hard code?

Update longcontrol.py

smooth

.gitattributes

@@ -1,10 +1,8 @@
-* text=auto eol=lf
+* text=auto
 
 # 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/workflows/build-all-tinygrad-models.yaml

@@ -41,7 +41,6 @@ jobs:
         with:
           path: sunnypilot
           submodules: recursive
-          fetch-depth: 1
 
       - name: Get tinygrad_repo ref
         id: get-tinygrad-ref
@@ -59,7 +58,6 @@ jobs:
           ref: gh-pages
           path: docs
           ssh-key: ${{ secrets.CI_SUNNYPILOT_DOCS_PRIVATE_KEY }}
-          fetch-depth: 1
 
       - name: Get next JSON version to use (from GitHub docs repo)
         id: get-json

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

@@ -46,8 +46,8 @@ jobs:
 
           if [ "${{ inputs.target }}" = "big" ]; then
             NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
+            ONNX_PATH="openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
             HF_DEFAULTS_PATH="models/defaults/big"
-            ONNX_PATH="openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl"
           elif [ "${{ inputs.target }}" = "dm" ]; then
             ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
             HF_DEFAULTS_PATH="models/defaults/dm"
@@ -57,9 +57,8 @@ jobs:
             ONNX_PATH="openpilot/selfdrive/modeld/models/driving_supercombo.onnx"
             HF_DEFAULTS_PATH="models/defaults/small"
           fi
-          ONNX_REF=""
-          [ -n "$ONNX_PATH" ] && ONNX_REF=$(git log -1 --format='%H' -- "$ONNX_PATH")
 
+          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"
@@ -79,8 +78,6 @@ jobs:
     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:
@@ -88,10 +85,9 @@ jobs:
         with:
           submodules: recursive
 
-      - name: Pull small ONNX via LFS
+      - name: Pull ONNX via LFS
         run: git lfs pull -I "${{ env.SMALL_ONNX }}"
 
-
       - name: Set environment variables
         run: |
           source /etc/profile
@@ -107,15 +103,38 @@ jobs:
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
 
-      - name: Compile small model from ONNX
+      - name: Compile small model with stock compiler
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          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}')")
+          FRAME_SKIP=$(python3 -c "from openpilot.selfdrive.modeld.constants import ModelConstants as MC; print(MC.MODEL_RUN_FREQ // MC.MODEL_CONTEXT_FREQ)")
+
           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
+
+          env ${TG_FLAGS} python3 \
+            ${{ github.workspace }}/openpilot/selfdrive/modeld/compile_modeld.py \
+            --onnx ${{ github.workspace }}/${{ env.SMALL_ONNX }} \
+            --model-size $MODEL_SIZE \
+            --camera-resolutions $CAMERA_RES \
+            --frame-skip $FRAME_SKIP \
+            --output ${{ github.workspace }}/${{ env.SMALL_PKL }}
+
+      - 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:
@@ -128,16 +147,14 @@ jobs:
           PKL_BASE="driving_tinygrad.pkl"
           mkdir -p "$OUTPUT_DIR"
 
-          cp "$MODELS_DIR/${PKL_BASE}" "$OUTPUT_DIR/"
-
-          ONNX_SHA256=$(git cat-file blob "$(git ls-files -s "${{ github.workspace }}/${{ env.SMALL_ONNX }}" | awk '{print $2}')" | grep '^oid sha256:' | cut -d: -f2)
+          cp "$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 "${{ needs.resolve.outputs.onnx_ref }}" \
-            --onnx-sha256 "$ONNX_SHA256"
+            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
 
           echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
 
@@ -164,16 +181,15 @@ jobs:
     if: ${{ inputs.target == 'big' }}
     runs-on: [self-hosted, chestnut]
     env:
-      MODELS_DIR: openpilot/selfdrive/modeld/models
-      COMPILER: tinygrad_repo/examples/openpilot
+      BIG_ONNX: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
       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 "${{ env.BIG_PKL }}"
+      - name: Pull big ONNX via LFS
+        run: git lfs pull -I "${{ env.BIG_ONNX }}"
 
       - name: Set environment variables
         run: |
@@ -206,33 +222,38 @@ jobs:
               raise RuntimeError('Chestnut PCIe link not ready after 10 attempts')
           "
 
-      - name: Compile big warp
+      - name: Compile big model with stock compiler
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
 
-          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"
-          COMPILER="${{ github.workspace }}/tinygrad_repo/examples/openpilot"
-          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/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}')")
+          FRAME_SKIP=$(python3 -c "from openpilot.selfdrive.modeld.constants import ModelConstants as MC; print(MC.MODEL_RUN_FREQ // MC.MODEL_CONTEXT_FREQ)")
 
-          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}/big_driving_warp_${res}_tinygrad.pkl"
-            env ${CHESTNUT_TG_FLAGS} python3 "${COMPILER}/compile_warp.py" \
-              --frame ${CAM_W},${CAM_H},${STRIDE_INFO} \
-              --warp-to ${MODEL_SIZE} \
-              --layout yuv420 \
-              --frames 2 \
-              --output "${WARP_PKL}"
-          done
+          TG_FLAGS="DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
+
+          env ${TG_FLAGS} python3 \
+            ${{ github.workspace }}/openpilot/selfdrive/modeld/compile_modeld.py \
+            --onnx ${{ github.workspace }}/${{ env.BIG_ONNX }} \
+            --model-size $MODEL_SIZE \
+            --camera-resolutions $CAMERA_RES \
+            --frame-skip $FRAME_SKIP \
+            --output ${{ github.workspace }}/${{ env.BIG_PKL }}
+
+      - 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:
@@ -245,18 +266,14 @@ jobs:
           PKL_BASE="big_driving_tinygrad.pkl"
           mkdir -p "$OUTPUT_DIR"
 
-          cp "$MODELS_DIR/${PKL_BASE}" "$OUTPUT_DIR/"
-
-          PKL_LFS_SHA256=$(git cat-file blob "$(git ls-files -s "${{ github.workspace }}/${{ env.BIG_PKL }}" | awk '{print $2}')" | grep '^oid sha256:' | cut -d: -f2)
+          cp "$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 "${{ needs.resolve.outputs.onnx_ref }}" \
-            --onnx-sha256 "$PKL_LFS_SHA256"
-
-          cp "$MODELS_DIR"/big_driving_warp_* "$OUTPUT_DIR/" || true
+            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
 
           echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
 
@@ -294,8 +311,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Pull LFS for resolved ONNX files
-        if: ${{ needs.resolve.outputs.onnx_path != '' }}
+      - name: Pull ONNX via LFS
         run: git lfs pull -I "${{ needs.resolve.outputs.onnx_path }}"
 
       - name: Install huggingface_hub
@@ -360,28 +376,38 @@ jobs:
           from datetime import datetime, UTC
 
           dm_dir = Path('dm_output')
-          matches = sorted(dm_dir.glob('dmonitoring_*_tinygrad.pkl'))
-          assert len(matches) == 1, f'expected one DM pkl in {dm_dir}, found {matches}'
-          pkl_name = matches[0].name
+          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()
-          with open(dm_dir / pkl_name, 'rb') as f:
-              while block := f.read(1024*1024):
-                  digest.update(block)
+          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 }}',
-                  'tinygrad_ref': '${{ needs.resolve.outputs.tinygrad_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()}
+                          'download_uri': {'url': '', 'sha256': digest.hexdigest()},
+                          'chunks': chunks
                       }
                   }]
               }]
@@ -444,39 +470,42 @@ jobs:
             ${{ github.workspace }}/${{ 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"
+          MODEL_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld"
           DM_SIZE=$(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},${STRIDE_INFO} \
+            WARP_PKL="${MODEL_DIR}/models/dm_warp_${res}_tinygrad.pkl"
+            taskset -c 7 env ${TG_FLAGS} python3 ${MODEL_DIR}/compile_dm_warp.py \
+              --camera-resolution ${res} \
               --warp-to ${DM_SIZE} \
-              --layout luma \
-              --border-fill 16 \
-              --transform-device NPY \
-              --output "${WARP_PKL}"
+              --output ${WARP_PKL}
           done
 
       - name: Prepare DM output
         run: |
           mkdir -p dm_output
-          cp ${{ github.workspace }}/${{ env.DM_PKL }} 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
@@ -490,3 +519,4 @@ jobs:
         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

@@ -134,10 +134,12 @@ jobs:
 
   publish_model:
     if: ${{ !cancelled() && needs.build_model.result == 'success' }}
+    concurrency:
+      group: hf-push-${{ inputs.recompiled_dir }}
+      cancel-in-progress: false
     needs: build_model
     runs-on: ubuntu-latest
     permissions:
-      actions: read
       id-token: write
       contents: write
     steps:
@@ -180,21 +182,18 @@ jobs:
           echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
 
       - name: Download and extract model artifact
-        env:
-          GH_TOKEN: ${{ github.token }}
-          ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
-        run: |
-          id=$(gh api -X GET "repos/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID/artifacts" -f name="$ARTIFACT_NAME" --jq '.artifacts[0].id')
-          url=$(curl -sf -o /dev/null -w '%{redirect_url}' -H "Authorization: Bearer $GH_TOKEN" "https://api.github.com/repos/$GITHUB_REPOSITORY/actions/artifacts/$id/zip")
-          sudo apt-get install -y -qq aria2 > /dev/null
-          aria2c -q -x16 -s16 -k8M --max-tries=5 --file-allocation=none -o model.zip "$url" && unzip -q model.zip -d output && rm model.zip
+        uses: actions/download-artifact@v4
+        with:
+          name: ${{ steps.read-artifact-name.outputs.artifact_name }}
+          path: output
 
       - name: Create models folder
         env:
           ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
         run: |
           mkdir -p "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}"
-          cp output/metadata.json "local_models/${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: Upload to Hugging Face
         env:
@@ -206,12 +205,13 @@ jobs:
             "models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/" \
             --repo-type=dataset
 
-      - name: Update and push JSON to docs repo
+      - name: Pull gh-pages
         run: |
           cd docs
-          git config --global user.name "GitHub Action"
-          git config --global user.email "action@github.com"
+          git pull origin gh-pages
 
+      - name: Run json_parser.py to update JSON
+        run: |
           FOLDER="${{ inputs.model_folder }}"
           if [ "$FOLDER" = "Other" ]; then
             FOLDER="${{ inputs.custom_model_folder }}"
@@ -224,27 +224,18 @@ jobs:
           [ -n "${{ 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 "$JSON_FILE" \
+            --recompiled-dir "local_models/$RECOMPILED_DIR" \
+            --sort-by-date \
+            $ARGS
 
-          for attempt in $(seq 1 10); do
-            git fetch origin gh-pages
-            git reset --hard origin/gh-pages
-
-            eval python3 json_parser.py \
-              --json-path "docs/$(basename $JSON_FILE)" \
-              --recompiled-dir "../local_models/$RECOMPILED_DIR" \
-              --sort-by-date \
-              $ARGS
-
-            git add docs/"$(basename $JSON_FILE)"
-            git commit -m "Update $(basename $JSON_FILE) after recompiling model" || { echo "No changes to commit"; exit 0; }
-
-            if git push origin gh-pages; then
-              echo "Push succeeded on attempt $attempt"
-              exit 0
-            fi
-
-            echo "Push failed (attempt $attempt/10), retrying after backoff..."
-            sleep $((RANDOM % 10 + 3))
-          done
-          echo "All 10 push attempts failed"
-          exit 1
+      - name: Push updated JSON to GitHub docs repo
+        run: |
+          cd docs
+          git config --global user.name "GitHub Action"
+          git config --global user.email "action@github.com"
+          git checkout gh-pages
+          git add docs/"$(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/compile-warp-kernels.yaml

@@ -1,71 +0,0 @@
-name: Compile warp for sunnypilot modeld
-
-on:
-  workflow_dispatch:
-
-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 $CAMERA_RES; do
-            FRAME_PARAM=$(python3 -c "from openpilot.system.camerad.cameras.nv12_info import get_nv12_info; w, h = map(int, '${res}'.split('x')); stride, y_h, uv_h, _ = get_nv12_info(w, h); print(f'{w},{h},{stride},{y_h},{uv_h},{stride * (y_h + uv_h)}')")
-
-            WARP_PKL="openpilot/sunnypilot/modeld_v2/models/driving_warp_${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 openpilot/sunnypilot/modeld_v2/compile_warp.py \
-              --frame ${FRAME_PARAM} --warp-to ${MODEL_SIZE} --output "${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 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32 python3 openpilot/sunnypilot/modeld_v2/compile_warp.py \
-              --frame ${FRAME_PARAM} --warp-to ${MODEL_SIZE} --output "${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

