw_texture_ex(button_img, button_pos, 0.0, 1.0, tint)
 
     # Microphone button
     if self._recording_audio:

openpilot/selfdrive/ui/lib/prime_state.py

@@ -101,6 +101,10 @@ class PrimeState:
     with self._lock:
       return bool(self.prime_type > PrimeType.NONE)
 
+  def is_full_prime(self) -> bool:
+    with self._lock:
+      return self.prime_type > PrimeType.NONE and self.prime_type != PrimeType.LITE
+
   def is_paired(self) -> bool:
     with self._lock:
       return self.prime_type > PrimeType.UNPAIRED

openpilot/selfdrive/ui/mici/layouts/home.py

@@ -1,4 +1,7 @@
+from __future__ import annotations
+
 import datetime
+import math
 import time
 
 from openpilot.cereal import log
@@ -8,8 +11,8 @@ from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.layouts import HBoxLayout
 from openpilot.system.ui.widgets.icon_widget import IconWidget
 from openpilot.system.ui.widgets.label import UnifiedLabel, gui_label
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
-from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos, TextAlignment, TextAlignmentVertical
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.common.version import RELEASE_BRANCHES
 
 HEAD_BUTTON_FONT_SIZE = 40
@@ -38,16 +41,13 @@ class AlertsPill(Widget):
     self.set_rect(rl.Rectangle(0, 0, 104, 52))
 
     self._pill_bg_txt = gui_app.texture("icons_mici/alerts_pill.png", 104, 52)
-    self._icon_red = gui_app.texture("icons_mici/offroad_alerts/red_warning.png", 36, 36)
-    self._icon_orange = gui_app.texture("icons_mici/offroad_alerts/orange_warning.png", 36, 36)
-    self._icon_green = gui_app.texture("icons_mici/offroad_alerts/green_wheel.png", 36, 36)
     self._alert_count_callback: Callable[[], int] | None = None
-    self._max_severity_callback: Callable[[], int | None] | None = None
+    self._alert_icon_callback: Callable[[], rl.Texture | None] | None = None
 
   def set_alert_count_callback(self, callback: Callable[[], int] | None,
-                               severity_callback: Callable[[], int | None] | None = None):
+                               icon_callback: Callable[[], rl.Texture | None] | None = None):
     self._alert_count_callback = callback
-    self._max_severity_callback = severity_callback
+    self._alert_icon_callback = icon_callback
 
   def _render(self, _):
     alert_count = self._alert_count_callback() if self._alert_count_callback else 0
@@ -55,42 +55,37 @@ class AlertsPill(Widget):
       pill_w, pill_h = self._pill_bg_txt.width, self._pill_bg_txt.height
       rl.draw_texture_ex(self._pill_bg_txt, rl.Vector2(self.rect.x, self.rect.y), 0.0, 1.0, rl.WHITE)
 
-      severity = self._max_severity_callback() if self._max_severity_callback else None
-      if severity == -1:
-        warning_txt = self._icon_green
-      elif severity is not None and severity > 0:
-        warning_txt = self._icon_red
-      else:
-        warning_txt = self._icon_orange
-
-      warn_x = self.rect.x + self.ICON_OFFSET
-      warn_y = self.rect.y + (pill_h - warning_txt.height) / 2
-      rl.draw_texture_ex(warning_txt, rl.Vector2(warn_x, warn_y), 0.0, 1.0, rl.WHITE)
+      warning_txt = self._alert_icon_callback() if self._alert_icon_callback else None
+      if warning_txt is not None:
+        scale = 36 / max(warning_txt.width, warning_txt.height)
+        warn_x = self.rect.x + self.ICON_OFFSET
+        warn_y = self.rect.y + (pill_h - warning_txt.height * scale) / 2
+        rl.draw_texture_ex(warning_txt, rl.Vector2(warn_x, warn_y), 0.0, scale, rl.WHITE)
 
       count_rect = rl.Rectangle(self.rect.x + self.COUNT_OFFSET, self.rect.y, pill_w - self.COUNT_OFFSET, pill_h)
       gui_label(count_rect, str(alert_count), font_size=36,
-                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                alignment=TextAlignment.CENTER,
+                alignment_vertical=TextAlignmentVertical.MIDDLE)
 
 
 class NetworkIcon(Widget):
   def __init__(self):
     super().__init__()
-    self.set_rect(rl.Rectangle(0, 0, 54, 44))  # max size of all icons
+    self.set_rect(rl.Rectangle(0, 0, 60, 47))  # max size of all icons
     self._net_type = NetworkType.none
     self._net_strength = 0
 
-    self._wifi_slash_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_slash.png", 50, 44)
-    self._wifi_none_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_none.png", 50, 37)
-    self._wifi_low_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_low.png", 50, 37)
-    self._wifi_medium_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_medium.png", 50, 37)
-    self._wifi_full_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_full.png", 50, 37)
+    self._wifi_slash_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_slash.png", 54, 47)
+    self._wifi_none_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_none.png", 54, 40)
+    self._wifi_low_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_low.png", 54, 40)
+    self._wifi_medium_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_medium.png", 54, 40)
+    self._wifi_full_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_full.png", 54, 40)
 
