ref

simple

control: restore stock deceleration behavior

test

maybe better

tune

.github/CODEOWNERS

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

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

@@ -8,13 +8,13 @@ on:
         required: true
         type: string
       target_hardware:
-        description: 'Hardware target to compile for (qcom or usbgpu)'
+        description: 'Hardware target to compile for (qcom or chestnut)'
         required: true
         type: choice
         default: 'qcom'
         options:
           - qcom
-          - usbgpu
+          - chestnut
       hf_repo:
         description: 'Hugging Face dataset repository'
         required: false
@@ -59,7 +59,7 @@ jobs:
         id: get-json
         run: |
           cd docs/docs
-          PREFIX="driving_models_${{ inputs.target_hardware == 'usbgpu' && 'usbgpu_' || '' }}v"
+          PREFIX="driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_' || '' }}v"
           latest=$(ls ${PREFIX}*.json | sed -E "s/${PREFIX}([0-9]+)\.json/\1/" | sort -n | tail -1)
           next=$((latest+1))
           json_file="${PREFIX}${next}.json"
@@ -78,6 +78,7 @@ jobs:
       - name: Get next recompiled dir number
         id: create-recompiled-dir
         env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
           HF_REPO: ${{ github.event.inputs.hf_repo }}
         run: |
           pip install huggingface_hub

.github/workflows/build-default-big-model.yaml

@@ -1,83 +0,0 @@
-name: Build default big model
-
-on:
-  workflow_dispatch:
-
-env:
-  HF_REPO: sunnypilot/sunnypilot_models_v1
-  HF_DEFAULTS_PATH: models/defaults/big
-
-jobs:
-  resolve_name:
-    runs-on: ubuntu-24.04
-    outputs:
-      model_name: ${{ steps.name.outputs.model_name }}
-      onnx_ref: ${{ steps.name.outputs.onnx_ref }}
-    steps:
-      - uses: actions/checkout@v4
-      - id: name
-        run: |
-          NAME=$(PYTHONPATH=${{ github.workspace }} python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
-          ONNX_REF=$(git log -1 --format='%H' -- openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx)
-          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
-          echo "onnx_ref=$ONNX_REF" >> $GITHUB_OUTPUT
-
-  build_model:
-    needs: resolve_name
-    uses: ./.github/workflows/sunnypilot-build-model.yaml
-    with:
-      upstream_branch: ${{ needs.resolve_name.outputs.onnx_ref }}
-      custom_name: ${{ needs.resolve_name.outputs.model_name }}
-      target_hardware: usbgpu
-    secrets: inherit
-
-  upload_defaults:
-    needs: [ resolve_name, build_model ]
-    runs-on: ubuntu-24.04
-    permissions:
-      id-token: write
-      contents: write
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-      - run: git lfs pull -I "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
-
-      - name: Install huggingface_hub
-        run: pip install --upgrade "huggingface_hub>=0.22.0"
-
-      - name: Download artifact name
-        uses: actions/download-artifact@v4
-        with:
-          name: artifact-name-${{ needs.resolve_name.outputs.model_name }}
-          path: artifact_name
-
-      - name: Read artifact name
-        id: artifact
-        run: |
-          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
-          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
-
-      - name: Download model artifact
-        uses: actions/download-artifact@v4
-        with:
-          name: ${{ steps.artifact.outputs.artifact_name }}
-          path: output
-
-      - name: Upload to HF and update default_models.json
-        env:
-          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
-          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
-        run: |
-          rm -f output/artifact_name.txt
-          export PYTHONPATH=$(pwd)
-          python3 release/ci/upload_default_model.py \
-            --hf-repo "${{ env.HF_REPO }}" \
-            --hf-defaults-path "${{ env.HF_DEFAULTS_PATH }}" \
-            --artifact-name "$ARTIFACT_NAME" \
-            --model-dir output \
-            --onnx-path "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" \
-            --onnx-ref "${{ needs.resolve_name.outputs.onnx_ref }}" \
-            --model-name "${{ needs.resolve_name.outputs.model_name }}" \
-            --tinygrad-ref "$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)" \
-            --run-number "${{ github.run_number }}"

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

@@ -0,0 +1,522 @@
+name: Build default models
+
+on:
+  workflow_dispatch:
+    inputs:
+      target:
+        description: 'Model target to build'
+        required: true
+        type: choice
+        options:
+          - small
+          - big
+          - dm
+  workflow_call:
+    inputs:
+      target:
+        description: 'Model target to build (small, big, or dm)'
+        required: true
+        type: string
+
+concurrency:
+  group: build-default-models-${{ inputs.target }}
+  cancel-in-progress: false
+
+env:
+  HF_REPO: sunnypilot/sunnypilot_models_v1
+
+jobs:
+  resolve:
+    runs-on: ubuntu-24.04
+    outputs:
+      model_name: ${{ steps.resolve.outputs.model_name }}
+      safe_model_name: ${{ steps.resolve.outputs.safe_model_name }}
+      onnx_ref: ${{ steps.resolve.outputs.onnx_ref }}
+      onnx_path: ${{ steps.resolve.outputs.onnx_path }}
+      hf_defaults_path: ${{ steps.resolve.outputs.hf_defaults_path }}
+      tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - id: resolve
+        run: |
+          export PYTHONPATH=${{ github.workspace }}
+
+          if [ "${{ inputs.target }}" = "big" ]; then
+            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
+            ONNX_PATH="openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
+            HF_DEFAULTS_PATH="models/defaults/big"
+          elif [ "${{ inputs.target }}" = "dm" ]; then
+            ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
+            HF_DEFAULTS_PATH="models/defaults/dm"
+            NAME="dmonitoring_model ($(git log -1 --format=%cd --date=format:'%B %d, %Y' -- "$ONNX_PATH"))"
+          else
+            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL; print(DEFAULT_MODEL)")
+            ONNX_PATH="openpilot/selfdrive/modeld/models/driving_supercombo.onnx"
+            HF_DEFAULTS_PATH="models/defaults/small"
+          fi
+
+          ONNX_REF=$(git log -1 --format='%H' -- "$ONNX_PATH")
+          TINYGRAD_REF=$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)
+          if [ -z "$TINYGRAD_REF" ]; then
+            echo "::error::Failed to resolve tinygrad ref"
+            exit 1
+          fi
+
+          SAFE_NAME="${NAME// /-}"
+          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
+          echo "safe_model_name=${SAFE_NAME}" >> $GITHUB_OUTPUT
+          echo "onnx_ref=${ONNX_REF}" >> $GITHUB_OUTPUT
+          echo "onnx_path=${ONNX_PATH}" >> $GITHUB_OUTPUT
+          echo "hf_defaults_path=${HF_DEFAULTS_PATH}" >> $GITHUB_OUTPUT
+          echo "tinygrad_ref=${TINYGRAD_REF}" >> $GITHUB_OUTPUT
+
+  build_small_model:
+    needs: resolve
+    if: ${{ inputs.target == 'small' }}
+    runs-on: [self-hosted, tici]
+    env:
+      SMALL_ONNX: openpilot/selfdrive/modeld/models/driving_supercombo.onnx
+      SMALL_PKL: openpilot/selfdrive/modeld/models/driving_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull ONNX via LFS
+        run: git lfs pull -I "${{ env.SMALL_ONNX }}"
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Compile small model 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 }}/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:
+          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
+          OUTPUT_DIR="${{ github.workspace }}/small_output"
+          PKL_BASE="driving_tinygrad.pkl"
+          mkdir -p "$OUTPUT_DIR"
+
+          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
+
+          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
+            --model-dir "$MODELS_DIR" \
+            --output-dir "$OUTPUT_DIR" \
+            --custom-name "$MODEL_NAME" \
+            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
+
+          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
+
+      - name: Upload small model artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
+          path: ${{ github.workspace }}/small_output/
+
+      - name: Upload artifact name file
+        uses: actions/upload-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          path: ${{ github.workspace }}/small_output/artifact_name.txt
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+
+  build_big_model:
+    needs: resolve
+    if: ${{ inputs.target == 'big' }}
+    runs-on: [self-hosted, chestnut]
+    env:
+      BIG_ONNX: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
+      BIG_PKL: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull big ONNX via LFS
+        run: git lfs pull -I "${{ env.BIG_ONNX }}"
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Wait for chestnut PCIe link
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+          python3 -c "
+          import time
+          from openpilot.system.hardware.chestnut.flash import link_up
+          for i in range(10):
+              if link_up():
+                  print(f'PCIe link up after {i+1} attempt(s)')
+                  break
+              time.sleep(1)
+          else:
+              raise RuntimeError('Chestnut PCIe link not ready after 10 attempts')
+          "
+
+      - name: Compile big 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="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:
+          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
+          OUTPUT_DIR="${{ github.workspace }}/big_output"
+          PKL_BASE="big_driving_tinygrad.pkl"
+          mkdir -p "$OUTPUT_DIR"
+
+          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
+
+          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
+            --model-dir "$MODELS_DIR" \
+            --output-dir "$OUTPUT_DIR" \
+            --custom-name "$MODEL_NAME" \
+            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
+
+          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
+
+      - name: Upload big model artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
+          path: ${{ github.workspace }}/big_output/
+
+      - name: Upload artifact name file
+        uses: actions/upload-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          path: ${{ github.workspace }}/big_output/artifact_name.txt
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+
+  upload_defaults:
+    needs: [ resolve, build_small_model, build_big_model, build_dm_model ]
+    if: |
+      ${{
+        !cancelled() &&
+        (inputs.target == 'big' && needs.build_big_model.result == 'success' ||
+         inputs.target == 'small' && needs.build_small_model.result == 'success' ||
+         inputs.target == 'dm' && needs.build_dm_model.result == 'success')
+      }}
+    runs-on: ubuntu-24.04
+    permissions:
+      id-token: write
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Pull ONNX via LFS
+        run: git lfs pull -I "${{ needs.resolve.outputs.onnx_path }}"
+
+      - name: Install huggingface_hub
+        run: pip install --upgrade "huggingface_hub>=0.22.0"
+
+      - name: Download artifact name
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          path: artifact_name
+
+      - name: Read artifact name
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        id: artifact
+        run: |
+          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
+          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
+
+      - name: Download model artifact
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: ${{ steps.artifact.outputs.artifact_name }}
+          path: output
+
+      - name: Upload model to HF
+        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
+        run: |
+          rm -f output/artifact_name.txt
+          export PYTHONPATH=$(pwd)
+          python3 release/ci/upload_default_model.py \
+            --hf-repo "${{ env.HF_REPO }}" \
+            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
+            --artifact-name "$ARTIFACT_NAME" \
+            --model-dir output \
+            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
+            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
+            --model-name "${{ needs.resolve.outputs.model_name }}" \
+            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
+            --run-number "${{ github.run_number }}"
+
+      - name: Download DM artifact
+        if: ${{ inputs.target == 'dm' }}
+        uses: actions/download-artifact@v4
+        with:
+          name: dm-model-${{ github.run_number }}
+          path: dm_output
+
+      - name: Generate DM metadata and upload to HF
+        if: ${{ inputs.target == 'dm' }}
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: |
+          export PYTHONPATH=$(pwd)
+          python3 -c "
+          import json, hashlib
+          from pathlib import Path
+          from datetime import datetime, UTC
+
+          dm_dir = Path('dm_output')
+          manifest = list(dm_dir.glob('*.chunkmanifest'))
+          assert manifest, 'No chunkmanifest found'
+          pkl_name = manifest[0].name.removesuffix('.chunkmanifest')
+          num_chunks = int(manifest[0].read_text().strip())
+
+          chunks = []
+          for i in range(num_chunks):
+              chunk = dm_dir / f'{pkl_name}.chunk{i+1:02d}of{num_chunks:02d}'
+              chunks.append({
+                  'file_name': chunk.name,
+                  'sha256': hashlib.sha256(chunk.read_bytes()).hexdigest()
+              })
+
+          digest = hashlib.sha256()
+          for c in chunks:
+              with open(dm_dir / c['file_name'], 'rb') as f:
+                  while block := f.read(1024*1024):
+                      digest.update(block)
+
+          metadata = {
+              'bundles': [{
+                  'short_name': 'DMMODEL',
+                  'display_name': '${{ needs.resolve.outputs.model_name }}',
+                  'ref': '${{ needs.resolve.outputs.onnx_ref }}',
+                  'runner': 'tinygrad',
+                  'build_time': datetime.now(UTC).strftime('%Y-%m-%dT%H:%M:%SZ'),
+                  'models': [{
+                      'type': 'chunked',
+                      'artifact': {
+                          'file_name': pkl_name,
+                          'download_uri': {'url': '', 'sha256': digest.hexdigest()},
+                          'chunks': chunks
+                      }
+                  }]
+              }]
+          }
+          with open(dm_dir / 'metadata.json', 'w') as f:
+              json.dump(metadata, f, indent=2)
+          print('Generated DM metadata.json')
+          "
+
+          python3 release/ci/upload_default_model.py \
+            --hf-repo "${{ env.HF_REPO }}" \
+            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
+            --artifact-name "dm-model-${{ github.run_number }}" \
+            --model-dir dm_output \
+            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
+            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
+            --model-name "${{ needs.resolve.outputs.model_name }}" \
+            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
+            --run-number "${{ github.run_number }}"
+
+  build_dm_model:
+    needs: resolve
+    if: ${{ inputs.target == 'dm' }}
+    runs-on: [self-hosted, tici]
+    env:
+      DM_ONNX: openpilot/selfdrive/modeld/models/dmonitoring_model.onnx
+      DM_PKL: openpilot/selfdrive/modeld/models/dmonitoring_model_tinygrad.pkl
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Pull DM ONNX via LFS
+        run: git lfs pull -I "${{ env.DM_ONNX }}"
+
+      - name: Set environment variables
+        run: |
+          source /etc/profile
+          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
+          export UV_PYTHON_PREFERENCE=managed
+          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
+          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
+          uv sync --frozen
+          printenv >> $GITHUB_ENV
+
+      - name: Disable powersave
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
+
+      - name: Compile DM model
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+
+          taskset -c 7 env ${TG_FLAGS} python3 \
+            ${{ github.workspace }}/tinygrad_repo/examples/openpilot/compile3.py \
+            ${{ github.workspace }}/${{ env.DM_ONNX }} \
+            ${{ github.workspace }}/${{ env.DM_PKL }}
+
+      - name: Chunk DM pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.DM_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked {pkl} into {len(targets)} chunks')
+          "
+
+      - name: Compile DM warp
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+          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 $(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')"); do
+            WARP_PKL="${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} \
+              --output ${WARP_PKL}
+          done
+
+      - name: Prepare DM output
+        run: |
+          mkdir -p dm_output
+          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunk* dm_output/
+          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunkmanifest dm_output/
+          cp ${{ github.workspace }}/openpilot/selfdrive/modeld/models/dm_warp_* dm_output/
+
+      - name: Upload DM artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: dm-model-${{ github.run_number }}
+          path: dm_output/
+
+      - name: Re-enable powersave
+        if: always()
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+