@@ -18,25 +18,24 @@ concurrency:
 env:
   GIT_CONFIG_COUNT: 1
   GIT_CONFIG_KEY_0: lfs.fetchexclude
-  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
 
 jobs:
   docs:
     name: build docs
-    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"]') }}
+    runs-on: ubuntu-24.04
     steps:
     - uses: commaai/timeout@v1
+
     - uses: actions/checkout@v7
-    - run: ./tools/op.sh setup
+      with:
+        submodules: true
 
     # Build
     - name: Build docs
-      run: ./tools/op.sh docs --build
+      run: |
+        git lfs pull
+        python docs/serve.py --build
 
     # Push to docs.comma.ai
     - uses: actions/checkout@v7

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

@@ -1,5 +1,5 @@
-name: Download HF model
-description: Resolve and download models from HuggingFace in parallel
+name: Download HF model chunks
+description: Resolve and download model chunks from HuggingFace in parallel
 
 inputs:
   hf_repo:
@@ -11,21 +11,16 @@ inputs:
   dest_dir:
     description: Destination directory for downloaded chunks
     required: true
-  tinygrad_ref:
-    description: 'Tinygrad ref to match bundle against'
-    required: false
-    default: ''
 
 runs:
   using: composite
   steps:
-    - name: Download models
+    - name: Download model chunks
       shell: bash
       env:
         HF_REPO: ${{ inputs.hf_repo }}
         MODELS_JSON: ${{ inputs.models }}
         DEST_DIR: ${{ inputs.dest_dir }}
-        TINYGRAD_REF: ${{ inputs.tinygrad_ref }}
       run: |
         set -eo pipefail
         DOWNLOAD_LIST=$(mktemp)
@@ -33,41 +28,30 @@ runs:
         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/${HF_PATH}/default_models.json"
-          local DEFAULTS BUNDLE ARTIFACT FILE_URL BASE_URL
+          local DEFAULTS BUNDLE ARTIFACT BASE_URL NUM_CHUNKS
           DEFAULTS=$(curl -fsSL "$JSON_URL")
-          if [ -n "$TINYGRAD_REF" ]; then
-            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" --arg tg "$TINYGRAD_REF" '
-              . as $root | [.bundles[] | select(.onnx_sha256 == $hash and (.tinygrad_ref == $tg or (.tinygrad_ref == null and $root.tinygrad_ref == $tg)))] | .[0] // empty
-            ')
-          else
-            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '
-              [.bundles[] | select(.onnx_sha256 == $hash)] | .[0] // empty
-            ')
-          fi
-
-          if [ -z "$BUNDLE" ] || [ "$BUNDLE" = "null" ]; then
-            echo "::error::No model bundle found matching ONNX hash $ONNX_HASH (tinygrad ref: $TINYGRAD_REF) in $HF_PATH"
-            return 1
-          fi
-
+          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
           ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
-          FILE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url')
-          BASE_URL=$(echo "$FILE_URL" | sed 's|/[^/]*$||')
+          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
+          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
 
           mkdir -p "$DEST_DIR"
-          ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${FILE_URL}', safe=':/'))")
-          printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${CANONICAL}" >> "$DOWNLOAD_LIST"
+          while IFS= read -r CHUNK_NAME; do
+            CHUNK_IDX=$(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
-          elif [ "$CANONICAL" = "big_driving_tinygrad.pkl" ]; then
-            for warp in big_driving_warp_1928x1208_tinygrad.pkl big_driving_warp_1344x760_tinygrad.pkl; do
-              ENCODED_URL=$(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
         }
 
@@ -79,7 +63,7 @@ runs:
         done
 
         TOTAL=$(wc -l < "$DOWNLOAD_LIST")
-        echo "Downloading $TOTAL files with 8 parallel connections..."
+        echo "Downloading $TOTAL chunks with 8 parallel connections..."
         xargs -P8 -d'\n' -I{} bash -c '
           URL="${1%%	*}"
           DEST="${1#*	}"

.github/workflows/lfs-maintenance.yaml

@@ -1,8 +1,8 @@
 name: Sync comma's LFS
 
 env:
-  LFS_URL: 'https://huggingface.co/sunnypilot/sunnypilot-lfs.git/info/lfs'
-  LFS_PUSH_URL: 'https://huggingface.co/sunnypilot/sunnypilot-lfs.git/info/lfs'
+  LFS_URL: 'https://gitlab.com/sunnypilot/public/sunnypilot-new-lfs.git/info/lfs'
+  LFS_PUSH_URL: 'ssh://git@gitlab.com/sunnypilot/public/sunnypilot-new-lfs.git'
 
 on:
   schedule:
@@ -40,12 +40,14 @@ jobs:
           git config --global user.name 'GitHub Action'
           git config --global user.email 'action@github.com'
 
-      - name: Setup hf
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+      - name: Set up SSH
+        uses: webfactory/ssh-agent@v0.9.0
+        with:
+          ssh-private-key: ${{ secrets.SSH_PRIVATE_KEY }}
+
+      - name: Add GitLab public keys
         run: |
-          git config --global credential.helper store
-          echo "https://user:${HF_TOKEN}@huggingface.co" > ~/.git-credentials
+          ssh-keyscan -H gitlab.com >> ~/.ssh/known_hosts
 
       - name: Ensure branch
         run: |

.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_tinygrad.pkl
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
 
 jobs:
   build___nightly:
@@ -34,7 +34,3 @@ 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_tinygrad.pkl
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
 
 jobs:
   package_updates:

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

@@ -100,56 +100,24 @@ jobs:
           commit_date=$(git log -1 --format=%cd --date=format:'%B %d, %Y')
           echo "model_date=${commit_date}" >> $GITHUB_OUTPUT
           cat $GITHUB_OUTPUT
-
-      - name: Fetch Models
-        run: |
+      - run: |
           cd ${{ github.workspace }}/openpilot/openpilot
-          fetch_lfs() {
-            sudo apt-get install -y -qq aria2 > /dev/null # Parallel ranges because gh is flaky
-            LFS_URL=$(git config -f "$(git rev-parse --show-toplevel)/.lfsconfig" lfs.url)
-            for f in "$@"; do
-              grep -qs "^version https://git-lfs" "$f" || continue
-              OID=$(awk -F'sha256:' '/^oid/{print $2}' "$f"); SIZE=$(awk '/^size/{print $2}' "$f")
-              HREF=$(curl -fsSL --retry 3 -X POST -H "Accept: application/vnd.git-lfs+json" -H "Content-Type: application/vnd.git-lfs+json" "$LFS_URL/objects/batch" \
-                -d "{\"operation\":\"download\",\"transfer\":[\"basic\"],\"objects\":[{\"oid\":\"$OID\",\"size\":$SIZE}]}" | jq -r '.objects[0].actions.download.href')
-              aria2c -x 16 -s 16 -k 16M --max-tries=5 --retry-wait=5 --file-allocation=none --summary-interval=30 --allow-overwrite=true \
-                -d "$(dirname "$f")" -o "$(basename "$f")" "$HREF"
-              echo "$OID  $f" | sha256sum -c -
-            done
-          }
-          UPSTREAM_PKL=selfdrive/modeld/models/big_driving_tinygrad.pkl
           if [ "${{ 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
-          elif compgen -G "selfdrive/modeld/models/big_*.onnx" > /dev/null; then
-            fetch_lfs selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/big_*.pkl
-            find selfdrive/modeld/models -type f \( -name "*.onnx" -o -name "*.pkl" \) ! -name "big_*.onnx" ! -name "big_*.pkl" -delete
-          elif [ -f "$UPSTREAM_PKL" ]; then
-            echo "No big model ONNX tracked: converting commaai's precompiled $UPSTREAM_PKL, with the tinygrad it was built with"
-            fetch_lfs "$UPSTREAM_PKL"
-            find selfdrive/modeld/models -type f \( -name "*.onnx" -o -name "*.pkl" \) ! -path "$UPSTREAM_PKL" -delete
-            GITMODULES="$(git rev-parse --show-toplevel)/.gitmodules"
-            TG_NAME=$(git config -f "$GITMODULES" --get-regexp '^submodule\..*\.path$' | awk '$2 == "tinygrad_repo" {sub(/^submodule\./, "", $1); sub(/\.path$/, "", $1); print $1}')
-            TG_URL=$(git config -f "$GITMODULES" "submodule.$TG_NAME.url" | sed 's|^\.\./\.\./|https://github.com/|')
-            echo "$TG_URL $(git rev-parse HEAD:tinygrad_repo) $(sha256sum "$UPSTREAM_PKL" | cut -d' ' -f1)" > selfdrive/modeld/models/upstream_pkl.txt
+            git lfs pull -X "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/dmonitoring_*.onnx"
+            rm -f selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/dmonitoring_*.onnx
           else
-            echo "::error::no big model ONNX or precompiled big_driving_tinygrad.pkl at this ref"
-            exit 1
+            git lfs pull -I "**/selfdrive/modeld/models/big_*.onnx" -X ""
+            find selfdrive/modeld/models -name "*.onnx" ! -name "big_*.onnx" -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"
+          if grep -lIF "version https://git-lfs.github.com/spec/v1" selfdrive/modeld/models/*.onnx; then
+            echo "::error::the ONNX 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  }}
-          compression-level: 0
-          path: |
-            ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
-            ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.pkl
-            ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/upstream_pkl.txt
+          path: ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
           if-no-files-found: error
 
   build_model:
@@ -164,6 +132,7 @@ jobs:
           fetch-depth: 1
           submodules: recursive
 
+
       - name: Set environment variables
         id: set-env
         run: |
@@ -175,6 +144,9 @@ jobs:
           export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
           uv sync --frozen
           printenv >> $GITHUB_ENV
+          if [[ "${{ runner.debug }}" == "1" ]]; then
+            cat $GITHUB_OUTPUT
+          fi
 
       - name: Setup build environment
         run: |
@@ -186,6 +158,10 @@ jobs:
           echo "VERSION: ${{ steps.set-env.outputs.version }}"
           echo "UV_PROJECT_ENVIRONMENT: ${UV_PROJECT_ENVIRONMENT}"
           echo "VIRTUAL_ENV: ${VIRTUAL_ENV}"
+          echo "-------"
+          if [[ "${{ runner.debug }}" == "1" ]]; then
+            printenv
+          fi
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
           rm -rf ${{ env.MODELS_DIR }}/*.onnx*
@@ -208,11 +184,11 @@ jobs:
           MODEL_SIZE=$(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}')")
 
-          TG_FLAGS_QCOM="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 OPENPILOT_HACKS=1"
+          TG_FLAGS_QCOM="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
           if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
             echo "CHESTNUT build"
             export CHESTNUT=1
-            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32"
+            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1"
             OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
           else
             echo "QCOM build"
@@ -220,77 +196,64 @@ jobs:
             OUTPUT_PKL="${{ env.MODELS_DIR }}/driving_tinygrad.pkl"
           fi
 
-          NATIVE_PKL=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "*.pkl" -print -quit)
+          # 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
 
-          if [ -f "${{ env.MODELS_DIR }}/upstream_pkl.txt" ]; then
-            read -r TG_URL TG_SHA _ < "${{ env.MODELS_DIR }}/upstream_pkl.txt"
-            echo "Converting commaai's precompiled model with tinygrad $TG_SHA"
-            UPSTREAM_TG="${{ runner.temp }}/upstream_tinygrad"
-            rm -rf "$UPSTREAM_TG" && git init -q "$UPSTREAM_TG" && git -C "$UPSTREAM_TG" fetch -q --depth 1 "$TG_URL" "$TG_SHA" && git -C "$UPSTREAM_TG" checkout -q FETCH_HEAD
-            CONVERTED="${{ runner.temp }}/big_driving_tinygrad_plain.pkl"
-            env DEV=USB+AMD PYTHONPATH="$UPSTREAM_TG:${{ github.workspace }}" taskset -c 7 python3 openpilot/sunnypilot/modeld_v2/convert_upstream_pkl.py \
-              "${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl" "$CONVERTED"
-            mv "$CONVERTED" "$OUTPUT_PKL"
-          elif NEW_ARCH_ONNX=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "${{ inputs.target_hardware == 'chestnut' && 'big_' || '' }}*driving*.onnx" -print -quit) &&
-               [ -n "$NEW_ARCH_ONNX" ] && grep -qa new_img "$NEW_ARCH_ONNX"; then # the new architecture: one ONNX taking the warped frames as new_img
-            echo "Compiling new architecture ONNX: $NEW_ARCH_ONNX"
-            env ${TG_FLAGS} taskset -c 7 python3 openpilot/sunnypilot/modeld_v2/compile_modeld_v2.py \
-              "$NEW_ARCH_ONNX" "$OUTPUT_PKL" --device-input "*" --benchmark-runs 1
-          else
-            echo "Detected onnx architecture. Routing to native compile_modeld.py."
-            # Detect model type and build compile args
-            VISION_ONNX=""
-            for f in "${{ env.MODELS_DIR }}/driving_vision.onnx" "${{ env.MODELS_DIR }}/big_driving_vision.onnx"; do
-              [ -f "$f" ] && VISION_ONNX="$f" && break
-            done
+          # Detect model type and build compile args
+          VISION_ONNX=""
+          for f in "${{ 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
+          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
+          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
+          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
+          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 $SUPERCOMBO_ONNX"
+          MODEL_TYPE="" ONNX_ARGS="" OUTPUT_NAME=""
+          if [ -f "$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
 