-    self._cell_none_txt = gui_app.texture("icons_mici/settings/network/cell_strength_none.png", 54, 36)
-    self._cell_low_txt = gui_app.texture("icons_mici/settings/network/cell_strength_low.png", 54, 36)
-    self._cell_medium_txt = gui_app.texture("icons_mici/settings/network/cell_strength_medium.png", 54, 36)
-    self._cell_high_txt = gui_app.texture("icons_mici/settings/network/cell_strength_high.png", 54, 36)
-    self._cell_full_txt = gui_app.texture("icons_mici/settings/network/cell_strength_full.png", 54, 36)
+    self._cell_none_txt = gui_app.texture("icons_mici/settings/network/cell_strength_none.png", 60, 40)
+    self._cell_low_txt = gui_app.texture("icons_mici/settings/network/cell_strength_low.png", 60, 40)
+    self._cell_medium_txt = gui_app.texture("icons_mici/settings/network/cell_strength_medium.png", 60, 40)
+    self._cell_high_txt = gui_app.texture("icons_mici/settings/network/cell_strength_high.png", 60, 40)
+    self._cell_full_txt = gui_app.texture("icons_mici/settings/network/cell_strength_full.png", 60, 40)
 
   def _update_state(self):
     device_state = ui_state.sm['deviceState']
@@ -139,8 +134,10 @@ class MiciHomeLayout(Widget):
     self._version_text = self._get_version_text()
 
     self._experimental_icon = IconWidget("icons_mici/experimental_mode.png", (48, 48))
-    self._egpu_icon = IconWidget("icons_mici/egpu_green.png", (50, 37))
-    self._egpu_icon_gray = IconWidget("icons_mici/egpu_gray.png", (50, 37))
+    self._usb_icon = IconWidget("icons_mici/usb.png", (62, 40))
+    self._chestnut_icon = IconWidget("icons_mici/chestnut_green.png", (54, 40))
+    self._chestnut_loading_icon = IconWidget("icons_mici/chestnut.png", (68, 40))
+    self._chestnut_failed_icon = IconWidget("icons_mici/chestnut_orange.png", (68, 40))
     self._mic_icon = IconWidget("icons_mici/microphone.png", (32, 46))
     self._body_icon = IconWidget("icons_mici/body.png", (54, 37))
 
@@ -150,13 +147,15 @@ class MiciHomeLayout(Widget):
       IconWidget("icons_mici/settings.png", (48, 48), opacity=0.9),
       NetworkIcon(),
       self._experimental_icon,
-      self._egpu_icon,
-      self._egpu_icon_gray,
+      self._usb_icon,
+      self._chestnut_icon,
+      self._chestnut_loading_icon,
+      self._chestnut_failed_icon,
       self._body_icon,
       self._mic_icon,
     ], spacing=18)
 
-    self._openpilot_label = UnifiedLabel("sunnypilot", font_size=96, font_weight=FontWeight.DISPLAY, max_width=480, wrap_text=False)
+    self._openpilot_label = UnifiedLabel("openpilot", font_size=96, font_weight=FontWeight.DISPLAY, max_width=480, wrap_text=False)
     self._version_label = UnifiedLabel("", font_size=36, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
     self._large_version_label = UnifiedLabel("", font_size=64, text_color=rl.GRAY, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
     self._date_label = UnifiedLabel("", font_size=36, text_color=rl.GRAY, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
@@ -182,11 +181,11 @@ class MiciHomeLayout(Widget):
 
   def set_callbacks(self, on_settings: Callable | None = None, on_alerts: Callable | None = None,
                     alert_count_callback: Callable[[], int] | None = None,
-                    max_severity_callback: Callable[[], int | None] | None = None):
+                    alert_icon_callback: Callable[[], rl.Texture | None] | None = None):
     self._on_settings_click = on_settings
     self._on_alerts_click = on_alerts
     self._alert_count_callback = alert_count_callback
-    self._alerts_pill.set_alert_count_callback(alert_count_callback, max_severity_callback)
+    self._alerts_pill.set_alert_count_callback(alert_count_callback, alert_icon_callback)
 
   def _handle_mouse_release(self, mouse_pos: MousePos):
     if not self._did_long_press:
@@ -247,9 +246,20 @@ class MiciHomeLayout(Widget):
         self._version_commit_label.render()
 
     # ***** Center-aligned bottom section icons *****
+    usb_connected = ui_state.usb_connected
+    usb_unknown = ui_state.usb_unknown
+    chestnut_state = ui_state.chestnut_state
     self._experimental_icon.set_visible(ui_state.experimental_mode)
-    self._egpu_icon.set_visible(ui_state.sm["deviceState"].chestnutPresent and ui_state.usbgpu_compiled)
-    self._egpu_icon_gray.set_visible(ui_state.sm["deviceState"].chestnutPresent and not ui_state.usbgpu_compiled)
+    if gui_app.sunnypilot_ui():
+      self._set_chestnut_visibility()
+    else:
+      self._usb_icon.set_visible(usb_connected and usb_unknown)
+      self._chestnut_icon.set_visible(not usb_unknown and chestnut_state not in
+                                      (ChestnutState.LOADING, ChestnutState.UNCOMPILED, ChestnutState.FAILED) and
+                                      (usb_connected or chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE)))
+      self._chestnut_loading_icon.set_visible(not usb_unknown and chestnut_state == ChestnutState.LOADING)
+      self._chestnut_loading_icon.set_opacity(0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0)))
+      self._chestnut_failed_icon.set_visible(not usb_unknown and chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
     self._mic_icon.set_visible(ui_state.recording_audio)
     self._body_icon.set_visible(bool(ui_state.is_body))