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

@@ -30,7 +30,7 @@ on:
         type: boolean
         default: true
       target_hardware:
-        description: 'Hardware target to compile for (qcom or usbgpu)'
+        description: 'Hardware target to compile for (qcom or chestnut)'
         required: false
         type: string
         default: 'qcom'
@@ -101,7 +101,7 @@ on:
         default: 'qcom'
         options:
           - qcom
-          - usbgpu
+          - chestnut
       hf_repo:
         description: 'Hugging Face dataset repository'
         required: false
@@ -109,7 +109,7 @@ on:
         default: 'sunnypilot/sunnypilot_models_v1'
 env:
   RECOMPILED_DIR: recompiled${{ inputs.recompiled_dir }}
-  JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'usbgpu' && 'usbgpu_v' || 'v' }}${{ inputs.json_version }}.json
+  JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_v' || 'v' }}${{ inputs.json_version }}.json
 
 jobs:
   build_model:
@@ -146,7 +146,7 @@ jobs:
 
       - name: Validate hf_repo and JSON version
         env:
-          HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
         run: |
           if [ ! -f "$JSON_FILE" ]; then
             echo "JSON file $JSON_FILE does not exist!"
@@ -155,13 +155,8 @@ jobs:
           python3 -c "
           import sys
           from huggingface_hub import HfApi
-          try:
-              api = HfApi()
-              api.repo_info(repo_id=sys.argv[1], repo_type='dataset')
-              print(f'Success: Repo {sys.argv[1]} exists.')
-          except Exception as e:
-              print('HF validation failed:', e)
-              sys.exit(1)
+          HfApi().repo_info(repo_id=sys.argv[1], repo_type='dataset')
+          print(f'Success: Repo {sys.argv[1]} exists.')
           " "${{ inputs.hf_repo }}"
 
       - name: Download artifact name file
@@ -192,7 +187,7 @@ jobs:
 
       - name: Upload to Hugging Face
         env:
-          HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
           ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
         run: |
           hf upload ${{ inputs.hf_repo }} \

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

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

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

@@ -31,7 +31,7 @@ on:
         type: string
         default: ''
       target_hardware:
-        description: 'Hardware target to compile for (qcom or usbgpu)'
+        description: 'Hardware target to compile for (qcom or chestnut)'
         required: false
         type: string
         default: 'qcom'
@@ -57,7 +57,7 @@ on:
         type: choice
         options:
           - qcom
-          - usbgpu
+          - chestnut
         default: 'qcom'
 
 
@@ -102,7 +102,7 @@ jobs:
           cat $GITHUB_OUTPUT
       - run: |
           cd ${{ github.workspace }}/openpilot/openpilot
-          if [ "${{ inputs.target_hardware }}" != "usbgpu" ]; then
+          if [ "${{ inputs.target_hardware }}" != "chestnut" ]; then
             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
@@ -121,7 +121,7 @@ jobs:
           if-no-files-found: error
 
   build_model:
-    runs-on: [self-hosted, usbgpu]
+    runs-on: [self-hosted, "${{ inputs.target_hardware == 'chestnut' && 'chestnut' || 'tici' }}"]
     needs: get_model
     env:
       MODEL_NAME: ${{ inputs.custom_name || inputs.upstream_branch }} (${{ needs.get_model.outputs.model_date }})
@@ -185,10 +185,10 @@ jobs:
           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 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-          if [ "${{ inputs.target_hardware }}" == "usbgpu" ]; then
-            echo "USBGPU build"
-            export USBGPU=1
-            TG_FLAGS="DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
+          if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
+            echo "CHESTNUT build"
+            export CHESTNUT=1
+            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1"
             OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
           else
             echo "QCOM build"

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

@@ -39,6 +39,8 @@ jobs:
       include_big_model: ${{ steps.strategy.outputs.include_big_model }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
       - name: Extract deploy strategy
         id: strategy
         run: |
@@ -96,6 +98,8 @@ jobs:
       }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
       - name: Wait for Tests
         uses: ./.github/workflows/wait-for-action # Path to where you place the action
         with:
@@ -119,6 +123,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
         with:
+          fetch-depth: 1
           submodules: recursive
           ref: ${{ env.SOURCE_BRANCH }}
           repository: ${{ github.event.pull_request.head.repo.fork && github.event.pull_request.head.repo.full_name || github.repository }}
@@ -165,7 +170,7 @@ jobs:
           scons -j1 cache_dir="$SCONS_CACHE" --minimal \
             openpilot/selfdrive/locationd openpilot/sunnypilot/selfdrive/locationd
           echo "Building rest of sunnypilot"
-          /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
+          SKIP_TINYGRAD_COMPILE=1 /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
           touch ${BUILD_DIR}/prebuilt
           if [[ "${{ runner.debug }}" == "1" ]]; then
             ls -la ${BUILD_DIR}
@@ -211,91 +216,245 @@ jobs:
     needs: [ prepare_strategy ]
     runs-on: ubuntu-24.04
     if: ${{ needs.prepare_strategy.outputs.include_big_model == 'true' }}
+    concurrency:
+      group: prepare-chestnut
+      cancel-in-progress: false
+    outputs:
+      onnx_sha256: ${{ steps.resolve.outputs.onnx_sha256 }}
     env:
+      GH_REPO: ${{ github.repository }}
       HF_REPO: sunnypilot/sunnypilot_models_v1
       HF_DEFAULTS_PATH: models/defaults/big
     steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ github.head_ref || github.ref_name }}
-
-      - run: git lfs pull -I "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
-
-      - name: Check HF defaults and build if needed
+      - name: Resolve ONNX hash and tinygrad ref via API
         id: resolve
         run: |
-          ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
-          echo "Repo ONNX hash: $ACTUAL_ONNX_HASH"
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          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 "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"
 
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
-          check_hash() {
-            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
-            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ACTUAL_ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+          check_defaults() {
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
             [ -n "$BUNDLE" ] && [ "$BUNDLE" != "null" ]
           }
 
-          if check_hash; then
-            echo "HF defaults match repo ONNX"
-          else
-            echo "No matching model on HF — triggering build"
-            gh workflow run build-default-big-model.yaml --ref "${{ github.head_ref || github.ref_name }}"
-
-            echo "Waiting for build to start..."
-            sleep 120
-
-            RUN_ID=$(gh run list --workflow=build-default-big-model.yaml --branch="${{ github.head_ref || github.ref_name }}" --limit=1 --json databaseId --jq '.[0].databaseId')
-            if [ -z "$RUN_ID" ] || [ "$RUN_ID" = "null" ]; then
-              echo "::error::Failed to find build-default-big-model run"
-              exit 1
-            fi
-
-            echo "Waiting for run $RUN_ID..."
-            gh run watch "$RUN_ID"
-
-            CONCLUSION=$(gh run view "$RUN_ID" --json conclusion --jq '.conclusion')
-            if [ "$CONCLUSION" != "success" ]; then
-              echo "::error::build-default-big-model failed: $CONCLUSION"
-              exit 1
-            fi
-
-            if ! check_hash; then
-              echo "::error::HF defaults still don't match after build"
-              exit 1
-            fi
+          if check_defaults; then
+            echo "HF defaults match repo ONNX hash and tinygrad ref"
+            exit 0
           fi
+
+          echo "No matching model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=big
+          sleep 10
+
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
+          for i in $(seq 1 90); do
+            sleep 30
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/90: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "Big model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
+            fi
+          done
+
+          echo "::error::Build run did not complete within 45 minutes"
+          exit 1
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Download big model chunks
+      - name: Cancel run on failure
+        if: failure()
+        run: gh run cancel ${{ github.run_id }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+  prepare_small_model:
+    needs: [ prepare_strategy ]
+    runs-on: ubuntu-24.04
+    concurrency:
+      group: prepare-small-model
+      cancel-in-progress: false
+    outputs:
+      driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
+    env:
+      GH_REPO: ${{ github.repository }}
+      HF_REPO: sunnypilot/sunnypilot_models_v1
+      HF_DEFAULTS_PATH: models/defaults/small
+    steps:
+      - name: Resolve ONNX hash and tinygrad ref via API
+        id: resolve
         run: |
-          ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.sha')
+          DRIVING_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          echo "Driving ONNX hash: $DRIVING_HASH"
+          [ -n "$DRIVING_HASH" ] || { echo "::error::Failed to extract driving ONNX hash"; exit 1; }
+          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: $TINYGRAD_REF"
+
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
-          DEFAULTS=$(curl -fsSL "$JSON_URL")
-          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ACTUAL_ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
 