-            if [ -n "$MODEL_TYPE" ]; then
-              echo "Detected: $MODEL_TYPE -> $OUTPUT_PKL"
-              env ${TG_FLAGS} taskset -c 7 python3 "$COMPILE_MODELD" \
-                --model-type $MODEL_TYPE \
-                --model-size $MODEL_SIZE \
-                --camera-resolutions $CAMERA_RES \
-                $ONNX_ARGS \
-                --output "$OUTPUT_PKL"
-            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"
           fi
 
       - name: Prepare Output
@@ -301,7 +264,8 @@ jobs:
           # Copy the model files
           rsync -avm \
             --include='*.dlc' \
-            --include='/${{ inputs.target_hardware == 'chestnut' && 'big_' || '' }}driving_tinygrad.pkl' \
+            --include='*.chunk*' \
+            --include='*.chunkmanifest' \
             --exclude='*' \
             --delete-excluded \
             --chown=comma:comma \
@@ -312,7 +276,6 @@ jobs:
             --output-dir "${{ env.OUTPUT_DIR }}" \
             --custom-name "${{ env.MODEL_NAME }}" \
             --upstream-branch "${{ inputs.upstream_branch }}" \
-            $([ -f "${{ env.MODELS_DIR }}/upstream_pkl.txt" ] && echo "--onnx-sha256 $(cut -d' ' -f3 "${{ env.MODELS_DIR }}/upstream_pkl.txt")") \
             ${{ inputs.is_20hz && '--is-20hz' || '' }}
 
       - name: Write artifact name to file
@@ -324,7 +287,6 @@ jobs:
         with:
           name: model-${{ env.MODEL_NAME }}${{ inputs.artifact_suffix }}-${{ github.run_number }}
           path: ${{ env.OUTPUT_DIR }}
-          compression-level: 0
 
       - name: Upload artifact name file
         uses: actions/upload-artifact@v4

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

@@ -170,9 +170,6 @@ jobs:
           scons -j1 cache_dir="$SCONS_CACHE" --minimal \
             openpilot/selfdrive/locationd openpilot/sunnypilot/selfdrive/locationd
           echo "Building rest of sunnypilot"
-          sudo rm -rf /tmp/* || true
-          mkdir -p "$BUILD_DIR/tmp"
-          export TMPDIR="$BUILD_DIR/tmp"
           SKIP_TINYGRAD_COMPILE=1 /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
           touch ${BUILD_DIR}/prebuilt
           if [[ "${{ runner.debug }}" == "1" ]]; then
@@ -224,40 +221,37 @@ jobs:
       cancel-in-progress: false
     outputs:
       onnx_sha256: ${{ steps.resolve.outputs.onnx_sha256 }}
-      tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
     env:
       GH_REPO: ${{ github.repository }}
       HF_REPO: sunnypilot/sunnypilot_models_v1
       HF_DEFAULTS_PATH: models/defaults/big
     steps:
-      - name: Resolve tinygrad ref via API
+      - name: Resolve ONNX hash and tinygrad ref via API
         id: resolve
         run: |
           REF="${{ 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; }
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx?ref=${REF}" --jq '.sha')
           ONNX_HASH=$(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; }
-          echo "onnx_sha256=$ONNX_HASH" >> "$GITHUB_OUTPUT"
+          echo "ONNX hash: $ONNX_HASH"
+          [ -n "$ONNX_HASH" ] || { echo "::error::Failed to extract ONNX hash"; exit 1; }
+          echo "onnx_sha256=$ONNX_HASH" >> $GITHUB_OUTPUT
 
           TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
           echo "tinygrad ref: $TINYGRAD_REF"
-          echo "tinygrad_ref=$TINYGRAD_REF" >> "$GITHUB_OUTPUT"
 
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
             DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
-            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" --arg ref "$TINYGRAD_REF" '
-              . as $root | [.bundles[] | select(.onnx_sha256 == $hash and (.tinygrad_ref == $ref or (.tinygrad_ref == null and $root.tinygrad_ref == $ref)))] | .[0] // empty
-            ' 2>/dev/null)
+            TINYGRAD_MATCH=$(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"
+            echo "HF defaults match repo ONNX hash and tinygrad ref"
             exit 0
           fi
 
@@ -310,13 +304,12 @@ jobs:
       cancel-in-progress: false
     outputs:
       driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
-      tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
     env:
       GH_REPO: ${{ github.repository }}
       HF_REPO: sunnypilot/sunnypilot_models_v1
       HF_DEFAULTS_PATH: models/defaults/small
     steps:
-      - name: Resolve tinygrad ref via API
+      - name: Resolve ONNX hash and tinygrad ref via API
         id: resolve
         run: |
           REF="${{ github.head_ref || github.ref_name }}"
@@ -325,24 +318,23 @@ jobs:
           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; }
-          echo "driving_onnx_sha256=$DRIVING_HASH" >> "$GITHUB_OUTPUT"
+          echo "driving_onnx_sha256=$DRIVING_HASH" >> $GITHUB_OUTPUT
 
           TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
           echo "tinygrad ref: $TINYGRAD_REF"
-          echo "tinygrad_ref=$TINYGRAD_REF" >> "$GITHUB_OUTPUT"
 
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
             DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
-            DRIVING=$(echo "$DEFAULTS" | jq --arg hash "$DRIVING_HASH" --arg ref "$TINYGRAD_REF" '
-              . as $root | [.bundles[] | select(.onnx_sha256 == $hash and (.tinygrad_ref == $ref or (.tinygrad_ref == null and $root.tinygrad_ref == $ref)))] | .[0] // empty
-            ' 2>/dev/null)
-            [ -n "$DRIVING" ] && [ "$DRIVING" != "null" ]
+            TINYGRAD_MATCH=$(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"
+            echo "HF defaults match repo ONNX hash and tinygrad ref"
             exit 0
           fi
 
@@ -395,13 +387,12 @@ jobs:
       cancel-in-progress: false
     outputs:
       dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
-      tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
     env:
       GH_REPO: ${{ github.repository }}
       HF_REPO: sunnypilot/sunnypilot_models_v1
       HF_DEFAULTS_PATH: models/defaults/dm
     steps:
-      - name: Resolve tinygrad ref via API
+      - name: Resolve ONNX hash and tinygrad ref via API
         id: resolve
         run: |
           REF="${{ github.head_ref || github.ref_name }}"
@@ -410,24 +401,23 @@ jobs:
           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; }
-          echo "dm_onnx_sha256=$DM_HASH" >> "$GITHUB_OUTPUT"
+          echo "dm_onnx_sha256=$DM_HASH" >> $GITHUB_OUTPUT
 
           TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
           echo "tinygrad ref: $TINYGRAD_REF"
-          echo "tinygrad_ref=$TINYGRAD_REF" >> "$GITHUB_OUTPUT"
 
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
             DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
-            DM=$(echo "$DEFAULTS" | jq --arg hash "$DM_HASH" --arg ref "$TINYGRAD_REF" '
-              . as $root | [.bundles[] | select(.onnx_sha256 == $hash and (.tinygrad_ref == $ref or (.tinygrad_ref == null and $root.tinygrad_ref == $ref)))] | .[0] // empty
-            ' 2>/dev/null)
-            [ -n "$DM" ] && [ "$DM" != "null" ]
+            TINYGRAD_MATCH=$(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"
+            echo "HF defaults match DM ONNX hash and tinygrad ref"
             exit 0
           fi
 
@@ -503,12 +493,11 @@ jobs:
           mkdir -p ${{ env.OUTPUT_DIR }}
           tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
 
-      - name: Download models from HF
-        uses: ./.github/workflows/download-hf-model
+      - 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
-          tinygrad_ref: ${{ needs.prepare_dm_model.outputs.tinygrad_ref }}
           models: |
             [
               {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
@@ -573,12 +562,11 @@ jobs:
           mkdir -p ${{ env.OUTPUT_DIR }}
           tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
 
-      - name: Download models from HF
-        uses: ./.github/workflows/download-hf-model
+      - 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
-          tinygrad_ref: ${{ needs.prepare_dm_model.outputs.tinygrad_ref }}
           models: |
             [
               {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},

.github/workflows/test_models.yml

@@ -47,23 +47,33 @@ jobs:
         with:
           submodules: true
 
-      - name: Download model
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
-          MODEL_URL: ${{ matrix.artifact.download_uri.url }}
-          MODEL_FILE: ${{ matrix.artifact.file_name }}
-        shell: bash
+      - name: Download Model Chunks in Parallel
         run: |
-          mkdir -p /tmp/models
-          AUTH=()
-          if [ -n "$HF_TOKEN" ]; then AUTH=(-H "Authorization: Bearer $HF_TOKEN"); fi
-          curl --retry 3 --retry-all-errors -s -S -f -L "${AUTH[@]}" -o "/tmp/models/$MODEL_FILE" "$MODEL_URL"
+          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"]
+          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")
+          '
+          curl -Z --parallel-immediate --parallel-max 16 -s -S -f -L -K /tmp/curl_config.txt
 
       - name: Run Model Compatibility Test
         env:
           MODEL_BASE_NAME: ${{ matrix.artifact.file_name }}
-          MODEL_DIR: "/tmp/models"
+          MODEL_CHUNK_DIR: "/tmp/model_chunks"
+          PYTHONPATH: ".:./tinygrad_repo"
         run: |
-          export PYTHONPATH="$GITHUB_WORKSPACE/tinygrad_repo:$GITHUB_WORKSPACE:$PYTHONPATH"
-          python3 -m pip uninstall -y tinygrad || uv pip uninstall -y tinygrad --system || true
           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_tinygrad.pkl
+  GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
 
 jobs:
   build_release:

.gitignore

@@ -50,8 +50,6 @@ 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

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

.lfsconfig

@@ -1,5 +1,4 @@
 [lfs]
-	url = https://huggingface.co/sunnypilot/sunnypilot-lfs.git/info/lfs
-	pushurl = https://huggingface.co/sunnypilot/sunnypilot-lfs.git/info/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

@@ -12,17 +12,16 @@ 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=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'
+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'
 
 set -e
 
 export TERM=xterm-256color
 
-trap 'kill 0' HUP # stop this process group on SSH disconnect
+shopt -s huponexit # kill all child processes when the shell exits
 
 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}
@@ -70,8 +69,7 @@ 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} ) &
-wait \$!
+time ${cmd}
 END"""
 
     sh script: ssh_cmd, label: step_label
@@ -161,14 +159,6 @@ def step(String name, String cmd, Map args = [:]) {
   return [name, cmd, args]
 }
 
-def chestnutStage(String name = "chestnut") {
-  deviceStage(name, "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]),
-  ])
-}
-
 node {
   env.CI = "1"
   env.PYTHONWARNINGS = "error"
@@ -179,37 +169,7 @@ node {
   env.GIT_BRANCH = checkout(scm).GIT_BRANCH
   env.GIT_COMMIT = checkout(scm).GIT_COMMIT
 