-          mkdir -p big_model_chunks
-          ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
-          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
-          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
+          check_defaults() {
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            DRIVING=$(echo "$DEFAULTS" | jq --arg hash "$DRIVING_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            [ -n "$DRIVING" ] && [ "$DRIVING" != "null" ] || return 1
+          }
 
-          CANONICAL="big_driving_tinygrad.pkl"
-          echo "$ARTIFACT" | jq -r '.chunks[].file_name' | while read CHUNK_NAME; do
-            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+')
-            CANONICAL_CHUNK="${CANONICAL}.chunk${CHUNK_IDX}"
-            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
-            echo "Downloading $CHUNK_NAME -> $CANONICAL_CHUNK"
-            curl -fsSL -o "big_model_chunks/${CANONICAL_CHUNK}" "$ENCODED_URL"
+          if check_defaults; then
+            echo "HF defaults match repo ONNX hash and tinygrad ref"
+            exit 0
+          fi
+
+          echo "No matching model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=small
+          sleep 10
+
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
+          for i in $(seq 1 60); do
+            sleep 30
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "Small model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
+            fi
           done
 
-          echo "$NUM_CHUNKS" > "big_model_chunks/${CANONICAL}.chunkmanifest"
+          echo "::error::Small model build did not complete within 30 minutes"
+          exit 1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Upload big model chunks
-        uses: actions/upload-artifact@v4
-        with:
-          name: big-model-chunks
-          path: big_model_chunks/
-          compression-level: 0
+      - name: Cancel run on failure
+        if: failure()
+        run: gh run cancel ${{ github.run_id }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+
+  prepare_dm_model:
+    needs: [ prepare_strategy ]
+    runs-on: ubuntu-24.04
+    concurrency:
+      group: prepare-dm-model
+      cancel-in-progress: false
+    outputs:
+      dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
+    env:
+      GH_REPO: ${{ github.repository }}
+      HF_REPO: sunnypilot/sunnypilot_models_v1
+      HF_DEFAULTS_PATH: models/defaults/dm
+    steps:
+      - name: Resolve ONNX hash and tinygrad ref via API
+        id: resolve
+        run: |
+          REF="${{ github.head_ref || github.ref_name }}"
+
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.sha')
+          DM_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          echo "DM ONNX hash: $DM_HASH"
+          [ -n "$DM_HASH" ] || { echo "::error::Failed to extract DM ONNX hash"; exit 1; }
+          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: $TINYGRAD_REF"
+
+          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
+
+          check_defaults() {
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
+            [ "$TINYGRAD_MATCH" = "true" ] || return 1
+            DM=$(echo "$DEFAULTS" | jq --arg hash "$DM_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            [ -n "$DM" ] && [ "$DM" != "null" ] || return 1
+          }
+
+          if check_defaults; then
+            echo "HF defaults match DM ONNX hash and tinygrad ref"
+            exit 0
+          fi
+
+          echo "No matching DM model on HF — dispatching build"
+          gh workflow run build-default-models.yaml --ref "$REF" -f target=dm
+          sleep 10
+
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
+          for i in $(seq 1 60); do
+            sleep 30
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "DM model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but DM model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
+            fi
+          done
+
+          echo "::error::DM model build did not complete within 30 minutes"
+          exit 1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Cancel run on failure
         if: failure()
@@ -305,23 +464,24 @@ jobs:
 
   publish:
     concurrency:
-      # We do a bit of a hack here to avoid canceling the publishing job if a new commit comes in while we're publishing by adding the sha to the group name.
-      # This means that if multiple commits come in while we're publishing, they will be queued up and publish one after the other.
-      # Otherwise, if a job is waiting to be published due to environment wait time, it would be canceled by a new commit and restart the wait time.
       group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}
       cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
     if: ${{
       always() && !cancelled() &&
       needs.build.result == 'success' &&
       needs.prepare_strategy.result == 'success' &&
+      needs.prepare_small_model.result == 'success' &&
+      needs.prepare_dm_model.result == 'success' &&
       (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) &&
       (needs.prepare_strategy.outputs.include_big_model != 'true' || needs.prepare_chestnut.result == 'success')
       }}
-    needs: [ build, prepare_strategy, prepare_chestnut ]
+    needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
     runs-on: ubuntu-24.04
     environment: ${{ needs.prepare_strategy.outputs.environment }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
 
       - name: Download prebuilt artifact
         uses: actions/download-artifact@v4
@@ -333,23 +493,16 @@ jobs:
           mkdir -p ${{ env.OUTPUT_DIR }}
           tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
 
-      - name: Prepare chestnut output
-        if: ${{ needs.prepare_chestnut.result == 'success' }}
-        run: |
-          mkdir -p "${{ github.workspace }}/chestnut_output"
-          tar xzf prebuilt.tar.gz -C "${{ github.workspace }}/chestnut_output"
-
-      - name: Download big model chunks
-        if: ${{ needs.prepare_chestnut.result == 'success' }}
-        uses: actions/download-artifact@v4
+      - name: Download model chunks from HF
+        uses: ./.github/workflows/download-hf-model-chunks
         with:
-          name: big-model-chunks
-          path: big_model_chunks
-
-      - name: Inject big model into chestnut
-        if: ${{ needs.prepare_chestnut.result == 'success' }}
-        run: |
-          cp big_model_chunks/* "${{ github.workspace }}/chestnut_output/openpilot/selfdrive/modeld/models/"
+          hf_repo: sunnypilot/sunnypilot_models_v1
+          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
+          models: |
+            [
+              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
+              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"}
+            ]
 
       - name: Configure Git
         run: |
@@ -371,22 +524,6 @@ jobs:
             "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
             "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
 
-      - name: Publish chestnut branch
-        if: ${{ needs.prepare_chestnut.result == 'success' }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
-          CHESTNUT_DIR="${{ github.workspace }}/chestnut_output"
-
-          ${{ env.CI_DIR }}/publish.sh \
-            "${{ github.workspace }}" \
-            "$CHESTNUT_DIR" \
-            "$CHESTNUT_BRANCH" \
-            "${{ needs.prepare_strategy.outputs.version }}" \
-            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
-            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
-
       - name: Tag ${{ needs.prepare_strategy.outputs.environment }}
         if: ${{ needs.prepare_strategy.outputs.is_stable_branch == 'true' && (github.event_name != 'push' || !startsWith(github.ref, 'refs/tags/')) }}
         run: |
@@ -394,12 +531,77 @@ jobs:
             git tag -f -a ${TAG} -m "${{ needs.prepare_strategy.outputs.environment }} @ ${{ needs.prepare_strategy.outputs.version }} of build ${{ needs.prepare_strategy.outputs.build }}."
             git push -f origin ${TAG}
 
+  publish_chestnut:
+    concurrency:
+      group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}-chestnut
+      cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
+    if: ${{
+      always() && !cancelled() &&
+      needs.build.result == 'success' &&
+      needs.prepare_strategy.result == 'success' &&
+      needs.prepare_small_model.result == 'success' &&
+      needs.prepare_dm_model.result == 'success' &&
+      needs.prepare_chestnut.result == 'success' &&
+      (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt'))
+      }}
+    needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
+    runs-on: ubuntu-24.04
+    environment: ${{ needs.prepare_strategy.outputs.environment }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
+
+      - name: Download prebuilt artifact
+        uses: actions/download-artifact@v4
+        with:
+          name: prebuilt
+
+      - name: Untar prebuilt
+        run: |
+          mkdir -p ${{ env.OUTPUT_DIR }}
+          tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
+
+      - name: Download model chunks from HF
+        uses: ./.github/workflows/download-hf-model-chunks
+        with:
+          hf_repo: sunnypilot/sunnypilot_models_v1
+          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
+          models: |
+            [
+              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
+              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"},
+              {"hf_path": "models/defaults/big", "onnx_hash": "${{ needs.prepare_chestnut.outputs.onnx_sha256 }}", "canonical": "big_driving_tinygrad.pkl"}
+            ]
+
+      - name: Configure Git
+        run: |
+          git config --global user.email "github-actions[bot]@users.noreply.github.com"
+          git config --global user.name "github-actions[bot]"
+
+      - name: Publish chestnut branch
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
+
+          ${{ env.CI_DIR }}/publish.sh \
+            "${{ github.workspace }}" \
+            "${{ env.OUTPUT_DIR }}" \
+            "$CHESTNUT_BRANCH" \
+            "${{ needs.prepare_strategy.outputs.version }}" \
+            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
+            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
+
   notify:
     needs:
     - prepare_strategy
     - build
     - publish
+    - publish_chestnut
     - prepare_chestnut
+    - prepare_small_model
+    - prepare_dm_model
     runs-on: ubuntu-24.04
     if: ${{ (always() && !cancelled() && !failure())
       && needs.publish.result == 'success'
@@ -407,6 +609,8 @@ jobs:
       && (fromJSON(vars.DEV_FEEDBACK_NOTIFICATION_BRANCHES_V2)[github.head_ref || github.ref_name] != null) }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
 
       - name: Prepare notification message
         id: message

.gitmodules

@@ -4,6 +4,7 @@
 [submodule "opendbc"]
   path = opendbc_repo
   url = https://github.com/sunnypilot/opendbc.git
+  branch = tn
 [submodule "msgq"]
   path = msgq_repo
   url = https://github.com/sunnypilot/msgq.git

launch_chffrplus.sh

@@ -24,7 +24,9 @@ function agnos_init {
     if $AGNOS_PY --verify $MANIFEST; then
       sudo reboot
     fi
-    $DIR/openpilot/common/hardware/comma/updater $AGNOS_PY $MANIFEST
+    while true; do
+      $DIR/openpilot/common/hardware/comma/updater $AGNOS_PY $MANIFEST
+    done
   fi
 }
 

launch_env.sh

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

openpilot/cereal/custom.capnp

@@ -131,6 +131,7 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
     downloaded @2;
     cached @3;
     failed @4;
+    verifying @5;
   }
 
   struct DownloadProgress {
@@ -203,11 +204,16 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
   aTarget @5 :Float32;
   events @6 :List(OnroadEventSP.Event);
   e2eAlerts @7 :E2eAlerts;
+  accelController @8 :AccelController;
 
   struct DynamicExperimentalControl {
     state @0 :DynamicExperimentalControlState;
     enabled @1 :Bool;
     active @2 :Bool;
+    decelIntent @3 :Float32;
+    curveDetected @4 :Bool;
+    wantBlended @5 :Bool;
+    leadVeto @6 :Bool;
 
     enum DynamicExperimentalControlState {
       acc @0;
@@ -305,6 +311,17 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
     greenLightAlert @0 :Bool;
     leadDepartAlert @1 :Bool;
   }
+
+  struct AccelController {
+    enabled @0 :Bool;
+    active @1 :Bool;
+    profile @2 :Profile;
+    enum Profile {
+      eco @0;
+      normal @1;
+      sport @2;
+    }
+  }
 }
 
 struct OnroadEventSP @0xda96579883444c35 {
@@ -352,6 +369,7 @@ struct OnroadEventSP @0xda96579883444c35 {
     speedLimitPending @22;
     e2eChime @23;
     laneChangeRoadEdge @24;
+    bigModelReady @25;
   }
 }
 