-  if (env.JOB_BASE_NAME == 'chestnut-stresstest') {
-    sh 'git fetch --no-tags origin nightly-chestnut'
-    env.GIT_COMMIT = sh(script: 'git show FETCH_HEAD:git_src_commit', returnStdout: true).trim()
-    if (!(env.GIT_COMMIT ==~ /[0-9a-f]{40}/)) {
-      error("invalid nightly-chestnut source commit")
-    }
-    def results = []
-    try {
-      timeout(time: 12, unit: 'HOURS') {
-        for (int run = 1; run <= 100; run++) {
-          results << "run ${run}: INCOMPLETE"
-          try {
-            chestnutStage("chestnut ${run}/100")
-            results[run - 1] = "run ${run}: PASS"
-          } catch (hudson.AbortException e) {
-            results[run - 1] = "run ${run}: FAIL"
-            echo e.toString()
-          }
-        }
-      }
-    } finally {
-      writeFile file: 'chestnut_stress_report.txt', text: "commit: ${env.GIT_COMMIT}\ncompleted: ${results.count { !it.endsWith('INCOMPLETE') }}/100\n" + results.join('\n') + '\n'
-      archiveArtifacts artifacts: 'chestnut_stress_report.txt'
-    }
-    if (results.any { !it.endsWith('PASS') }) {
-      error("chestnut stress test failed")
-    }
-    return
-  }
-
-  def excludeBranches = ['__nightly', '__nightly-chestnut', 'devel', 'devel-staging',
+  def excludeBranches = ['__nightly', 'devel', 'devel-staging',
                          'release-tizi', 'release-tizi-staging', 'release-mici', 'release-mici-staging', 'testing-closet*', 'hotfix-*']
   def excludeRegex = excludeBranches.join('|').replaceAll('\\*', '.*')
 
@@ -241,21 +201,6 @@ node {
       )
     }
 
-    if (env.BRANCH_NAME == '__nightly-chestnut') {
-      parallel (
-        'nightly-chestnut': {
-          deviceStage("build nightly-chestnut", "mici-chestnut-ci", ["CHESTNUT=1"], [
-            step("build nightly-chestnut", "SCONSFLAGS=-j4 INCLUDE_BIG_MODEL=1 RELEASE_BRANCH=nightly-chestnut $SOURCE_DIR/tools/release/build_release.sh TestChestnutOnroad"),
-          ])
-        },
-        'nightly-chestnut-dev': {
-          deviceStage("build nightly-chestnut-dev", "mici-chestnut-ci", ["CHESTNUT=1"], [
-            step("build nightly-chestnut-dev", "SCONSFLAGS=-j4 INCLUDE_BIG_MODEL=1 PANDA_DEBUG_BUILD=1 RELEASE_BRANCH=nightly-chestnut-dev $SOURCE_DIR/tools/release/build_release.sh TestChestnutOnroad"),
-          ])
-        },
-      )
-    }
-
     if (!env.BRANCH_NAME.matches(excludeRegex)) {
     parallel (
       'onroad tests': {
@@ -307,9 +252,6 @@ node {
           step("test amp", "./openpilot/common/hardware/comma/tests/test_amplifier.py"),
         ])
       },
-      'chestnut': {
-        chestnutStage()
-      },
 
     )
     }

RELEASES.md

@@ -1,14 +1,4 @@
-Version 0.11.3 (2026-XX-XX)
-========================
-* Autospeed
-  * On supported cars, openpilot will intelligently decide what speed to drive based on the scene, including:
-    * stopping at red lights, and going at green lights
-    * slowing down for curves
-    * adjusting speed based on surrounding traffic
-  * This behavior was previously available with openpilot's "Experimental mode", but is now out of beta and always enabled
-  * With openpilot deciding which speed to drive, the car's cruise speed is treated as a maximum speed openpilot will not exceed
-
-Version 0.11.2 (2026-10-14)
+Version 0.11.2 (2026-08-12)
 =======================
 * New driving model
   * Big model with 880M parameters

SConstruct

@@ -20,7 +20,7 @@ SetOption('num_jobs', max(1, int(os.cpu_count()/(1 if "CI" in os.environ else 2)
 
 AddOption('--ccflags', action='store', type='string', default='', help='pass arbitrary flags over the command line')
 AddOption('--verbose', action='store_true', default=False, help='show full build commands')
-release = not os.path.exists(File('#.gitmodules').abspath) # file absent on release branch, see release_files.py
+release = not os.path.exists(File('#.gitattributes').abspath) # file absent on release branch, see release_files.py
 AddOption('--minimal',
           action='store_false',
           dest='extras',
@@ -87,6 +87,7 @@ acados_include_dirs = [
 # vendored in commaai/dependencies.
 allowed_system_libs = {
   "EGL", "GLESv2", "GL",
+  "Qt5Charts", "Qt5Core", "Qt5Gui", "Qt5Widgets",
   "dl", "drm", "gbm", "m", "pthread",
 }
 
@@ -120,7 +121,6 @@ def _libflags(target, source, env, for_signature):
 env = Environment(
   ENV={
     "PATH": os.environ['PATH'],
-    "TMPDIR": os.environ.get('TMPDIR', '/tmp'),
     "PYTHONPATH": os.pathsep.join(submodule_python_paths),
     "ACADOS_SOURCE_DIR": acados.DIR,
     "ACADOS_PYTHON_INTERFACE_PATH": acados.TEMPLATE_DIR,
@@ -316,6 +316,8 @@ def count_scons_nodes(nodes):
     if node in seen:
       continue
     seen.add(node)
+    if hasattr(node, 'has_builder') and node.has_builder():
+      build_product_nodes.add(node)
     executor = node.get_executor()
     if executor is not None:
       stack += executor.get_all_prerequisites() + executor.get_all_children()
@@ -324,6 +326,7 @@ def count_scons_nodes(nodes):
 
 progress_interval = 5
 progress_count = 0
+build_product_nodes = set()
 progress_total = max(1, count_scons_nodes(env.arg2nodes(BUILD_TARGETS or [Dir('.')], env.fs.Entry)))
 
 def progress_function(node):
@@ -339,3 +342,11 @@ def progress_function(node):
 
 Progress(progress_function, interval=progress_interval)
 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 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'):
+  AddPostAction(list(build_product_nodes), Action(check_build_product_size, None))