openpilot/cereal/log.capnp

@@ -725,6 +725,7 @@ struct ChestnutState {
   pcieLtssm @7 :UInt8;
   supplyVoltage @8 :UInt16;  # mV
   supplyCurrent @9 :Int16;  # mA
+  supplyFault @10 :Bool;
 }
 
 struct RadarState @0x9a185389d6fdd05f {
@@ -1004,6 +1005,7 @@ struct DrivingModelData {
   frameIdExtra @1 :UInt32;
   frameDropPerc @6 :Float32;
   modelExecutionTime @7 :Float32;
+  big @8 :Bool;
 
   action @2 :ModelDataV2.Action;
 

openpilot/common/hardware/comma/agnos.json

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

openpilot/common/hardware/comma/modem.py

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

openpilot/common/hardware/usb.py

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

openpilot/common/params_keys.h

@@ -59,7 +59,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"IsDriverViewEnabled", {CLEAR_ON_MANAGER_START, BOOL}},
     {"IsEngaged", {PERSISTENT, BOOL}},
     {"IsLdwEnabled", {PERSISTENT | BACKUP, BOOL}},
-    {"IsLiveStreaming", {CLEAR_ON_MANAGER_START, BOOL}},
+    {"IsLiveStreaming", {CLEAR_ON_MANAGER_START | CLEAR_ON_IGNITION_ON, BOOL}},
     {"IsMetric", {PERSISTENT | BACKUP, BOOL}},
     {"IsOffroad", {CLEAR_ON_MANAGER_START, BOOL}},
     {"IsRhdDetected", {PERSISTENT, BOOL}},
@@ -92,6 +92,12 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"ObdMultiplexingEnabled", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"Offroad_CarUnrecognized", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
     {"Offroad_ChestnutBranch", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutNotDetected", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutOverheated", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutPcieUnavailable", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutUncompiled", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutUpdateFailed", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutUsbSlow", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
     {"Offroad_ConnectivityNeeded", {CLEAR_ON_MANAGER_START, JSON}},
     {"Offroad_ConnectivityNeededPrompt", {CLEAR_ON_MANAGER_START, JSON}},
     {"Offroad_ExcessiveActuation", {PERSISTENT, JSON}},
@@ -130,8 +136,9 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"UpdaterLastFetchTime", {PERSISTENT, TIME}},
     {"UptimeOffroad", {PERSISTENT, FLOAT, "0.0"}},
     {"UptimeOnroad", {PERSISTENT, FLOAT, "0.0"}},
-    {"UsbGpuActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
-    {"UsbGpuLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"ChestnutActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"ChestnutLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"ChestnutModelError", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
     {"Version", {PERSISTENT, STRING}},
 
     // --- sunnypilot params --- //
@@ -187,6 +194,12 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"StandstillTimer", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"TrueVEgoUI", {PERSISTENT | BACKUP, BOOL, "0"}},
 
+    // toyota specific params
+    {"ToyotaAutoHold", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"ToyotaEnhancedBsm", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"ToyotaTSS2Long", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"ToyotaDriveMode", {PERSISTENT | BACKUP, BOOL, "0"}},
+
     // MADS params
     {"Mads", {PERSISTENT | BACKUP, BOOL, "1"}},
     {"MadsMainCruiseAllowed", {PERSISTENT | BACKUP, BOOL, "1"}},
@@ -195,14 +208,16 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
 
     // Model Manager params
     {"ModelManager_ActiveBundle", {PERSISTENT, JSON}},
-    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, STRING}},
+    {"ModelManager_ActiveBundleUSBGPU", {PERSISTENT, JSON}}, //TODO-SP: kept for migration, remove on next sync?
+    {"ModelManager_ActiveBundleChestnut", {PERSISTENT, JSON}},
+    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, JSON}},
     {"ModelManager_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
-    {"ModelManager_DownloadIndex", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, INT}},
+    {"ModelManager_DownloadRef", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
     {"ModelManager_Favs", {PERSISTENT | BACKUP, STRING}},
     {"ModelManager_LastSyncTime", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
-    {"ModelManager_LastSyncTime_USBGPU", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
+    {"ModelManager_LastSyncTime_Chestnut", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
     {"ModelManager_ModelsCache", {PERSISTENT | BACKUP, JSON}},
-    {"ModelManager_ModelsCache_USBGPU", {PERSISTENT | BACKUP, JSON}},
+    {"ModelManager_ModelsCache_Chestnut", {PERSISTENT | BACKUP, JSON}},
 
     // Neural Network Lateral Control
     {"NeuralNetworkLateralControl", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -234,6 +249,10 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"DynamicExperimentalControl", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"BlindSpot", {PERSISTENT | BACKUP, BOOL, "0"}},
 
+    // Accel Controller profiles (Eco / Normal / Sport)
+    {"AccelPersonalityEnabled", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"AccelPersonality", {PERSISTENT | BACKUP, INT, "1"}},
+
     // sunnypilot model params
     {"CameraOffset", {PERSISTENT | BACKUP, FLOAT, "0.0"}},
     {"LagdToggle", {PERSISTENT | BACKUP, BOOL, "1"}},
@@ -245,6 +264,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
 
     // mapd
     {"MapAdvisorySpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, FLOAT}},
+    {"Mapd_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
     {"MapdVersion", {PERSISTENT, STRING}},
     {"MapSpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, FLOAT, "0.0"}},
     {"NextMapSpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, JSON}},

openpilot/common/prefix.h

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

openpilot/common/tests/test_params.py

@@ -117,12 +117,16 @@ class TestParams(OpenpilotTestCase):
   def test_params_default_value(self):
     self.params.remove("LanguageSetting")
     self.params.remove("LongitudinalPersonality")
+    self.params.remove("AccelPersonalityEnabled")
+    self.params.remove("AccelPersonality")
     self.params.remove("LiveParametersV2")
 
     assert self.params.get("LanguageSetting") is None
     assert self.params.get("LanguageSetting", return_default=False) is None
     assert isinstance(self.params.get("LanguageSetting", return_default=True), str)
     assert isinstance(self.params.get("LongitudinalPersonality", return_default=True), int)
+    assert self.params.get("AccelPersonalityEnabled", return_default=True) is False
+    assert self.params.get("AccelPersonality", return_default=True) == 1
     assert self.params.get("LiveParametersV2") is None
     assert self.params.get("LiveParametersV2", return_default=True) is None
 

openpilot/selfdrive/assets/icons_mici/chestnut_orange.png

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:845c40ff0d37612e8f2f482a36845744b5ae91ce2fcfc8117990d7d278b59820
+size 13079

openpilot/selfdrive/assets/icons_mici/egpu_crossed.png

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

openpilot/selfdrive/assets/icons_mici/egpu_gray.png

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

openpilot/selfdrive/assets/icons_mici/egpu_orange.png

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

openpilot/selfdrive/assets/icons_mici/usb.png

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

openpilot/selfdrive/car/card.py

@@ -11,13 +11,13 @@ from opendbc.car.structs import car
 from openpilot.common.params import Params
 from openpilot.common.realtime import config_realtime_process, Priority, Ratekeeper
 from openpilot.common.swaglog import cloudlog, ForwardingHandler
-
 from opendbc.car import DT_CTRL, structs
 from opendbc.car.can_definitions import CanData, CanRecvCallable, CanSendCallable
 from opendbc.car.carlog import carlog
 from opendbc.car.fw_versions import ObdCallback
 from opendbc.car.car_helpers import get_car, interfaces
 from opendbc.car.interfaces import CarInterfaceBase, RadarInterfaceBase
+from opendbc.safety import ALTERNATIVE_EXPERIENCE
 from openpilot.selfdrive.pandad import can_capnp_to_list, can_list_to_can_capnp
 from openpilot.selfdrive.car.cruise import VCruiseHelper
 from openpilot.selfdrive.car.helpers import convert_carControlSP, convert_to_capnp
@@ -123,6 +123,9 @@ class Car:
       self.RI = RI
 
     self.CP.alternativeExperience = 0
+    if self.params.get_bool("ToyotaAutoHold"):
+      self.CP.alternativeExperience |= ALTERNATIVE_EXPERIENCE.ALLOW_AEB
+
     # mads
     set_alternative_experience(self.CP, self.CP_SP, self.params)
     set_car_specific_params(self.CP, self.CP_SP, self.params)

openpilot/selfdrive/car/cruise.py

@@ -19,6 +19,7 @@ IMPERIAL_INCREMENT = round(CV.MPH_TO_KPH, 1)  # round here to avoid rounding err
 ButtonEvent = car.CarState.ButtonEvent
 ButtonType = car.CarState.ButtonEvent.Type
 CRUISE_LONG_PRESS = 50
+TOYOTA_VIRTUAL_CRUISE_LONG_PRESS = 65
 CRUISE_NEAREST_FUNC = {
   ButtonType.accelCruise: math.ceil,
   ButtonType.decelCruise: math.floor,
@@ -43,6 +44,30 @@ class VCruiseHelper(VCruiseHelperSP):
   def v_cruise_initialized(self):
     return self.v_cruise_kph != V_CRUISE_UNSET
 
+  @property
+  def software_pcm_cruise_speed(self) -> bool:
+    return self.CP.brand == "toyota" and self.CP.pcmCruise and self.CP.openpilotLongitudinalControl and not self.CP_SP.pcmCruiseSpeed
+
+  @property
+  def cruise_long_press_frames(self) -> int:
+    return TOYOTA_VIRTUAL_CRUISE_LONG_PRESS if self.software_pcm_cruise_speed else CRUISE_LONG_PRESS
+
+  @property
+  def software_pcm_cruise_initialized(self) -> bool:
+    return 0 < self.v_cruise_kph < V_CRUISE_UNSET and 0 < self.v_cruise_cluster_kph < V_CRUISE_UNSET
+
+  def _apply_software_pcm_cruise_delta(self, delta_kph: float, is_metric: bool) -> None:
+    """Move Toyota's planner/display targets together while respecting both targets' bounds."""
+    cluster_min_kph = self.v_cruise_min if is_metric else self.v_cruise_min * CV.MPH_TO_KPH
+    min_delta = max(V_CRUISE_MIN - self.v_cruise_kph, cluster_min_kph - self.v_cruise_cluster_kph)
+    max_delta = min(V_CRUISE_MAX - self.v_cruise_kph, V_CRUISE_MAX - self.v_cruise_cluster_kph)
+    if delta_kph > 0:
+      applied_delta = min(delta_kph, max(0., max_delta))
+    else:
+      applied_delta = max(delta_kph, min(0., min_delta))
+    self.v_cruise_kph = round(self.v_cruise_kph + applied_delta, 1)
+    self.v_cruise_cluster_kph = round(self.v_cruise_cluster_kph + applied_delta, 1)
+
   def update_v_cruise(self, CS, enabled, is_metric):
     self.v_cruise_kph_last = self.v_cruise_kph
 