docs/CARS.md

@@ -34,7 +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>|||
+|CUPRA[<sup>12</sup>](#footnotes)|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 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 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>|||
@@ -99,7 +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 2023-27|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|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|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>|||
@@ -268,8 +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) 2020-24[<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>|||
+|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>|||
 |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>|||
@@ -335,8 +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)|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 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 ID.4 2021-23">Buy Here</a></sub></details>|||
+|Volkswagen[<sup>12</sup>](#footnotes)|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 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 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>|||
@@ -363,7 +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>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>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>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
-op docs --build
+python docs/serve.py --build
 ```
 
 **2. Run the site locally** (rebuilds on change)
 ``` bash
-op docs
+python docs/serve.py
 ```

launch_chffrplus.sh

@@ -18,21 +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 $MANIFEST; then
       sudo reboot
     fi
     while true; do
-      "$DIR/openpilot/common/hardware/comma/updater" "$AGNOS_PY" "$MANIFEST"
+      $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:
@@ -44,7 +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
@@ -53,11 +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"
-          # releases before the openpilot/ move can't swap AGNOS on newer AGNOS, use ours
-          [ ! -L system/hardware/tici/agnos.json ] && /data/safe_staging/old_openpilot/openpilot/common/hardware/comma/agnos.py --verify system/hardware/tici/agnos.json && sudo reboot
+          mv $DIR /data/safe_staging/old_openpilot
+          mv "${STAGING_ROOT}/finalized" $DIR
+          cd $DIR
 
           echo "Restarting launch script ${LAUNCHER_LOCATION}"
           unset AGNOS_VERSION
@@ -71,7 +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.
@@ -92,7 +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="19.9"
+  export AGNOS_VERSION="19.7"
 fi
 
 export STAGING_ROOT="/data/safe_staging"

openpilot/cereal/custom.capnp

@@ -196,6 +196,7 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
 }
 
 struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
+  dec @0 :DynamicExperimentalControl;
   longitudinalPlanSource @1 :LongitudinalPlanSource;
   smartCruiseControl @2 :SmartCruiseControl;
   speedLimit @3 :SpeedLimit;
@@ -204,11 +205,7 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
   events @6 :List(OnroadEventSP.Event);
   e2eAlerts @7 :E2eAlerts;
 
-  deprecated :group {
-    dec @0 :DynamicExperimentalControlDEPRECATED;
-  }
-
-  struct DynamicExperimentalControlDEPRECATED {
+  struct DynamicExperimentalControl {
     state @0 :DynamicExperimentalControlState;
     enabled @1 :Bool;
     active @2 :Bool;

openpilot/cereal/log.capnp

@@ -128,7 +128,6 @@ struct OnroadEvent @0xc4fa6047f024e718 {
     personalityChanged @91;
     aeb @92;
     userBookmark @95;
-    userBookmarkNotPaired @104;
     excessiveActuation @96;
     bigModelLoading @100;
     bigModelFailed @102;
@@ -167,7 +166,12 @@ struct InitData {
   gitSrcCommit @23 :Text;
   gitSrcCommitDate @24 :Text;
 
+  androidProperties @16 :Map(Text, Text);
+
+  pandaInfo @8 :PandaInfo;
+
   dirty @9 :Bool;
+  passive @12 :Bool;
   params @17 :Map(Text, Data);
 
   commands @19 :Map(Text, Data);
@@ -185,17 +189,6 @@ struct InitData {
     mici @7;  # comma four
   }
 
-  deprecated :group {
-    gctx @1 :Text;
-    androidBuildInfo @5 :Deprecated.AndroidBuildInfo;
-    androidSensors @6 :List(Deprecated.AndroidSensor);
-    chffrAndroidExtra @7 :ChffrAndroidExtra;
-    pandaInfo @8 :PandaInfo;
-    passive @12 :Bool;
-    iosBuildInfo @14 :Deprecated.IosBuildInfo;
-    androidProperties @16 :Map(Text, Text);
-  }
-
   struct PandaInfo {
     hasPanda @0 :Bool;
     dongleId @1 :Text;
@@ -206,6 +199,14 @@ struct InitData {
   struct ChffrAndroidExtra {
     allCameraCharacteristics @0 :Map(Text, Text);
   }
+
+  deprecated :group {
+    gctx @1 :Text;
+    androidBuildInfo @5 :Deprecated.AndroidBuildInfo;
+    androidSensors @6 :List(Deprecated.AndroidSensor);
+    chffrAndroidExtra @7 :ChffrAndroidExtra;
+    iosBuildInfo @14 :Deprecated.IosBuildInfo;
+  }
 }
 
 struct FrameData {
@@ -571,9 +572,6 @@ struct PandaState @0xa7649e2575e4591e {
   controlsAllowedLateral @38 :Bool;
   controlsAllowedLongitudinal @39 :Bool;
 
-  nmiReset @40 :Bool;
-  hardfaultReset @41 :Bool;
-
   enum FaultStatus {
     none @0;
     faultTemp @1;
@@ -696,7 +694,6 @@ struct PeripheralState {
 
 struct UsbState {
   devices @0 :List(Device);
-  connected @1 :Bool;
 
   struct Device {
     busnum @0 :UInt8;
@@ -822,6 +819,7 @@ struct SelfdriveState {
   alertHudVisual @12 :Car.CarControl.HUDControl.VisualAlert;
 
   # configurable driving settings
+  experimentalMode @10 :Bool;
   personality @11 :LongitudinalPersonality;
 
   enum AudibleAlert {
@@ -865,7 +863,6 @@ struct SelfdriveState {
 
   deprecated :group {
     alertSound @8 :Car.CarControl.HUDControl.AudibleAlert;
-    experimentalMode @10 :Bool;
   }
 }
 
@@ -1240,7 +1237,6 @@ struct LongitudinalPlan @0xe00b5b3eba12876c {
   shouldStop @37: Bool;
   allowThrottle @38: Bool;
   allowBrake @39: Bool;
-  accelBoost @40 :Float32;
 
 
   solverExecutionTime @35 :Float32;
@@ -2238,7 +2234,6 @@ struct DriverMonitoringState {
       pose @0: Bool;
       eye @1: Bool;
       phone @2: Bool;
-      sleep @3: Bool;
     }
 
     struct Pose {
@@ -2599,7 +2594,6 @@ struct Event {
     clocks @35 :Clocks;
     deviceState @6 :DeviceState;
     chestnutState @152 :ChestnutState;
-    chestnutGpuState @153 :ChestnutState;
     logMessage @18 :Text;
     errorLogMessage @85 :Text;
 
@@ -2710,8 +2704,8 @@ struct Event {
     driverMonitoringStateDEPRECATED @71 :DriverMonitoringStateDEPRECATED;
     gpsNMEADEPRECATED @3 :GPSNMEAData;
     uploaderStateDEPRECATED @79 :UploaderState;
-    navInstruction @82 :NavInstruction;
-    navRoute @83 :NavRoute;
+    navInstructionDEPRECATED @82 :NavInstruction;
+    navRouteDEPRECATED @83 :NavRoute;
     navThumbnailDEPRECATED @84 :Thumbnail;
     gnssMeasurementsDEPRECATED @91 :GnssMeasurements;
     mapRenderStateDEPRECATED @105: MapRenderState;

openpilot/cereal/services.py

@@ -25,8 +25,7 @@ _services: dict[str, tuple] = {
   "accelerometer": (True, 104., 104),
   "temperatureSensor": (True, 2., 200),
   "deviceState": (True, 2., 1),
-  "chestnutState": (True, 10., 1),
-  "chestnutGpuState": (False, 10.),
+  "chestnutState": (True, 10., 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),
@@ -52,8 +51,6 @@ _services: dict[str, tuple] = {
   "procLog": (True, 0.5, 15, QueueSize.BIG),
   "gpsLocationExternal": (True, 10., 10),
   "gpsLocation": (True, 1., 1),
-  "navInstruction": (True, 1., 10),
-  "navRoute": (True, 0.),
   "ubloxGnss": (True, 10.),
   "qcomGnss": (True, 2.),
   "clocks": (True, 0.1, 1),

openpilot/common/api/__init__.py

@@ -1,4 +1,4 @@
-from openpilot.common.api.comma_connect import API_HOST as API_HOST, CommaConnectApi
+from openpilot.common.api.comma_connect import CommaConnectApi
 
 
 class Api:

openpilot/common/constants.py

@@ -16,10 +16,6 @@ class CV:
   DEG_TO_RAD = np.pi / 180.
   RAD_TO_DEG = 1. / DEG_TO_RAD
 
-  # Length
-  METER_TO_FOOT = 3.28084
-  METER_TO_MILE = 1. / 1609.344
-
   # Mass
   LB_TO_KG = 0.453592
 

openpilot/common/esim/base.py

@@ -1,8 +1,6 @@
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 
-WEBBING_ICCID_PREFIX = "8985235"
-
 
 class LPAError(RuntimeError):
   pass
@@ -21,14 +19,7 @@ class Profile:
 
   @property
   def is_comma(self) -> bool:
-    return self.provider == 'Webbing' and self.iccid.startswith(WEBBING_ICCID_PREFIX)
-
-  @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:]})"
+    return self.provider == 'Webbing' and self.iccid.startswith('8985235')
 
 
 class LPABase(ABC):

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 or not all(parts):
+  if len(parts) != 3:
     raise ValueError("Invalid activation code format")
   return parts[1], parts[2]
 

openpilot/common/file_chunker.py

@@ -24,7 +24,6 @@ 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:
@@ -32,6 +31,14 @@ 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)
@@ -59,11 +66,11 @@ class ChunkStream(io.RawIOBase):
 
 def open_file_chunked(path):
   manifest_path = get_manifest_path(path)
-  if os.path.isfile(path):
-    paths = [path]
-  elif os.path.isfile(manifest_path):
+  if 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/gpio.py

@@ -27,6 +27,16 @@ def gpio_read(pin: int) -> bool | None:
 
   return val
 
+def gpio_export(pin: int) -> None:
+  if os.path.isdir(f"/sys/class/gpio/gpio{pin}"):
+    return
+
+  try:
+    with open("/sys/class/gpio/export", 'w') as f:
+      f.write(str(pin))
+  except Exception:
+    print(f"Failed to export gpio {pin}")
+
 @cache
 def get_irq_action(irq: int) -> list[str]:
   try:

openpilot/common/hardware/base.py

@@ -145,9 +145,6 @@ 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

@@ -56,28 +56,28 @@
   },
   {
     "name": "boot",
-    "url": "https://commadist.azureedge.net/agnosupdate/boot-b9c9b9261fca0cef9e6d9b198fa4b563767e6342afc7a61ab137b2b519260615.img.xz",
-    "hash": "b9c9b9261fca0cef9e6d9b198fa4b563767e6342afc7a61ab137b2b519260615",
-    "hash_raw": "b9c9b9261fca0cef9e6d9b198fa4b563767e6342afc7a61ab137b2b519260615",
-    "size": 46962688,
+    "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": "3ef4769bb1cc73bfc31f96f073b46af42dcc0bad4ab2dde32d11929745d0cd28"
+    "ondevice_hash": "d12e1e5b9455b62a1464558716493b33e470d7a7e88da1c4105a3b21d0961808"
   },
   {
     "name": "system",
-    "url": "https://commadist.azureedge.net/agnosupdate/system-80d9373348ddff2a5d1f534fab3420383939c96f3eba60baab6b15339fc602c7.img.xz",
-    "hash": "9aebca09b9d142718e71efbfe44b723010eec6e70067c043c63186067291739d",
-    "hash_raw": "80d9373348ddff2a5d1f534fab3420383939c96f3eba60baab6b15339fc602c7",
+    "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": "270b76c5c5568828e3883390b83ea445425a104dd42119d68f06093ce6b6fcef",
+    "ondevice_hash": "6a992680183685eea9db99d915219a37935f45989330d9b619e880450257f448",
     "alt": {
-      "hash": "80d9373348ddff2a5d1f534fab3420383939c96f3eba60baab6b15339fc602c7",
-      "url": "https://commadist.azureedge.net/agnosupdate/system-80d9373348ddff2a5d1f534fab3420383939c96f3eba60baab6b15339fc602c7.img",
+      "hash": "3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f",
+      "url": "https://commadist.azureedge.net/agnosupdate/system-3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f.img",
       "size": 4718592000
     }
   }

openpilot/common/hardware/comma/hardware.py

@@ -8,7 +8,6 @@ from functools import cached_property, lru_cache
 from pathlib import Path
 
 from openpilot.cereal import log
-from openpilot.common.esim.base import WEBBING_ICCID_PREFIX
 from openpilot.common.utils import sudo_read, sudo_write
 from openpilot.common.gpio import gpio_set, gpio_init, get_irqs_for_action
 from openpilot.common.esim.base import LPABase
@@ -208,8 +207,6 @@ class HardwareComma(HardwareBase):
 
   def get_network_metered(self, network_type) -> bool:
     if network_type in (NetworkType.cell2G, NetworkType.cell3G, NetworkType.cell4G, NetworkType.cell5G):
-      if self.get_modem_state().get("iccid", "").startswith(WEBBING_ICCID_PREFIX):
-        return True
       from openpilot.common.params import Params
       return Params().get_bool("GsmMetered")
     try:

openpilot/common/hardware/comma/modem.py

@@ -17,8 +17,6 @@ from ipaddress import IPv4Address, AddressValueError
 
 from enum import Enum
 
-from openpilot.common.esim.base import WEBBING_ICCID_PREFIX
-
 logging.basicConfig(
   level=logging.INFO,
   format="%(asctime)s.%(msecs)03d %(levelname)-7s modem: %(message)s",
@@ -46,6 +44,7 @@ NETWORK_TYPE = {0: "gsm", 1: "gsm", 3: "gsm", 8: "gsm",
                 11: "nr", 12: "nr", 13: "nr"}
 
 DIAL_CID = 1
+WEBBING_ICCID_PREFIX = "8985235"
 
 PPPD_CMD = [
   "sudo", "pppd", PPP_PORT, "460800", "noauth", "nodetach", "noipdefault", "usepeerdns",

openpilot/common/hardware/comma/updater

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f92c0a9b41613e063b6a1cd086729f5555d9df6482249e171ed1e276272cad7d
-size 24709520
+oid sha256:3a94ab8395f20d20a9d5a2a2bacca0694f072df8421cf13adca6250d28065bdc
+size 24709205

openpilot/common/hardware/usb.py

@@ -1,7 +1,7 @@
 import os
 from pathlib import Path
 