@@ -51,11 +76,21 @@ class VCruiseHelper(VCruiseHelperSP):
     _enabled = self.update_enabled_state(CS, enabled)
 
     if CS.cruiseState.available:
-      if not self.CP.pcmCruise or (not self.CP_SP.pcmCruiseSpeed and _enabled):
+      software_pcm_enabled = not self.CP_SP.pcmCruiseSpeed and _enabled
+      if self.software_pcm_cruise_speed:
+        software_pcm_enabled = software_pcm_enabled and self.software_pcm_cruise_initialized
+
+      if not self.CP.pcmCruise or software_pcm_enabled:
         # if stock cruise is completely disabled, then we can use our own set speed logic
         self._update_v_cruise_non_pcm(CS, _enabled, is_metric)
+        v_cruise_kph_before_sla = self.v_cruise_kph
         self.update_speed_limit_assist_v_cruise_non_pcm()
-        self.v_cruise_cluster_kph = self.v_cruise_kph
+        if self.software_pcm_cruise_speed:
+          sla_delta_kph = self.v_cruise_kph - v_cruise_kph_before_sla
+          self.v_cruise_kph = v_cruise_kph_before_sla
+          self._apply_software_pcm_cruise_delta(sla_delta_kph, is_metric)
+        else:
+          self.v_cruise_cluster_kph = self.v_cruise_kph
       else:
         self.v_cruise_kph = CS.cruiseState.speed * CV.MS_TO_KPH
         self.v_cruise_cluster_kph = CS.cruiseState.speedCluster * CV.MS_TO_KPH
@@ -85,13 +120,13 @@ class VCruiseHelper(VCruiseHelperSP):
 
     for b in CS.buttonEvents:
       if b.type.raw in self.button_timers and not b.pressed:
-        if self.button_timers[b.type.raw] > CRUISE_LONG_PRESS:
+        if self.button_timers[b.type.raw] > self.cruise_long_press_frames:
           return  # end long press
         button_type = b.type.raw
         break
     else:
       for k, timer in self.button_timers.items():
-        if timer and timer % CRUISE_LONG_PRESS == 0:
+        if timer and timer % self.cruise_long_press_frames == 0:
           button_type = k
           long_press = True
           break
@@ -115,10 +150,26 @@ class VCruiseHelper(VCruiseHelperSP):
       return
 
     long_press, v_cruise_delta = VCruiseHelperSP.update_v_cruise_delta(self, long_press, v_cruise_delta)
-    if long_press and self.v_cruise_kph % v_cruise_delta != 0:  # partial interval
-      self.v_cruise_kph = CRUISE_NEAREST_FUNC[button_type](self.v_cruise_kph / v_cruise_delta) * v_cruise_delta
+    # Toyota's canonical PCM set speed and displayed cluster set speed can differ. In
+    # software-owned PCM mode, round the value the driver sees and apply the same delta
+    # to both targets so the planner/cluster calibration offset remains intact.
+    v_cruise_reference = self.v_cruise_cluster_kph if self.software_pcm_cruise_speed else self.v_cruise_kph
+    if long_press and v_cruise_reference % v_cruise_delta != 0:  # partial interval
+      v_cruise_reference_new = CRUISE_NEAREST_FUNC[button_type](v_cruise_reference / v_cruise_delta) * v_cruise_delta
     else:
-      self.v_cruise_kph += v_cruise_delta * CRUISE_INTERVAL_SIGN[button_type]
+      v_cruise_reference_new = v_cruise_reference + v_cruise_delta * CRUISE_INTERVAL_SIGN[button_type]
+
+    if self.software_pcm_cruise_speed:
+      delta_kph = v_cruise_reference_new - v_cruise_reference
+
+      # If SET is pressed while overriding, do not lower the target below the current speed.
+      if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
+        delta_kph = max(delta_kph, CS.vEgo * CV.MS_TO_KPH - self.v_cruise_kph)
+
+      self._apply_software_pcm_cruise_delta(delta_kph, is_metric)
+      return
+
+    self.v_cruise_kph += v_cruise_reference_new - v_cruise_reference
 
     # If set is pressed while overriding, clip cruise speed to minimum of vEgo
     if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
@@ -127,6 +178,12 @@ class VCruiseHelper(VCruiseHelperSP):
     self.v_cruise_kph = np.clip(round(self.v_cruise_kph, 1), self.v_cruise_min, V_CRUISE_MAX)
 
   def update_button_timers(self, CS, enabled):
+    if self.software_pcm_cruise_speed and (not enabled or not CS.cruiseState.available or not self.software_pcm_cruise_initialized):
+      for k in self.button_timers:
+        self.button_timers[k] = 0
+        self.button_change_states[k] = {"standstill": False, "enabled": False}
+      return
+
     # increment timer for buttons still pressed
     for k in self.button_timers:
       if self.button_timers[k] > 0:

openpilot/selfdrive/controls/lib/drive_helpers.py

@@ -14,8 +14,11 @@ MAX_LATERAL_JERK = 5.0  # m/s^3
 MAX_LATERAL_ACCEL_NO_ROLL = 3.0  # m/s^2
 
 
+STOPPING_SPEED = 0.25  # m/s, speed at which the car goes into the stopping state
+
+
 def should_stop(v_ego: float, a_target: float) -> bool:
-  return bool(v_ego < 0.3 and a_target < 0.1)
+  return bool(v_ego < STOPPING_SPEED and a_target < 0.1)
 
 def clamp(val, min_val, max_val):
   clamped_val = float(np.clip(val, min_val, max_val))

openpilot/selfdrive/controls/lib/longcontrol.py

@@ -7,6 +7,8 @@ from openpilot.selfdrive.modeld.constants import ModelConstants
 
 CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
 
+STOPPING_DECEL_RATE = 0.3  # m/s^2/s while trying to stop
+
 LongCtrlState = car.CarControl.Actuators.LongControlState
 
 
@@ -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 -= STOPPING_DECEL_RATE * DT_CTRL
       self.reset()
 
     else:  # LongCtrlState.pid

openpilot/selfdrive/controls/lib/longitudinal_planner.py

@@ -37,7 +37,6 @@ def get_coast_accel(pitch):
 
 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)
-
   if not e2e:
     a_total_max = np.interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
     a_y = v_ego ** 2 * angle_steers * CV.DEG_TO_RAD / (CP.steerRatio * CP.wheelbase)
@@ -84,7 +83,8 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     v_ego = sm['carState'].vEgo
     v_cruise_kph = min(sm['carState'].vCruise, V_CRUISE_MAX)
     v_cruise = v_cruise_kph * CV.KPH_TO_MS
-    if sm['controlsState'].forceDecel:
+    force_decel = sm['controlsState'].forceDecel
+    if force_decel:
       v_cruise = 0.0
 
     long_control_off = sm['controlsState'].longControlState == LongCtrlState.off
@@ -118,6 +118,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     self.mpc.set_weights(prev_accel_constraint, personality=sm['selfdriveState'].personality)
     self.mpc.set_cur_state(self.v_desired_filter.x, self.output_a_target)
     self.mpc.update(sm['radarState'], personality=sm['selfdriveState'].personality)
+    self.update_dec(sm)
 
     self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
     self.a_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.a_solution)
@@ -140,9 +141,15 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
 
     is_e2e = self.is_e2e(sm)
 
-    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)
+    a_cruise_prev = self.a_cruise
+    gated_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego, a_cruise_prev, steer_angle_without_offset,
+                                    self.CP, self.dt, accel_coast, self.allow_throttle)
+    ungated_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego, a_cruise_prev, steer_angle_without_offset,
+                                      self.CP, self.dt, accel_coast, True)
+    self.a_cruise = self.arbitrate_cruise_candidate(
+      sm, gated_cruise, ungated_cruise, output_a_target_mpc, self.mpc.source,
+      allow_throttle=self.allow_throttle, e2e=is_e2e, force_decel=force_decel,
+    )
     cruise_should_stop = should_stop(v_ego, self.a_cruise)
 
     candidates = [(output_a_target_mpc, self.mpc.source, output_should_stop_mpc),
@@ -150,9 +157,11 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     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])
-    self.output_should_stop = any(should_stop for _, _, should_stop in candidates)
+    output_a_target, self.mpc.source, self.output_should_stop = min(candidates, key=lambda candidate: candidate[0])
+    output_a_target = self.accel_controller.limit_accel(output_a_target, v_ego)
+
     self.output_a_target = np.clip(output_a_target, ACCEL_MIN, ACCEL_MAX)
+    self.accel_controller_active = self.is_accel_controller_active(force_decel, self.output_a_target)
 
     self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.output_a_target + a_prev) / 2.0
 

openpilot/selfdrive/controls/tests/test_longcontrol.py

@@ -1,6 +1,7 @@
 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.selfdrive.controls.lib.drive_helpers import STOPPING_SPEED, should_stop
+from openpilot.selfdrive.controls.lib.longcontrol import STOPPING_DECEL_RATE, LongCtrlState, long_control_state_trans
 
 
 class TestLongControlStateTransition(OpenpilotTestCase):
@@ -42,3 +43,13 @@ 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 TestTerminalStop(OpenpilotTestCase):
+  def test_stopping_tune_is_gentler_than_upstream_default(self):
+    # Upstream #38394 hardcoded a 1.0 m/s^2/s ramp and a 0.3 m/s latch. comma's own one-stopping-tune uses
+    # 0.3 / 0.25, and every stop recorded on this car was driven with that pair. Both must stay on the less
+    # braking side, or a future edit re-deepens the terminal brake unnoticed - which already happened once.
+    assert 0.0 < STOPPING_DECEL_RATE <= 1.0
+    assert 0.0 < STOPPING_SPEED <= 0.3
+    assert should_stop(STOPPING_SPEED - 0.01, 0.0)
+    assert not should_stop(0.29, 0.0)  # the band upstream would latch in and we do not

openpilot/selfdrive/modeld/SConscript

@@ -7,14 +7,9 @@ from openpilot.common.file_chunker import chunk_file, get_chunk_targets, get_exi
 from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
 from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE, DM_INPUT_SIZE
 from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.selfdrive.modeld.helpers import TG_INPUT_DEVICES_PATH, usbgpu_present, modeld_pkl_path
+from openpilot.selfdrive.modeld.helpers import TG_INPUT_DEVICES_PATH, chestnut_present, modeld_pkl_path
 
 
-CAMERA_CONFIGS = [
-  (_ar_ox_fisheye.width, _ar_ox_fisheye.height),  # tici: 1928x1208
-  (_os_fisheye.width, _os_fisheye.height),        # mici: 1344x760
-]
-
 Import('env', 'arch')
 chunker_file = File("#openpilot/common/file_chunker.py")
 lenv = env.Clone()
@@ -24,30 +19,32 @@ tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "
                   if 'pycache' not in x and os.path.isfile(os.path.join(tinygrad_root, x))]
 
 def estimate_pickle_max_size(onnx_size):
-  return 1.2 * onnx_size  + 10 * 1024 * 1024  # 20% + 10MB is plenty
+  # QCOM programs for models with spatial recurrent features can approach 2x
+  # the ONNX size. Overestimating only adds an empty trailing chunk.
+  return 2.0 * onnx_size + 10 * 1024 * 1024
 
 if arch == 'comma_arm64':
+  from openpilot.common.hardware import HARDWARE
+  camera = _os_fisheye if HARDWARE.get_device_type() == "mici" else _ar_ox_fisheye
+  camera_configs = [(camera.width, camera.height)]
   tg_backend = 'QCOM'
   tg_flags = f'DEV={tg_backend} IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1'
 else:
+  camera_configs = [(c.width, c.height) for c in (_ar_ox_fisheye, _os_fisheye)]
   tg_backend = 'CPU'
   tg_flags = f'DEV=CPU' if arch == 'Darwin' else 'DEV=CPU:LLVM'
 
 tg_devices = { # which device to put jit inputs to at runtime
-  'openpilot.selfdrive.modeld.modeld': {
-    'default': {'WARP_DEV': tg_backend, 'QUEUE_DEV': tg_backend},
-    'usbgpu': {'WARP_DEV': tg_backend, 'QUEUE_DEV': 'AMD'}
-  },
   'openpilot.selfdrive.modeld.dmonitoringmodeld': {
     'default': {'DEV': tg_backend}
   },
 }
 