-CHESTNUT_FW_VERSION = "8516b768"
+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"
@@ -36,10 +36,6 @@ def read_int(path: Path, base: int = 10) -> int:
     return 0
 
 
-def cable_connected() -> bool:
-  return read_int(TYPEC_CC_ORIENTATION_PATH) != 0
-
-
 def usb_devices() -> list[Path]:
   try:
     devices = (d for d in USB_DEVICES_PATH.glob("*") if (d / "idVendor").exists())
@@ -95,4 +91,3 @@ def set_usb_state(device_state, devices: list[dict]) -> None:
       chestnut_present = True
 
   device_state.chestnutPresent = chestnut_present
-  device_state.usbState.connected = cable_connected()

openpilot/common/params_keys.h

@@ -28,7 +28,6 @@ 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"}},
@@ -139,15 +138,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"UptimeOnroad", {PERSISTENT, FLOAT, "0.0"}},
     {"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}},
-    {"ChestnutRetry", {CLEAR_ON_MANAGER_START | CLEAR_ON_IGNITION_ON, BOOL}},
-    {"InitialCruiseSpeedKph", {PERSISTENT, INT, "40"}},
-    {"NavDestination", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, JSON}},
-    {"NavigationEnabled", {PERSISTENT, BOOL, "0"}},
-    {"Offroad_ChestnutModelError", {CLEAR_ON_MANAGER_START, JSON}},
-    {"Offroad_Pairing", {CLEAR_ON_MANAGER_START, JSON}},
-    {"Offroad_UploadsIgnored", {CLEAR_ON_MANAGER_START, JSON}},
-    {"PairingEmail", {PERSISTENT, STRING}},
-    {"PairingProvider", {PERSISTENT, STRING}},
+    {"ChestnutModelError", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
     {"Version", {PERSISTENT, STRING}},
 
     // --- sunnypilot params --- //
@@ -249,6 +240,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"ToyotaEnforceStockLongitudinal", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"ToyotaStopAndGoHack", {PERSISTENT | BACKUP, BOOL, "0"}},
 
+    {"DynamicExperimentalControl", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"BlindSpot", {PERSISTENT | BACKUP, BOOL, "0"}},
 
     // sunnypilot model params

openpilot/common/qrcode.py

@@ -1,47 +1,16 @@
-"""QR code encoding, decoding, and UI textures."""
-
-import functools
-import itertools
+"""Small QR encoder for the UI's byte-mode, error-correction-level-L codes."""
 
 import numpy as np
 import pyray as rl
 
 
-# (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)),
-]
+# 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)
 
-# 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)]
+# 15 format-info bits for level L (01) with mask 0: ((0x08 << 10) | bch_remainder) ^ 0x5412
+_FORMAT_BITS = 0b111011111000100
 
 
 def _raw_modules(version: int) -> int:
@@ -52,24 +21,8 @@ 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 sum(_block_lengths(version, 0))
+  return _raw_modules(version) // 8 - _ECC_LEN[version] * _NUM_BLOCKS[version]
 
 
 def _append_bits(bits: list[int], value: int, length: int) -> None:
@@ -96,18 +49,37 @@ 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)
-  divisor = _divisor(_EC[version - 1][0][0])
-  blocks = []
+  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]] = []
   offset = 0
-  for length in _block_lengths(version, 0):
+  for i in range(num_blocks):
+    length = short_len - ecc_len + (0 if i < num_short else 1)
     block = data[offset:offset + length]
-    blocks.append(block + _remainder(block, divisor))
+    blocks.append((block, _remainder(block, divisor)))
     offset += length
-  return bytes(blocks[b][i] for b, i in _interleaved(version, 0))
+  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)
 
 
 def _multiply(x: int, y: int) -> int:
-  return _EXP[(_LOG[x] + _LOG[y]) % 255] if x and y else 0
+  result = 0
+  for _ in range(8):
+    result = (result << 1) ^ (0x11D if result & 0x80 else 0)
+    if y & 0x80:
+      result ^= x
+    y <<= 1
+  return result
 
 
 def _divisor(degree: int) -> bytes:
@@ -136,7 +108,7 @@ def _alignment_positions(version: int) -> list[int]:
   if version == 1:
     return []
   count = version // 7 + 2
-  step = (version * 8 + count * 3 + 5) // (count * 4 - 4) * 2
+  step = ((version * 4 + count * 2 + 1) // (count * 2 - 2)) * 2
   return [6] + [version * 4 + 10 - step * i for i in range(count - 1)][::-1]
 
 
@@ -199,7 +171,7 @@ class _Qr:
 
   def _format(self) -> None:
     for i in range(15):
-      bit = ((_FORMATS[1 << 3 | 0] >> i) & 1) != 0  # level L, mask 0
+      bit = ((_FORMAT_BITS >> i) & 1) != 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
@@ -244,496 +216,3 @@ 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/realtime.py

@@ -91,13 +91,8 @@ class Ratekeeper:
     self.avg_dt.add_value(self._last_monitor_time - prev)
 
     lagged = False
-    now = time.monotonic()
-    remaining = self._next_frame_time - now
-    if remaining < -self._interval:
-      # more than a frame behind (e.g. a stall): resync instead of running catch-up frames back-to-back
-      self._next_frame_time = now + self._interval
-    else:
-      self._next_frame_time += self._interval
+    remaining = self._next_frame_time - time.monotonic()
+    self._next_frame_time += self._interval
     if self._print_delay_threshold is not None and remaining < -self._print_delay_threshold:
       print(f"{self._process_name} lagging by {-remaining * 1000:.2f} ms")
       lagged = True

openpilot/common/tests/test_qrcode.py

@@ -1,178 +0,0 @@
-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/utils.py

@@ -5,6 +5,7 @@ import contextlib
 import subprocess
 import time
 import functools
+from subprocess import Popen, PIPE, TimeoutExpired
 import zstandard as zstd
 
 LOG_COMPRESSION_LEVEL = 10  # little benefit up to level 15. level ~17 is a small step change
@@ -156,6 +157,20 @@ def run_cmd_default(cmd: list[str], default: str = "", cwd=None, env=None) -> st
     return default
 
 
+@contextlib.contextmanager
+def managed_proc(cmd: list[str], env: dict[str, str]):
+  proc = Popen(cmd, env=env, stdout=PIPE, stderr=PIPE)
+  try:
+    yield proc
+  finally:
+    if proc.poll() is None:
+      proc.terminate()
+    try:
+      proc.wait(timeout=5)
+    except TimeoutExpired:
+      proc.kill()
+
+
 def tabulate(tabular_data, headers=(), tablefmt="simple", floatfmt="g", stralign="left", numalign=None):
   rows = [list(row) for row in tabular_data]
 

openpilot/common/version.h

@@ -1 +1 @@
-#define COMMA_VERSION "0.11.3"
+#define COMMA_VERSION "0.11.2"

openpilot/selfdrive/assets/icons/couch.png

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:911f59f248015600da7ecc689398103d47dfc57f6be17ac8c8e543a726a6c64b
+size 3311

openpilot/selfdrive/assets/icons/couch.svg

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dd5d8d3fce5e30662797f7eeed224f5775b2cabcc055f01f5ebf6e7b2657b616
+size 1801

openpilot/selfdrive/assets/icons/experimental.png

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1e58deb1778cf2826339f27e9f09eecc79ea137c1436210c14b71c352a649c77
+size 34953

openpilot/selfdrive/assets/icons/experimental.svg

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b7ab989c9fe22e7d2119bac5284cdccfba2889477d69f5f6c6b4470c7ee0aab3
+size 1801

openpilot/selfdrive/assets/icons/experimental_grey.png

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f37a02dd914405c6f86f415700dd5985eb976b923e7abd6580d2da76533594e
+size 9466

openpilot/selfdrive/assets/icons/experimental_grey.svg

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:90d441310f8e1833c661d8a4f0546aab2eb50eb21cc21beb0aff0d27b5ee6066
+size 1571

openpilot/selfdrive/assets/icons/experimental_white.png

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b2dad33fead9f064c3a548651d6ef37daf82b6127c329683f538ec6e986ecbc
+size 11204

openpilot/selfdrive/assets/icons/experimental_white.svg

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:82648254da89edb0cf65ef63fc5e6e0741414051bfea8a40449132fd61b1ed0f
+size 1533

openpilot/selfdrive/assets/icons_mici/experimental_mode.png

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 16243

openpilot/selfdrive/assets/icons_mici/longitudinal/car.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e0936a3d890a3ad68ffe021e4905b9b9e59ffc2ae19ee9c703daa3e7c92e7c78
-size 1793

openpilot/selfdrive/assets/icons_mici/longitudinal/car_green.png

@@ -1,3 +0,0 @@
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-oid sha256:57c7ba72642b0350ee764c924586fa66ff94915be4aba1813797e67eb4b74376
-size 33215

openpilot/selfdrive/assets/icons_mici/longitudinal/distance_1.png

@@ -1,3 +0,0 @@
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-size 237

openpilot/selfdrive/assets/icons_mici/longitudinal/distance_1_green.png

@@ -1,3 +0,0 @@
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-oid sha256:73a6fe02cf19105c0051a6664a424c1bf2ede364c6cf3791f235c86ffa203f39
-size 10348

openpilot/selfdrive/assets/icons_mici/longitudinal/distance_2.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:4f500f118dca3eedbd86fc6cc943ad8be67fe5d4f7b474d5b452cd757ad805c3
-size 282

openpilot/selfdrive/assets/icons_mici/longitudinal/distance_2_green.png

@@ -1,3 +0,0 @@
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-size 12103

openpilot/selfdrive/assets/icons_mici/longitudinal/distance_3.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8542374779f1908dc52c8a126bc041efea4c4d605afdd34e3bf8e520a7e78bf2
-size 320

openpilot/selfdrive/assets/icons_mici/longitudinal/distance_3_green.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:21e656b387c1a7e8de54d3e1b1c246f442cffe3c5e0924273d6d6d897c00b568
-size 13868

openpilot/selfdrive/assets/icons_mici/onroad/bookmark.png

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:92431d37a844206570d73d48f39dd8d934539a89668fe8d5f4cccae38f7b301b
-size 11530
+oid sha256:fd91685bf656e828648acf035a4737acb2c4709e8514cf0aa0a10fa470a9bb60
+size 11580

openpilot/selfdrive/assets/icons_mici/onroad/bookmark_fill.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3efe7d12ae82e0f5a1bd773129cf1eafe3c8c36ff5cba43a6c95f295706062b5
-size 19724

openpilot/selfdrive/assets/icons_mici/settings/device/apple.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:dfb645e59636687d61d20283bae65b68ddda6f7b2d4fda01a6e613a842e3b41f
-size 823

openpilot/selfdrive/assets/icons_mici/settings/device/commacare.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:df07383a6ddfe8cd7eeb2f22271cbd13068327ca0978873f8d10368860562e40
-size 111083

openpilot/selfdrive/assets/icons_mici/settings/device/github.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
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-size 1107

openpilot/selfdrive/assets/icons_mici/settings/device/google.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
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-size 920

openpilot/selfdrive/assets/icons_mici/settings/device/green_cell.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:710e74b526adb5bbac15cd8915a828dd673dd8ce15b2fd694c64c182eef6f56f
-size 13744

openpilot/selfdrive/assets/icons_mici/settings/device/green_settings.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:25db08a9038b5faa3b200ef5625cb216d7f4b31ea3d49fb0395f9b726bfaf8e6
-size 13135

openpilot/selfdrive/assets/icons_mici/settings/device/paired_apple.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:547f466cc59d29647f3bf131d8444d7f22b63b186bcea55ceb8109c68ca74fe8
-size 2345

openpilot/selfdrive/assets/icons_mici/settings/device/paired_github.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:55050096cd98e7f4ea3e843d927c18815e458dfbd5e7d100b503db92075d061b
-size 2373

openpilot/selfdrive/assets/icons_mici/settings/device/paired_google.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f9c439ed89bc0357e86c005d5dbb6f1ad2b8d72cdc0890e3201d842d8c3928f1
-size 2443

openpilot/selfdrive/assets/icons_mici/settings/device/phone.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7aeccd3e0d8517f74eb34f7d73632c0b29b0ad5df5b9686c0f509bb6b136561e
-size 1728

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/assets/sounds/critical_max.wav

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5d02369e21d3c78a3a5ece7e78deedb82343bc3228a28db73da48b5c27860004
-size 52374

openpilot/selfdrive/assets/sounds/dm_critical_max.wav

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3bef898e4e784baf98f3ceca53cbe95b1020da5e01162cdaa14b79b1ce0b1340
-size 52374

openpilot/selfdrive/assets/sounds/warning.wav

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:884e828e5c51d980d41b6e2400fcb4f4a926275018a00674d8239184e1eb96db
+oid sha256:1bb440f424c989c06e203bfba0b32d39aede8f6c78a9b335e5e778460202b601
 size 73026

openpilot/selfdrive/car/card.py

@@ -127,6 +127,9 @@ class Car:
     set_alternative_experience(self.CP, self.CP_SP, self.params)
     set_car_specific_params(self.CP, self.CP_SP, self.params)
 
+    # Dynamic Experimental Control
+    self.dynamic_experimental_control = self.params.get_bool("DynamicExperimentalControl")
+
     openpilot_enabled_toggle = self.params.get_bool("OpenpilotEnabledToggle")
     controller_available = self.CI.CC is not None and openpilot_enabled_toggle and not self.CP.dashcamOnly
     self.CP.passive = not controller_available or self.CP.dashcamOnly