-USBGPU = usbgpu_present()
-if USBGPU:
-  usbgpu_tg_flags = f'DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV={tg_backend} FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2'
+CHESTNUT = chestnut_present()
+if CHESTNUT:
+  chestnut_tg_flags = 'DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1'
   # the USB+AMD GPU takes an exclusive flock; serialize all targets that touch it
-  usbgpu_lock = File("models/.usb_gpu.lock").abspath
+  chestnut_lock = File("models/.chestnut.lock").abspath
 
 def write_tg_devices(target, source, env):
   with open(str(target[0]), "w") as f:
@@ -73,44 +70,44 @@ compile_modeld_script = [
 model_w, model_h = MEDMODEL_INPUT_SIZE
 frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
 
-for usbgpu in [False, True] if USBGPU else [False]:
-  target_pkl_path = File(modeld_pkl_path(usbgpu)).abspath
-  # BIG_INTO_SMALL=1 builds the default target from the big model, e.g. to test it without a USB GPU
-  file_prefix, cmd_flags = ('big_', usbgpu_tg_flags) if usbgpu else ('big_' if os.getenv('BIG_INTO_SMALL') else '', tg_flags)
-  driving_onnx_deps = get_existing_chunks(File(f"models/{file_prefix}driving_supercombo.onnx").abspath)
-  camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in CAMERA_CONFIGS)
-  # CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
-  taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
-  cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 {modeld_dir}/compile_modeld.py '
-        f'--model-size {model_w}x{model_h} '
-        f'--camera-resolutions {camera_res_args} '
-        f'--onnx {File(f"models/{file_prefix}driving_supercombo.onnx").abspath} '
-        f'--output {target_pkl_path} --frame-skip {frame_skip}')
-  onnx_sizes_sum = sum(os.path.getsize(f) for f in driving_onnx_deps)
-  chunk_targets = get_chunk_targets(target_pkl_path, estimate_pickle_max_size(onnx_sizes_sum))
-  def do_compile(target, source, env, command=cmd, pkl=target_pkl_path, chunks=chunk_targets):
-    from openpilot.system.hardware.chestnut.flash import link_up
-    # chestnut can enumerate before its PCIe link is up due to varying 12V power behavior across cars
-    for _ in range(10):
-      if link_up():
-        break
-      time.sleep(1)
-    else:
-      print("Chestnut not ready, skipping big model build")
-      return
-    if ret := env.Execute(command):
-      return ret
-    chunk_file(pkl, chunks)
-  def do_chunk(target, source, env, pkl=target_pkl_path, chunks=chunk_targets):
-    chunk_file(pkl, chunks)
-  actions = Action(do_compile, "  [USBGPU] $TARGET") if usbgpu else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
-  node = lenv.Command(
-    chunk_targets,
-    tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
-    actions,
-  )
-  if usbgpu:
-    lenv.SideEffect(usbgpu_lock, node)
+if not os.getenv('SKIP_TINYGRAD_COMPILE'):
+  for chestnut in [False, True] if CHESTNUT else [False]:
+    target_pkl_path = File(modeld_pkl_path(chestnut)).abspath
+    file_prefix, cmd_flags = ('big_', chestnut_tg_flags) if chestnut else ('', tg_flags)
+    driving_onnx_deps = get_existing_chunks(File(f"models/{file_prefix}driving_supercombo.onnx").abspath)
+    camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in camera_configs)
+    # CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
+    taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
+    cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 {modeld_dir}/compile_modeld.py '
+          f'--model-size {model_w}x{model_h} '
+          f'--camera-resolutions {camera_res_args} '
+          f'--onnx {File(f"models/{file_prefix}driving_supercombo.onnx").abspath} '
+          f'--output {target_pkl_path} --frame-skip {frame_skip}')
+    onnx_sizes_sum = sum(os.path.getsize(f) for f in driving_onnx_deps)
+    chunk_targets = get_chunk_targets(target_pkl_path, estimate_pickle_max_size(onnx_sizes_sum))
+    def do_compile(target, source, env, command=cmd, pkl=target_pkl_path, chunks=chunk_targets):
+      from openpilot.system.hardware.chestnut.flash import link_up
+      # chestnut can enumerate before its PCIe link is up due to varying 12V power behavior across cars
+      for _ in range(10):
+        if link_up():
+          break
+        time.sleep(1)
+      else:
+        print("Chestnut not ready, skipping big model build")
+        return
+      if ret := env.Execute(command):
+        return ret
+      chunk_file(pkl, chunks)
+    def do_chunk(target, source, env, pkl=target_pkl_path, chunks=chunk_targets):
+      chunk_file(pkl, chunks)
+    actions = Action(do_compile, "  [CHESTNUT] $TARGET") if chestnut else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
+    node = lenv.Command(
+      chunk_targets,
+      tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(camera_res_args), Value(chunk_targets), chunker_file],
+      actions,
+    )
+    if chestnut:
+      lenv.SideEffect(chestnut_lock, node)
 
 # get model metadata
 fn = File(f"models/dmonitoring_model").abspath
@@ -120,7 +117,7 @@ lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files + script_file
 
 dm_w, dm_h = DM_INPUT_SIZE
 compile_dm_warp_script = [File(f"{modeld_dir}/compile_dm_warp.py")]
-for cam_w, cam_h in CAMERA_CONFIGS:
+for cam_w, cam_h in camera_configs:
   dm_pkl_path = File(f"models/dm_warp_{cam_w}x{cam_h}_tinygrad.pkl").abspath
   cmd = (f'{tg_flags} {mac_brew_string} python3 {modeld_dir}/compile_dm_warp.py '
          f'--camera-resolution {cam_w}x{cam_h} --warp-to {dm_w}x{dm_h} '

openpilot/selfdrive/modeld/compile_modeld.py

@@ -37,17 +37,12 @@ from tinygrad.engine.jit import TinyJit
 
 
 NV12Frame = namedtuple("NV12Frame", ['width', 'height', 'stride', 'y_height', 'uv_height', 'size'])
-WARP_INPUTS = ['tfm', 'big_tfm']
-POLICY_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']
-
-UV_SCALE_MATRIX = np.array([[0.5, 0, 0], [0, 0.5, 0], [0, 0, 1]], dtype=np.float32)
-UV_SCALE_MATRIX_INV = np.linalg.inv(UV_SCALE_MATRIX)
-
-WARP_DEV = os.getenv('WARP_DEV')
+MODELD_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']
 
 
-def make_random_images(keys, shape, device=None):
-  return {k: Tensor.randint(shape, low=0, high=256, dtype='uint8', device=device).realize() for k in keys}
+def nv12_copy_size(stride: int, y_height: int, uv_height: int) -> int:
+  # Retain the padded Y and UV plane storage, but skip the trailing kernel/guard allocation.
+  return stride * (y_height + uv_height)
 
 
 def warp_perspective_tinygrad(src_flat, M_inv, dst_shape, src_shape, stride_pad, border_fill_val=None):
@@ -99,7 +94,7 @@ def make_frame_prepare(nv12: NV12Frame, model_w, model_h):
 
   def frame_prepare_tinygrad(input_frame, M_inv):
     # UV_SCALE @ M_inv @ UV_SCALE_INV simplifies to elementwise scaling
-    M_inv_uv = M_inv * Tensor([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]], device=WARP_DEV)
+    M_inv_uv = M_inv * Tensor([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]], device=Device.DEFAULT)
     # deinterleave NV12 UV plane (UVUV... -> separate U, V)
     uv = input_frame[uv_offset:uv_offset + uv_height * stride].reshape(uv_height, stride)
     with Context(SPLIT_REDUCEOP=0):
@@ -118,49 +113,43 @@ def make_frame_prepare(nv12: NV12Frame, model_w, model_h):
   return frame_prepare_tinygrad
 
 
-def make_warp_input_queues(vision_input_shapes, frame_skip, device):
-  img = vision_input_shapes['img']  # (1, 12, 128, 256)
-  n_frames = img[1] // 6
-  img_buf_shape = (frame_skip * (n_frames - 1) + 1, 6, img[2], img[3])
-
-  npy = {
-    'tfm': np.zeros((3, 3), dtype=np.float32),
-    'big_tfm': np.zeros((3, 3), dtype=np.float32),
-  }
-  input_queues = {
-    'img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
-    'big_img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
-    **{k: Tensor(v, device='NPY').realize() for k, v in npy.items()},
-  }
-  return input_queues, npy
-
-
 def get_policy_npy_shapes(input_shapes):
   dp = input_shapes['desire_pulse']  # (1, 25, 8)
   tc = input_shapes['traffic_convention']  # (1, 2)
   at = input_shapes['action_t']  # (1, 2)
-  fb = input_shapes['features_buffer']  # (1, 24, 512)
+  fb = input_shapes['features_buffer']  # (1, T-1, ...) e.g. (1, 24, 32, 512) with spatial features
+  feat_dim = math.prod(fb[2:])
   # TODO prev_feat shouldn't exist and be handled inside the JIT, but corrupt on QCOM for now
-  shapes = {'desire': (dp[2],), 'traffic_convention': tuple(tc), 'action_t': tuple(at), 'prev_feat': (fb[0], fb[2])}
+  shapes = {'desire': (dp[2],), 'traffic_convention': tuple(tc), 'action_t': tuple(at), 'prev_feat': (fb[0], feat_dim)}
   return shapes, [math.prod(s) for s in shapes.values()]
 
 
-def make_input_queues(input_shapes, frame_skip, device):
-  input_queues, npy = make_warp_input_queues(input_shapes, frame_skip, device)
-
-  fb = input_shapes['features_buffer']  # (1, 24, 512), past features only; the model appends the current frame's feature
+def make_input_queues(input_shapes, frame_skip, device, frame_copy_size):
+  img = input_shapes['img']  # (1, 12, 128, 256)
+  fb = input_shapes['features_buffer']  # (1, T-1, ...), past features only; the model appends the current frame's feature
+  feat_dim = math.prod(fb[2:])
   dp = input_shapes['desire_pulse']  # (1, 25, 8)
+  n_frames = img[1] // 6
+  img_buf_shape = (frame_skip * (n_frames - 1) + 1, 6, img[2], img[3])
 
-  shapes, sizes = get_policy_npy_shapes(input_shapes)
-  packed_npy_inputs = np.zeros(sum(sizes), dtype=np.float32)
+  policy_shapes, _ = get_policy_npy_shapes(input_shapes)
+  shapes = {'tfm': (3, 3), 'big_tfm': (3, 3)} | policy_shapes
+  sizes = [math.prod(s) for s in shapes.values()]
+  packed_npy_size = sum(sizes) * np.dtype(np.float32).itemsize
+  packed_input = np.zeros(packed_npy_size + 2 * frame_copy_size, dtype=np.uint8)
+  packed_npy_inputs = packed_input[:packed_npy_size].view(np.float32)
+  frames = packed_input[packed_npy_size:]
+  frame_views = {'img': frames[:frame_copy_size], 'big_img': frames[frame_copy_size:]}
   # views into the packed inputs, to be refilled at runtime
-  npy.update({k: v.reshape(s) for (k, s), v in zip(shapes.items(), np.split(packed_npy_inputs, np.cumsum(sizes[:-1])), strict=True)})
-  input_queues.update({
-    'feat_q': Tensor(np.zeros((frame_skip * fb[1], fb[0], fb[2]), dtype=np.float32), device=device).contiguous().realize(),
+  npy = {k: v.reshape(s) for (k, s), v in zip(shapes.items(), np.split(packed_npy_inputs, np.cumsum(sizes[:-1])), strict=True)}
+  input_queues = {
+    'img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
+    'big_img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
+    'feat_q': Tensor(np.zeros((frame_skip * fb[1], fb[0], feat_dim), dtype=np.float32), device=device).contiguous().realize(),
     'desire_q': Tensor(np.zeros((frame_skip * dp[1], dp[0], dp[2]), dtype=np.float32), device=device).contiguous().realize(),
-    'packed_npy_inputs': Tensor(packed_npy_inputs, device='NPY').realize(),
-  })
-  return input_queues, npy
+    'packed_npy_inputs': Tensor(packed_input, device='NPY').realize(),
+  }
+  return input_queues, npy, frame_views
 
 
 def shift_and_sample(buf, new_val, sample_fn):
@@ -176,13 +165,15 @@ def sample_desire(buf, frame_skip):
   return buf.reshape(-1, frame_skip, *buf.shape[1:]).max(1).flatten(0, 1).unsqueeze(0)
 
 
-def make_warp(nv12, model_w, model_h, frame_skip):
+def make_warp(nv12, model_w, model_h):
   frame_prepare = make_frame_prepare(nv12, model_w, model_h)
 
   def warp(tfm, big_tfm, frame, big_frame):
-    tfm = tfm.to(WARP_DEV)
-    big_tfm = big_tfm.to(WARP_DEV)
-    Tensor.realize(tfm, big_tfm)
+    tfm = tfm.to(Device.DEFAULT)
+    big_tfm = big_tfm.to(Device.DEFAULT)
+    frame = frame.to(Device.DEFAULT)
+    big_frame = big_frame.to(Device.DEFAULT)
+    Tensor.realize(tfm, big_tfm, frame, big_frame)
 
     warped_frame = frame_prepare(frame, tfm).unsqueeze(0)
     warped_big_frame = frame_prepare(big_frame, big_tfm).unsqueeze(0)
@@ -195,10 +186,10 @@ def make_run_policy(model_runner, model_metadata, frame_skip):
   sample_desire_fn = partial(sample_desire, frame_skip=frame_skip)
   sample_skip_fn = partial(sample_skip, frame_skip=frame_skip)
   npy_shapes, npy_sizes = get_policy_npy_shapes(model_metadata['input_shapes'])
+  model_input_dtypes = {name: spec.dtype for name, spec in model_runner.graph_inputs.items()}
 
   def run_policy(warped, img_q, big_img_q, feat_q, desire_q, packed_npy_inputs):
     packed_npy_inputs = packed_npy_inputs.to(Device.DEFAULT)
-    warped = warped.to(Device.DEFAULT)
     Tensor.realize(packed_npy_inputs, warped)
 
     img = shift_and_sample(img_q, warped[0:1], sample_skip_fn)
@@ -211,33 +202,50 @@ def make_run_policy(model_runner, model_metadata, frame_skip):
     inputs = {
       'img': img,
       'big_img': big_img,
-      'features_buffer': feat_buf,
+      'features_buffer': feat_buf.reshape(model_metadata['input_shapes']['features_buffer']),
       'desire_pulse': desire_buf,
       'traffic_convention': traffic_convention,
       'action_t': action_t,
     }
+    inputs = {name: value.cast(model_input_dtypes[name]) for name, value in inputs.items()}
     out = next(iter(model_runner(inputs).values())).cast('float32')
     return out,
   return run_policy
 
 
-def compile_jit(jit, make_random_inputs, input_keys, make_queues):
-  SEED = 42
-  def random_inputs_run(fn, seed, test_val=None, test_buffers=None, expect_match=True):
-    input_queues, npy = make_queues(Device.DEFAULT)
-    rng = np.random.default_rng(seed)
-    Tensor.manual_seed(seed)
+def make_run_model(warp, run_policy, model_metadata, frame_copy_size):
+  _, policy_sizes = get_policy_npy_shapes(model_metadata['input_shapes'])
+  packed_npy_size = (18 + sum(policy_sizes)) * np.dtype(np.float32).itemsize
 
-    testing = test_val is not None or test_buffers is not None
-    n_runs = 1 if testing else 3
+  def run_model(img_q, big_img_q, feat_q, desire_q, packed_npy_inputs):
+    packed_input = packed_npy_inputs.to(Device.DEFAULT)
+    Tensor.realize(packed_input)
+    packed_npy_inputs = packed_input[:packed_npy_size].bitcast('float32')
+    frame = packed_input[packed_npy_size:packed_npy_size + frame_copy_size]
+    big_frame = packed_input[packed_npy_size + frame_copy_size:]
+    tfm, big_tfm, policy_inputs = packed_npy_inputs.split([9, 9, sum(policy_sizes)])
+    warped = warp(tfm.reshape(3, 3), big_tfm.reshape(3, 3), frame, big_frame)
+    return run_policy(warped, img_q, big_img_q, feat_q, desire_q, policy_inputs)
+  return run_model
+
+
+def compile_jit(jit, input_keys, make_queues, benchmark_runs):
+  if benchmark_runs < 1:
+    raise ValueError("benchmark_runs must be at least 1")
+
+  SEED = 42
+  def random_inputs_run(fn, seed, n_runs, test_val=None, test_buffers=None, expect_match=True):
+    input_queues, npy, frame_views = make_queues(Device.DEFAULT)
+    rng = np.random.default_rng(seed)
 
     for i in range(n_runs):
       for v in npy.values():
         v[:] = rng.standard_normal(v.shape).astype(v.dtype)
+      for v in frame_views.values():
+        v[:] = rng.integers(0, 256, size=v.shape, dtype=np.uint8)
       Device.default.synchronize()
-      random_inputs = make_random_inputs()
       st = time.perf_counter()
-      outs = fn(**{k: input_queues[k] for k in input_keys}, **random_inputs)
+      outs = fn(**{k: input_queues[k] for k in input_keys})
       mt = time.perf_counter()
       Device.default.synchronize()
       et = time.perf_counter()
@@ -256,14 +264,15 @@ def compile_jit(jit, make_random_inputs, input_keys, make_queues):
     return val, buffers
 
   print('capture + replay')
-  test_val, test_buffers = random_inputs_run(jit, SEED)
-  print('pickle round trip')
+  test_val, test_buffers = random_inputs_run(jit, SEED, 3)
+  print(f'pickle round trip ({benchmark_runs} runs per seed)')
   with tempfile.TemporaryFile(dir=".") as f:
     dump_oob(jit, f)
     f.seek(0)
-    jit = load_oob(f)
-  random_inputs_run(jit, SEED, test_val, test_buffers, expect_match=True)
-  random_inputs_run(jit, SEED+1, test_val, test_buffers, expect_match=False)
+    loaded_jit = load_oob(f)
+  random_inputs_run(loaded_jit, SEED, benchmark_runs, test_val, test_buffers, expect_match=True)
+  random_inputs_run(loaded_jit, SEED+1, benchmark_runs, test_val, test_buffers, expect_match=False)
+  # Keep the original so per-resolution JITs share model weight buffers in the final pickle.
   return jit
 
 
@@ -292,27 +301,31 @@ if __name__ == "__main__":
   p.add_argument('--onnx', required=True)
   p.add_argument('--output', required=True)
   p.add_argument('--frame-skip', type=int, required=True)
+  p.add_argument('--benchmark-runs', type=int, default=1,
+                 help='timed loaded-JIT runs for each correctness seed')
   args = p.parse_args()
 
   model_path = read_file_chunked_to_disk(args.onnx)
   model_w, model_h = args.model_size
 
   model_runner = OnnxRunner(model_path)
-  out = {'metadata': make_metadata_dict(model_path)}
+  out = {
+    'metadata': make_metadata_dict(model_path),
+    'input_devices': {'model': Device.DEFAULT},
+    'run_model': {},
+  }
 
-  run_policy_jit = TinyJit(make_run_policy(model_runner, out['metadata'], args.frame_skip), prune=True)
-
-  make_policy_queues = partial(make_input_queues, out['metadata']['input_shapes'], args.frame_skip)
-  make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, *out['metadata']['input_shapes']['img'][2:]), device=WARP_DEV)
-  out['run_policy'] = compile_jit(run_policy_jit, make_random_model_inputs, POLICY_INPUTS,
-                                  make_policy_queues)
+  run_policy = make_run_policy(model_runner, out['metadata'], args.frame_skip)
 
   for cam_w, cam_h in args.camera_resolutions:
     nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-    make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=nv12.size, device=WARP_DEV)
-    warp = TinyJit(make_warp(nv12, model_w, model_h, args.frame_skip), prune=True)
-    make_warp_queues = partial(make_warp_input_queues, out['metadata']['input_shapes'], args.frame_skip)
-    out[(cam_w,cam_h)] = compile_jit(warp, make_random_warp_inputs, WARP_INPUTS, make_warp_queues)
+    frame_copy_size = nv12_copy_size(nv12.stride, nv12.y_height, nv12.uv_height)
+    make_model_queues = partial(make_input_queues, out['metadata']['input_shapes'], args.frame_skip,
+                                frame_copy_size=frame_copy_size)
+    warp = make_warp(nv12, model_w, model_h)
+    run_model_jit = TinyJit(make_run_model(warp, run_policy, out['metadata'], frame_copy_size), prune=True)
+    out['run_model'][(cam_w,cam_h)] = compile_jit(run_model_jit, MODELD_INPUTS, make_model_queues,
+                                                  args.benchmark_runs)
 
   with open(args.output, "wb") as f:
     dump_oob(out, f)

openpilot/selfdrive/modeld/dmonitoringmodeld.py

@@ -29,7 +29,7 @@ class ModelState:
   output: np.ndarray
 
   def __init__(self, cam_w: int, cam_h: int):
-    self.DEV = get_tg_input_devices(PROCESS_NAME, usbgpu=False)['DEV']
+    self.DEV = get_tg_input_devices(PROCESS_NAME, chestnut=False)['DEV']
     with open(METADATA_PATH, 'rb') as f:
       model_metadata = pickle.load(f)
       self.input_shapes = model_metadata['input_shapes']

openpilot/selfdrive/modeld/fill_model_msg.py

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

openpilot/selfdrive/modeld/helpers.py

@@ -7,18 +7,20 @@ import tempfile
 from pathlib import Path
 
 from openpilot.common.file_chunker import get_manifest_path
-from openpilot.common.hardware.usb import CHESTNUT_FW_VERSION, CHESTNUT_USB_IDS, USB_DEVICES_PATH
+from openpilot.common.hardware.usb import CHESTNUT_USB_PRODUCT, USB_DEVICES_PATH, is_chestnut_usb_id
 
 MODELS_DIR = Path(__file__).resolve().parent / 'models'
 TG_INPUT_DEVICES_PATH = MODELS_DIR / 'tg_input_devices.json'
+CHESTNUT_POWERED_VOLTAGE = 5000
+CHESTNUT_PCIE_READY = 0x78
 
 
-def get_tg_input_devices(process_name: str, usbgpu: bool):
+def get_tg_input_devices(process_name: str, chestnut: bool):
   with open(TG_INPUT_DEVICES_PATH) as f:
-    return json.load(f)[process_name]['default' if not usbgpu else 'usbgpu']
+    return json.load(f)[process_name]['default' if not chestnut else 'chestnut']
 
-def modeld_pkl_path(usbgpu: bool):
-  prefix = 'big_' if usbgpu else ''
+def modeld_pkl_path(chestnut: bool):
+  prefix = 'big_' if chestnut else ''
   return MODELS_DIR / f'{prefix}driving_tinygrad.pkl'
 
 def dump_oob(obj, f):
@@ -45,16 +47,20 @@ def load_oob(f):
       yield pb
   return pickle.load(io.BytesIO(opcodes), buffers=buffers())
 