@@ -178,11 +181,14 @@ class Car:
     self.v_cruise_helper = VCruiseHelper(self.CP, self.CP_SP)
 
     self.is_metric = self.params.get_bool("IsMetric")
-    self.initial_cruise_speed = self.params.get("InitialCruiseSpeedKph", return_default=True)
+    self.experimental_mode = self.params.get_bool("ExperimentalMode")
 
     # 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"""
 
@@ -211,7 +217,7 @@ class Car:
     self.v_cruise_helper.update_v_cruise(CS, self.sm['carControl'].enabled, self.is_metric)
     if self.sm['carControl'].enabled and not self.CC_prev.enabled:
       # Use CarState w/ buttons from the step selfdrived enables on
-      self.v_cruise_helper.initialize_v_cruise(self.CS_prev, self.initial_cruise_speed)
+      self.v_cruise_helper.initialize_v_cruise(self.CS_prev, self.experimental_mode, self.dynamic_experimental_control)
 
     # TODO: mirror the carState.cruiseState struct?
     CS.vCruise = float(self.v_cruise_helper.v_cruise_kph)
@@ -297,9 +303,9 @@ class Car:
     while not evt.is_set():
       self.is_metric = self.params.get_bool("IsMetric")
       self.experimental_mode = self.params.get_bool("ExperimentalMode") and self.CP.openpilotLongitudinalControl
-      self.initial_cruise_speed = self.params.get("InitialCruiseSpeedKph", return_default=True)
 
       # sunnypilot
+      self.dynamic_experimental_control = self.params.get_bool("DynamicExperimentalControl")
       self.v_cruise_helper.read_custom_set_speed_params()
 
       time.sleep(0.1)

openpilot/selfdrive/car/cruise.py

@@ -13,6 +13,7 @@ V_CRUISE_MIN = 8
 V_CRUISE_MAX = 145
 V_CRUISE_UNSET = 255
 V_CRUISE_INITIAL = 40
+V_CRUISE_INITIAL_EXPERIMENTAL_MODE = 105
 IMPERIAL_INCREMENT = round(CV.MPH_TO_KPH, 1)  # round here to avoid rounding errors incrementing set speed
 
 ButtonEvent = car.CarState.ButtonEvent
@@ -137,14 +138,17 @@ class VCruiseHelper(VCruiseHelperSP):
         self.button_timers[b.type.raw] = 1 if b.pressed else 0
         self.button_change_states[b.type.raw] = {"standstill": CS.cruiseState.standstill, "enabled": enabled}
 
-  def initialize_v_cruise(self, CS, initial_speed: int) -> None:
+  def initialize_v_cruise(self, CS, experimental_mode: bool, dynamic_experimental_control: bool) -> None:
     # initializing is handled by the PCM
     if self.CP.pcmCruise:
       return
 
+    initial_experimental_mode = experimental_mode and not dynamic_experimental_control
+    initial = V_CRUISE_INITIAL_EXPERIMENTAL_MODE if initial_experimental_mode else V_CRUISE_INITIAL
+
     if any(b.type in (ButtonType.accelCruise, ButtonType.resumeCruise) for b in CS.buttonEvents) and self.v_cruise_initialized:
       self.v_cruise_kph = self.v_cruise_kph_last
     else:
-      self.v_cruise_kph = int(round(np.clip(max(CS.vEgo * CV.MS_TO_KPH, initial_speed), V_CRUISE_INITIAL, V_CRUISE_MAX)))
+      self.v_cruise_kph = int(round(np.clip(CS.vEgo * CV.MS_TO_KPH, initial, V_CRUISE_MAX)))
 
     self.v_cruise_cluster_kph = self.v_cruise_kph

openpilot/selfdrive/car/tests/test_cruise_speed.py

@@ -14,7 +14,7 @@ ButtonEvent = car.CarState.ButtonEvent
 ButtonType = car.CarState.ButtonEvent.Type
 
 
-def run_cruise_simulation(cruise, personality, t_end=20.):
+def run_cruise_simulation(cruise, e2e, personality, t_end=20.):
   man = Maneuver(
     '',
     duration=t_end,
@@ -24,6 +24,7 @@ def run_cruise_simulation(cruise, personality, t_end=20.):
     cruise_values=[cruise],
     prob_lead_values=[0.0],
     breakpoints=[0.],
+    e2e=e2e,
     personality=personality,
   )
   valid, output = man.evaluate()
@@ -31,7 +32,8 @@ def run_cruise_simulation(cruise, personality, t_end=20.):
   return output[-1, 3]
 
 
-@parameterized_class(("personality", "speed"), itertools.product(
+@parameterized_class(("e2e", "personality", "speed"), itertools.product(
+                      [True, False], # e2e
                       log.LongitudinalPersonality.schema.enumerants, # personality
                       [5,35])) # speed
 class TestCruiseSpeed(OpenpilotTestCase):
@@ -39,7 +41,7 @@ class TestCruiseSpeed(OpenpilotTestCase):
     print(f'Testing {self.speed} m/s')
     cruise_speed = float(self.speed)
 
-    simulation_steady_state = run_cruise_simulation(cruise_speed, self.personality)
+    simulation_steady_state = run_cruise_simulation(cruise_speed, self.e2e, self.personality)
     self.assertAlmostEqual(simulation_steady_state, cruise_speed, delta=.01, msg=f'Did not reach {self.speed} m/s')
 
 
@@ -57,16 +59,16 @@ class TestVCruiseHelper(OpenpilotTestCase):
     for _ in range(2):
       self.v_cruise_helper.update_v_cruise(car.CarState(cruiseState={"available": False}), enabled=False, is_metric=False)
 
-  def enable(self, v_ego):
+  def enable(self, v_ego, experimental_mode, dynamic_experimental_control):
     # Simulates user pressing set with a current speed
-    self.v_cruise_helper.initialize_v_cruise(car.CarState(vEgo=v_ego), V_CRUISE_INITIAL)
+    self.v_cruise_helper.initialize_v_cruise(car.CarState(vEgo=v_ego), experimental_mode, dynamic_experimental_control)
 
   def test_adjust_speed(self):
     """
     Asserts speed changes on falling edges of buttons.
     """
 
-    self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS)
+    self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
 
     for btn in (ButtonType.accelCruise, ButtonType.decelCruise):
       for pressed in (True, False):
@@ -90,7 +92,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
       CS.buttonEvents = [ButtonEvent(type=ButtonType.decelCruise, pressed=pressed)]
       self.v_cruise_helper.update_v_cruise(CS, enabled=enabled, is_metric=False)
       if pressed:
-        self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS)
+        self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
 
       # Expected diff on enabling. Speed should not change on falling edge of pressed
       assert (not pressed) == (self.v_cruise_helper.v_cruise_kph == self.v_cruise_helper.v_cruise_kph_last)
@@ -100,7 +102,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
     Asserts we don't increment set speed if user presses resume/accel to exit cruise standstill.
     """
 
-    self.enable(0)
+    self.enable(0, False, False)
 
     for standstill in (True, False):
       for pressed in (True, False):
@@ -120,7 +122,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
 
     for v_ego in np.linspace(0, 100, 101):
       self.reset_cruise_speed_state()
-      self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS)
+      self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
 
       # first decrement speed, then perform gas pressed logic
       expected_v_cruise_kph = self.v_cruise_helper.v_cruise_kph - IMPERIAL_INCREMENT
@@ -141,10 +143,12 @@ class TestVCruiseHelper(OpenpilotTestCase):
     Asserts allowed cruise speeds on enabling with SET.
     """
 
-    for v_ego in np.linspace(0, 100, 101):
-      self.reset_cruise_speed_state()
-      assert not self.v_cruise_helper.v_cruise_initialized
+    for experimental_mode in (True, False):
+      for dynamic_experimental_control in (True, False):
+        for v_ego in np.linspace(0, 100, 101):
+          self.reset_cruise_speed_state()
+          assert not self.v_cruise_helper.v_cruise_initialized
 
-      self.enable(float(v_ego))
-      assert V_CRUISE_INITIAL <= self.v_cruise_helper.v_cruise_kph <= V_CRUISE_MAX
-      assert self.v_cruise_helper.v_cruise_initialized
+          self.enable(float(v_ego), experimental_mode, dynamic_experimental_control)
+          assert V_CRUISE_INITIAL <= self.v_cruise_helper.v_cruise_kph <= V_CRUISE_MAX
+          assert self.v_cruise_helper.v_cruise_initialized

openpilot/selfdrive/controls/lib/accel_boost.py

@@ -1,38 +0,0 @@
-import numpy as np
-from openpilot.common.constants import CV
-from openpilot.common.realtime import DT_MDL
-
-ACCEL_BOOST_MAX = 0.2
-ACCEL_BOOST_RATE = 0.025
-ACCEL_BOOST_PER_OVERRIDE = 0.05
-ACCEL_BOOST_MIN_SPEED = 10 * CV.MPH_TO_MS
-
-
-class AccelBoost:
-  def __init__(self):
-    self.total_boost = 0.0
-    self.boost_this_override = 0.0
-    self.boost_eligible = False
-
-  def update(self, sm, output_a_target_e2e, output_a_target_mpc, a_cruise):
-    enabled = sm['selfdriveState'].enabled
-    gas_pressed = sm['carState'].gasPressed
-    v_ego = sm['carState'].vEgo
-    speed_scale = np.interp(v_ego, [ACCEL_BOOST_MIN_SPEED, 2 * ACCEL_BOOST_MIN_SPEED], [0.0, 1.0])
-    boost_scale = speed_scale * np.interp(output_a_target_e2e, [-1.0, -0.5, 5.0], [0.0, 1.0, 1.0], right=0.0)
-    model_limited = output_a_target_e2e + self.total_boost * boost_scale < min(output_a_target_mpc, a_cruise) - 0.1
-
-    if not enabled or not gas_pressed:
-      self.boost_this_override = 0.0
-      # Latch eligibility before the override changes the lead plan.
-      self.boost_eligible = enabled and model_limited
-
-    if not enabled:
-      self.total_boost = 0.0
-    elif gas_pressed and self.boost_eligible:
-      increase = min(ACCEL_BOOST_RATE * DT_MDL * speed_scale,
-                     ACCEL_BOOST_PER_OVERRIDE - self.boost_this_override, ACCEL_BOOST_MAX - self.total_boost)
-      self.total_boost += increase
-      self.boost_this_override += increase
-
-    return output_a_target_e2e + self.total_boost * boost_scale

openpilot/selfdrive/controls/lib/drive_helpers.py

@@ -4,6 +4,7 @@ from openpilot.common.realtime import DT_CTRL, DT_MDL
 
 MIN_SPEED = 1.0
 CONTROL_N = 17
+CAR_ROTATION_RADIUS = 0.0
 # This is a turn radius smaller than most cars can achieve
 MAX_CURVATURE = 0.2
 MIN_STABLE_DELAY = 0.3

openpilot/selfdrive/controls/lib/latcontrol_curvature.py

@@ -1,13 +1,11 @@
 import math
-import numpy as np
-from collections import deque
 
 from openpilot.cereal import log
 from openpilot.common.pid import PIDController
 from openpilot.selfdrive.controls.lib.latcontrol import LatControl
 from openpilot.selfdrive.controls.lib.drive_helpers import MAX_CURVATURE
 
-LAT_ACCEL_SATURATION_THRESHOLD = 0.5  # m/s^2
+CURVATURE_SATURATION_THRESHOLD = 1e-3  # 1/m
 
 
 class LatControlCurvature(LatControl):
@@ -22,8 +20,6 @@ class LatControlCurvature(LatControl):
     else:
       self.pid = None
       self.kf = 1.
-    self.desired_curvature_buffer_len = int(1. / self.dt)
-    self.desired_curvature_buffer = deque([0.] * self.desired_curvature_buffer_len, maxlen=self.desired_curvature_buffer_len)
 
   def reset(self):
     super().reset()
@@ -34,9 +30,6 @@ class LatControlCurvature(LatControl):
     curvature_log = log.ControlsState.LateralCurvatureState.new_message()
     actual_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
     error = desired_curvature - actual_curvature
-    self.desired_curvature_buffer.append(desired_curvature)
-    delay_frames = int(np.clip(lat_delay / self.dt + 1, 1, self.desired_curvature_buffer_len))
-    expected_curvature = self.desired_curvature_buffer[-delay_frames]
 
     if not active:
       output_curvature = 0.0
@@ -60,6 +53,6 @@ class LatControlCurvature(LatControl):
     curvature_log.actualCurvature = float(actual_curvature)
     curvature_log.desiredCurvature = float(desired_curvature)
     curvature_log.output = float(output_curvature)
-    curvature_log.saturated = bool(self._check_saturation(abs(expected_curvature - actual_curvature) * CS.vEgo ** 2 > LAT_ACCEL_SATURATION_THRESHOLD, CS,
+    curvature_log.saturated = bool(self._check_saturation(abs(error) > CURVATURE_SATURATION_THRESHOLD, CS,
                                                           False, curvature_limited))
     return 0.0, float(output_curvature), curvature_log

openpilot/selfdrive/controls/lib/longcontrol.py

@@ -4,6 +4,7 @@ from openpilot.common.realtime import DT_CTRL
 from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N
 from openpilot.common.pid import PIDController
 from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.sunnypilot.selfdrive.controls.lib.longcontrol import LongControlSP
 
 CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
 
@@ -39,7 +40,8 @@ def long_control_state_trans(CP_SP, active, long_control_state,
 
   return long_control_state
 
-class LongControl:
+
+class LongControl(LongControlSP):
   def __init__(self, CP, CP_SP):
     self.CP = CP
     self.CP_SP = CP_SP
@@ -68,7 +70,7 @@ class LongControl:
       if output_accel > self.CP.stopAccel:
         output_accel = min(output_accel, 0.0)
         # TODO: can we just go straight to stopAccel?
-        output_accel -= 1.0 * DT_CTRL  # m/s^2/s while trying to stop
+        output_accel -= self.stopping_decel_rate(CS.vEgo) * DT_CTRL
       self.reset()
 
     else:  # LongCtrlState.pid

openpilot/selfdrive/controls/lib/longitudinal_planner.py

@@ -8,7 +8,6 @@ from openpilot.common.constants import CV
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.realtime import DT_MDL
 from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.selfdrive.controls.lib.accel_boost import AccelBoost
 from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
 from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalMpc, LongitudinalPlanSource
 from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import T_IDXS as T_IDXS_MPC
@@ -26,6 +25,7 @@ CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
 ALLOW_THROTTLE_THRESHOLD = 0.4
 MIN_ALLOW_THROTTLE_SPEED = 2.5
 
+# Lookup table for turns
 _A_TOTAL_MAX_V = [1.7, 3.2]
 _A_TOTAL_MAX_BP = [20., 40.]
 
@@ -33,7 +33,7 @@ def get_max_accel(v_ego):
   return np.interp(v_ego, A_CRUISE_MAX_BP, A_CRUISE_MAX_VALS)
 
 def get_coast_accel(pitch):
-  return np.sin(pitch) * -5.65 - 0.3
+  return np.sin(pitch) * -5.65 - 0.3  # fitted from data using xx/projects/allow_throttle/compute_coast_accel.py
 
 def get_cruise_accel(e2e, v_cruise, v_ego, a_cruise_prev, angle_steers, CP, dt, accel_coast, allow_throttle):
   max_accel = ACCEL_MAX if e2e else get_max_accel(v_ego)
@@ -62,7 +62,6 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     LongitudinalPlannerSP.__init__(self, self.CP, CP_SP, self.mpc)
     self.fcw = False
     self.dt = dt
-    self.accel_boost = AccelBoost()
     self.allow_throttle = True
 
     self.v_desired_filter = FirstOrderFilter(init_v, 2.0, self.dt)
@@ -90,18 +89,18 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
 
     long_control_off = sm['controlsState'].longControlState == LongCtrlState.off
 
-    throttle_probs = sm['modelV2'].meta.disengagePredictions.gasPressProbs
-    throttle_prob = throttle_probs[1] if len(throttle_probs) > 1 else 1.0
-    self.allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
-
-    steer_angle_without_offset = sm['carState'].steeringAngleDeg - sm['vehicleParameters'].angleOffsetDeg
-
     # Reset current state when not engaged, or user is controlling the speed
     reset_state = long_control_off if self.CP.openpilotLongitudinalControl else not sm['selfdriveState'].enabled
     # PCM cruise speed may be updated a few cycles later, check if initialized
     v_cruise_initialized = sm['carState'].vCruise != V_CRUISE_UNSET
     reset_state = reset_state or not v_cruise_initialized
 
+    throttle_probs = sm['modelV2'].meta.disengagePredictions.gasPressProbs
+    throttle_prob = throttle_probs[1] if len(throttle_probs) > 1 else 1.0
+    self.allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
+
+    steer_angle_without_offset = sm['carState'].steeringAngleDeg - sm['vehicleParameters'].angleOffsetDeg
+
     if reset_state:
       self.v_desired_filter.x = v_ego
       self.output_a_target = np.clip(sm['carState'].aEgo, ACCEL_MIN, ACCEL_MAX)
@@ -117,10 +116,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     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)
-    if self.CP.openpilotLongitudinalControl:
-      self.mpc.set_cur_state(self.v_desired_filter.x, self.output_a_target)
-    else:
-      self.mpc.set_cur_state(v_ego, sm['carState'].aEgo)
+    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)
@@ -142,18 +138,16 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
     output_should_stop_e2e = sm['modelV2'].action.shouldStop
 
-    experimental_mode = sm['selfdriveState'].deprecated.experimentalMode
+    is_e2e = self.is_e2e(sm)
 
-    self.a_cruise = get_cruise_accel(experimental_mode, v_cruise, v_ego,
+    self.a_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego,
                                      self.a_cruise, steer_angle_without_offset, self.CP, self.dt,
                                      accel_coast, self.allow_throttle)
     cruise_should_stop = should_stop(v_ego, self.a_cruise)
 
-    output_a_target_e2e = self.accel_boost.update(sm, output_a_target_e2e, output_a_target_mpc, self.a_cruise)
-
     candidates = [(output_a_target_mpc, self.mpc.source, output_should_stop_mpc),
                   (self.a_cruise, LongitudinalPlanSource.cruise, cruise_should_stop)]
-    if experimental_mode:
+    if is_e2e:
       candidates.append((output_a_target_e2e, LongitudinalPlanSource.e2e, output_should_stop_e2e))
 
     output_a_target, self.mpc.source, _ = min(candidates, key=lambda c: c[0])
@@ -181,7 +175,6 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     longitudinalPlan.fcw = self.fcw
 
     longitudinalPlan.aTarget = float(self.output_a_target)
-    longitudinalPlan.accelBoost = float(self.accel_boost.total_boost)
     longitudinalPlan.shouldStop = bool(self.output_should_stop)
     longitudinalPlan.allowBrake = True
     longitudinalPlan.allowThrottle = bool(self.allow_throttle)

openpilot/selfdrive/controls/tests/test_following_distance.py

@@ -13,7 +13,7 @@ def desired_follow_distance(v_ego, v_lead, t_follow=None):
     t_follow = get_T_FOLLOW()
   return get_safe_obstacle_distance(v_ego, t_follow) - get_stopped_equivalence_factor(v_lead)
 
-def run_following_distance_simulation(v_lead, t_end=100.0, personality=0):
+def run_following_distance_simulation(v_lead, t_end=100.0, e2e=False, personality=0):
   man = Maneuver(
     '',
     duration=t_end,
@@ -22,6 +22,7 @@ def run_following_distance_simulation(v_lead, t_end=100.0, personality=0):
     initial_distance_lead=100,
     speed_lead_values=[v_lead],
     breakpoints=[0.],
+    e2e=e2e,
     personality=personality,
   )
   valid, output = man.evaluate()
@@ -29,7 +30,8 @@ def run_following_distance_simulation(v_lead, t_end=100.0, personality=0):
   return output[-1,2] - output[-1,1]
 
 
-@parameterized_class(("personality", "speed"), itertools.product(
+@parameterized_class(("e2e", "personality", "speed"), itertools.product(
+                      [True, False], # e2e
                       [log.LongitudinalPersonality.relaxed, # personality
                        log.LongitudinalPersonality.standard,
                        log.LongitudinalPersonality.aggressive],
@@ -37,8 +39,9 @@ def run_following_distance_simulation(v_lead, t_end=100.0, personality=0):
 class TestFollowingDistance(OpenpilotTestCase):
   def test_following_distance(self):
     v_lead = float(self.speed)
-    simulation_steady_state = run_following_distance_simulation(v_lead, personality=self.personality)
+    simulation_steady_state = run_following_distance_simulation(v_lead, e2e=self.e2e, personality=self.personality)
     correct_steady_state = desired_follow_distance(v_lead, v_lead, get_T_FOLLOW(self.personality))
+    err_ratio = 0.2 if self.e2e else 0.1
     abs_err_margin = 0.5 if v_lead > 0.0 else 1.15
     self.assertAlmostEqual(simulation_steady_state, correct_steady_state,
-                           delta=0.2 * correct_steady_state + abs_err_margin)
+                           delta=err_ratio * correct_steady_state + abs_err_margin)

openpilot/selfdrive/controls/tests/test_latcontrol.py

@@ -8,14 +8,12 @@ from opendbc.car.honda.values import CAR as HONDA
 from opendbc.car.toyota.values import CAR as TOYOTA
 from opendbc.car.nissan.values import CAR as NISSAN
 from opendbc.car.gm.values import CAR as GM
-from opendbc.car.volkswagen.values import CAR as VOLKSWAGEN
 from opendbc.car.vehicle_model import VehicleModel
 from openpilot.common.realtime import DT_CTRL
 from openpilot.selfdrive.car.helpers import convert_to_capnp
 from openpilot.selfdrive.controls.lib.latcontrol_pid import LatControlPID
 from openpilot.selfdrive.controls.lib.latcontrol_torque import LatControlTorque
 from openpilot.selfdrive.controls.lib.latcontrol_angle import LatControlAngle
-from openpilot.selfdrive.controls.lib.latcontrol_curvature import LatControlCurvature
 from openpilot.selfdrive.locationd.helpers import Pose
 from openpilot.common.mock.generators import generate_deviceMotion
 from openpilot.sunnypilot.selfdrive.car import interfaces as sunnypilot_interfaces
@@ -24,8 +22,7 @@ from openpilot.sunnypilot.selfdrive.car import interfaces as sunnypilot_interfac
 class TestLatControl(OpenpilotTestCase):
 
   @parameterized.expand([(HONDA.HONDA_CIVIC, LatControlPID), (TOYOTA.TOYOTA_RAV4, LatControlTorque),
-                         (NISSAN.NISSAN_LEAF, LatControlAngle), (GM.CHEVROLET_BOLT_EUV, LatControlTorque),
-                         (VOLKSWAGEN.VOLKSWAGEN_ID4_MK2, LatControlCurvature)])
+                         (NISSAN.NISSAN_LEAF, LatControlAngle), (GM.CHEVROLET_BOLT_EUV, LatControlTorque)])
   def test_saturation(self, car_name, controller):
     CarInterface = interfaces[car_name]
     CP = CarInterface.get_non_essential_params(car_name)

openpilot/selfdrive/controls/tests/test_longcontrol.py

@@ -1,6 +1,10 @@
+from types import SimpleNamespace
+from typing import cast
+
 from openpilot.common.test import OpenpilotTestCase
 from openpilot.cereal import custom
 from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState, long_control_state_trans
+from openpilot.sunnypilot.selfdrive.controls.lib.longcontrol import LongControlSP
 
 
 class TestLongControlStateTransition(OpenpilotTestCase):
@@ -42,3 +46,21 @@ class TestLongControlStateTransition(OpenpilotTestCase):
     next_state = long_control_state_trans(CP_SP, active, current_state,
                              should_stop=False, brake_pressed=False, cruise_standstill=False)
     assert next_state == LongCtrlState.pid
+
+
+class TestStoppingHold:
+  def test_weak_brake_does_not_hold_stopping(self):
+    control = SimpleNamespace(last_output_accel=-0.109)
+    car_state = SimpleNamespace(vEgo=0.277, aEgo=-0.406)
+    assert not LongControlSP.should_hold_stopping(cast(LongControlSP, control), car_state, -0.072)
+
+  def test_sufficient_brake_holds_stopping(self):
+    control = SimpleNamespace(last_output_accel=-0.543)
+    car_state = SimpleNamespace(vEgo=0.209, aEgo=-0.534)
+    assert LongControlSP.should_hold_stopping(cast(LongControlSP, control), car_state, -0.469)
+
+  def test_stopping_decel_rate_is_smooth_while_rolling(self):
+    assert LongControlSP.stopping_decel_rate(0.1) == 0.3
+
+  def test_stopping_decel_rate_builds_holding_brake_at_stop(self):
+    assert LongControlSP.stopping_decel_rate(0.0) == 2.0

openpilot/selfdrive/locationd/locationd.py

@@ -278,12 +278,12 @@ def main():
   estimator = LocationEstimator(DEBUG)
 
   filter_initialized = False
-  critical_services = ["accelerometer", "gyroscope", "cameraOdometry"]
+  critcal_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 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}
+  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}
 
   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 critical_services:
+          if which not in critcal_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 critical_services)
+      critical_service_inputs_valid = all(observation_input_invalid[s] < input_invalid_threshold[s] for s in critcal_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/locationd/models/car_kf.py

@@ -80,6 +80,7 @@ class CarKalman(KalmanFilter):
   }
 
   global_vars = [
+    'mass',
     'rotational_inertia',
     'center_to_front',
     'center_to_rear',
@@ -98,10 +99,7 @@ class CarKalman(KalmanFilter):
 
     # globals
     global_vars = [sp.Symbol(name) for name in CarKalman.global_vars]
-    j, aF, aR, cF_orig, cR_orig = global_vars
-    # Tire stiffness and rotational inertia are already divided by vehicle mass, which cancels out of the model.
-    # Use unit mass to preserve the standard bicycle-model equations below.
-    m = 1
+    m, j, aF, aR, cF_orig, cR_orig = global_vars
 
     # make functions and jacobians with sympy
     # state variables
@@ -168,7 +166,8 @@ class CarKalman(KalmanFilter):
     self.filter = EKF_sym_pyx(generated_dir, CarKalman.name, CarKalman.Q, CarKalman.initial_x, CarKalman.P_initial,
                               dim_state, dim_state_err, global_vars=CarKalman.global_vars, logger=cloudlog)
 
-  def set_globals(self, rotational_inertia, center_to_front, center_to_rear, stiffness_front, stiffness_rear):
+  def set_globals(self, mass, rotational_inertia, center_to_front, center_to_rear, stiffness_front, stiffness_rear):
+    self.filter.set_global("mass", mass)
     self.filter.set_global("rotational_inertia", rotational_inertia)
     self.filter.set_global("center_to_front", center_to_front)
     self.filter.set_global("center_to_rear", center_to_rear)

openpilot/selfdrive/locationd/models/pose_kf.py

@@ -40,7 +40,7 @@ class PoseKalman(KalmanFilter):
   initial_P = np.diag([0.01**2, 0.01**2, 0.01**2,
                        10**2, 10**2, 10**2,
                        1**2, 1**2, 1**2,
-                       0.1**2, 0.1**2, 0.1**2,
+                       1**2, 1**2, 1**2,
                        100**2, 100**2, 100**2,
                        0.01**2, 0.01**2, 0.01**2])
 

openpilot/selfdrive/locationd/paramsd.py

@@ -36,11 +36,12 @@ class VehicleParamsLearner:
     self.P_initial = P_initial if P_initial is not None else CarKalman.P_initial
 
     self.kf.set_globals(
-      rotational_inertia=CP.rotationalInertiaPerMass,
+      mass=CP.mass,
+      rotational_inertia=CP.rotationalInertia,
       center_to_front=CP.centerToFront,
       center_to_rear=CP.wheelbase - CP.centerToFront,
-      stiffness_front=CP.tireStiffnessFrontPerMass,
-      stiffness_rear=CP.tireStiffnessRearPerMass
+      stiffness_front=CP.tireStiffnessFront,
+      stiffness_rear=CP.tireStiffnessRear
     )
 
     self.min_sr, self.max_sr = 0.5 * CP.steerRatio, 2.0 * CP.steerRatio