-def usbgpu_present() -> bool:
+def chestnut_present() -> bool:
   for d in USB_DEVICES_PATH.glob("*"):
     try:
       usb_id = (int((d / "idVendor").read_text(), 16), int((d / "idProduct").read_text(), 16))
       product = (d / "product").read_text().strip()
-      if usb_id in CHESTNUT_USB_IDS and product == f"custom {CHESTNUT_FW_VERSION}-CLEAN":
+      if is_chestnut_usb_id(*usb_id) and product == CHESTNUT_USB_PRODUCT:
         return True
     except Exception:
       pass
   return False
 
-def usbgpu_compiled() -> bool:
-  return Path(get_manifest_path(modeld_pkl_path(usbgpu=True))).is_file()
+def chestnut_compiled() -> bool:
+  return Path(get_manifest_path(modeld_pkl_path(chestnut=True))).is_file()
+
+
+def chestnut_ready(state) -> bool:
+  return state.supplyVoltage >= CHESTNUT_POWERED_VOLTAGE and not state.supplyFault and state.pcieLtssm == CHESTNUT_PCIE_READY

openpilot/selfdrive/modeld/modeld.py

@@ -1,9 +1,11 @@
 #!/usr/bin/env python3
+from collections.abc import Callable
+import ctypes
 from functools import cached_property
 import os
-os.environ['GMMU'] = '0' # for usbgpu fast loading, noop for qcom
-from tinygrad.tensor import Tensor
+os.environ['GMMU'] = '0' # for chestnut fast loading, noop for qcom
 from tinygrad.device import Device
+import usb1
 import struct
 import threading
 import time
@@ -26,17 +28,17 @@ from openpilot.common.transformations.model import get_warp_matrix
 from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
 from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan, should_stop, smooth_value, get_curvature_from_plan
 from openpilot.selfdrive.modeld.parse_model_outputs import Parser
-from openpilot.selfdrive.modeld.compile_modeld import make_input_queues, WARP_INPUTS, POLICY_INPUTS
+from openpilot.selfdrive.modeld.compile_modeld import make_input_queues, nv12_copy_size, MODELD_INPUTS
 from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_driving_model_data, fill_pose_msg, PublishState
 from openpilot.common.file_chunker import open_file_chunked
+from openpilot.common.hardware.usb import CHESTNUT_USB_IDS
 from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
-from openpilot.selfdrive.modeld.helpers import usbgpu_present, usbgpu_compiled, modeld_pkl_path, get_tg_input_devices, load_oob
+from openpilot.selfdrive.modeld.helpers import chestnut_present, chestnut_compiled, chestnut_ready, modeld_pkl_path, load_oob
 
 from openpilot.sunnypilot.livedelay.helpers import get_lat_delay
 from openpilot.sunnypilot.modeld_v2.modeld_base import ModelStateBase
 from openpilot.sunnypilot.selfdrive.controls.lib.relc import RoadEdgeLaneChangeController
 
-PROCESS_NAME = "openpilot.selfdrive.modeld.modeld"
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
 
 LAT_SMOOTH_SECONDS = 0.0
@@ -81,6 +83,37 @@ class ChestnutState:
     self.valid = True
     self.sends = 0
     self.metrics = {}
+    self._asm_usb = None
+
+  def _close_asm_usb(self) -> None:
+    if self._asm_usb is not None:
+      self._asm_usb.close()
+      self._asm_usb = None
+
+  def _open_asm_usb(self):
+    context = usb1.USBContext()
+    for vendor_id, product_id in CHESTNUT_USB_IDS:
+      if (handle := context.openByVendorIDAndProductID(vendor_id, product_id, skip_on_error=True)) is not None:
+        return handle
+    context.close()
+
+  def _read_ina(self) -> tuple[int, int, bool]:
+    if "AMD" in Device._opened_devices and self._asm_usb is None:
+      try:
+        raw = Device["AMD"].iface.pci_dev.usb.usb.control_read(0xC0, 5)
+        return struct.unpack('<Hh?', bytes(raw))
+      except Exception:
+        pass
+    if self._asm_usb is None:
+      self._asm_usb = self._open_asm_usb()
+    if self._asm_usb is None:
+      raise usb1.USBErrorNoDevice
+    try:
+      raw = self._asm_usb.controlRead(0xC0, 0xC0, 0, 0, 5, timeout=100)
+    except usb1.USBError:
+      self._close_asm_usb()
+      raise
+    return struct.unpack('<Hh?', bytes(raw))
 
   @cached_property
   def power_limit(self) -> int:
@@ -94,8 +127,10 @@ class ChestnutState:
     if self.big and "AMD" in Device._opened_devices and self.sends % 100 == 1:
       try:
         smu = Device["AMD"].iface.dev_impl.smu
+        metrics_t = smu.smu_mod.SmuMetricsExternal_t
         smu._send_msg(smu.smu_mod.PPSMC_MSG_TransferTableSmu2Dram, smu.smu_mod.TABLE_SMU_METRICS, timeout=100)
-        metrics = smu.read_table(smu.smu_mod.SmuMetricsExternal_t, smu.smu_mod.TABLE_SMU_METRICS).SmuMetrics
+        metrics_buf = bytearray(smu.adev.vram.view(smu.driver_table_paddr, ctypes.sizeof(metrics_t))[:])
+        metrics = metrics_t.from_buffer(metrics_buf).SmuMetrics
         self.metrics = {'tempC': metrics.AvgTemperature[smu.smu_mod.TEMP_HOTSPOT],
                         'memoryTempC': metrics.AvgTemperature[smu.smu_mod.TEMP_MEM],
                         'powerDrawW': metrics.AverageSocketPower,
@@ -114,13 +149,15 @@ class ChestnutState:
         setattr(state, k, v)
 
     asm_valid = False
+    try:
+      # ASM runs on USB-C power, these still read without a gpu
+      state.supplyVoltage, state.supplyCurrent, state.supplyFault = self._read_ina()
+      asm_valid = True
+    except Exception:
+      pass
     if "AMD" in Device._opened_devices:
       try:
-        # ASM runs on USB-C power, these still read without a gpu
-        asm = Device["AMD"].iface.pci_dev.usb
-        state.pcieLtssm = asm.read(0xB450, 1)[0]
-        state.supplyVoltage, state.supplyCurrent = struct.unpack('<Hh', bytes(asm.usb.control_read(0xC0, 5))[:4])
-        asm_valid = True
+        state.pcieLtssm = Device["AMD"].iface.pci_dev.usb.read(0xB450, 1)[0]
       except Exception:
         pass
 
@@ -141,42 +178,34 @@ class FrameMeta:
 class ModelState(ModelStateBase):
   prev_desire: np.ndarray  # for tracking the rising edge of the pulse
 
-  def __init__(self, cam_w: int, cam_h: int, usbgpu: bool):
+  def __init__(self, cam_w: int, cam_h: int, chestnut: bool):
     ModelStateBase.__init__(self)
-    input_devices = get_tg_input_devices(PROCESS_NAME, usbgpu)
-    self.WARP_DEV, self.QUEUE_DEV = input_devices['WARP_DEV'], input_devices['QUEUE_DEV']
-    jits = load_oob(open_file_chunked(modeld_pkl_path(usbgpu)))
+    jits = load_oob(open_file_chunked(modeld_pkl_path(chestnut)))
+    input_devices = jits['input_devices']
+    self.model_device = input_devices['model']
     metadata = jits['metadata']
     self.input_shapes = metadata['input_shapes']
     self.vision_input_names = [k for k in self.input_shapes if 'img' in k]
     self.output_slices = metadata['output_slices']
 
     self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32)
-    self.usbgpu = usbgpu
+    self.chestnut = chestnut
 
     self.frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
-    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
-    self.full_frames: dict[str, Tensor] = {}
-    self._blob_cache: dict[tuple[str, int], Tensor] = {}
+    self.frame_copy_size = nv12_copy_size(*get_nv12_info(cam_w, cam_h)[:3])
+    self.input_queues, self.npy, self.frame_views = make_input_queues(
+      self.input_shapes, self.frame_skip, device=self.model_device, frame_copy_size=self.frame_copy_size)
     self.parser = Parser()
-    self.frame_buf_params = {k: get_nv12_info(cam_w, cam_h) for k in ('img', 'big_img')}
-    self.run_policy = jits['run_policy']
-    self.warp = jits[(cam_w,cam_h)]
+    self.run_model = jits['run_model'][(cam_w,cam_h)]
 
   def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]:
     parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in output_slices.items()}
     return parsed_model_outputs
 
   def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray],
-          inputs: dict[str, np.ndarray]) -> dict[str, np.ndarray] | None:
-    for key in bufs.keys():
-      ptr = np.frombuffer(bufs[key].data, dtype=np.uint8).ctypes.data
-      yuv_size = self.frame_buf_params[key][3]
-      # There is a ringbuffer of imgs, just cache tensors pointing to all of them
-      cache_key = (key, ptr)
-      if cache_key not in self._blob_cache:
-        self._blob_cache[cache_key] = Tensor.from_blob(ptr, (yuv_size,), dtype='uint8', device=self.WARP_DEV)
-      self.full_frames[key] = self._blob_cache[cache_key]
+          inputs: dict[str, np.ndarray], after_enqueue: Callable[[], None] | None = None) -> dict[str, np.ndarray]:
+    for key, buf in bufs.items():
+      np.copyto(self.frame_views[key], np.frombuffer(buf.data, dtype=np.uint8, count=self.frame_copy_size))
 
     # Model decides when action is completed, so desire input is just a pulse triggered on rising edge
     inputs['desire_pulse'][0] = 0
@@ -187,16 +216,12 @@ class ModelState(ModelStateBase):
     self.npy['tfm'][:,:] = transforms['img'][:,:]
     self.npy['big_tfm'][:,:] = transforms['big_img'][:,:]
 
-    warped = self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames['img'], big_frame=self.full_frames['big_img'])
-
-    outs, = self.run_policy(
-      **{k: self.input_queues[k] for k in POLICY_INPUTS if k in self.input_queues}, warped=warped
-    )
+    outs, = self.run_model(**{k: self.input_queues[k] for k in MODELD_INPUTS})
+    if after_enqueue is not None:
+      after_enqueue()
     model_output = outs.numpy()[0]
-    if self.usbgpu and not np.all(np.isfinite(model_output)):
-      # TODO remove with prev_feat
-      cloudlog.error("model output not finite, dropping frame")
-      return None
+    if self.chestnut and not np.all(np.isfinite(model_output)):
+      raise RuntimeError("model output not finite")
     outputs_dict = self.parser.parse_outputs(self.slice_outputs(model_output, self.output_slices))
     self.npy['prev_feat'][:] = model_output[self.output_slices['hidden_state']]
 
@@ -205,25 +230,37 @@ class ModelState(ModelStateBase):
     return outputs_dict
 
   def warmup(self) -> None:
-    dummy_frames = {k: np.zeros(self.frame_buf_params[k][3], dtype=np.uint8) for k in self.vision_input_names}
+    dummy_frames = {k: np.zeros(self.frame_copy_size, dtype=np.uint8) for k in self.vision_input_names}
     eye = np.eye(3, dtype=np.float32)
     dims = {'desire_pulse': ModelConstants.DESIRE_LEN, 'traffic_convention': 2, 'action_t': 2}
     self.run(dummy_frames, dict.fromkeys(self.vision_input_names, eye), {k: np.zeros(v, dtype=np.float32) for k, v in dims.items()})
-    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
+    self.input_queues, self.npy, self.frame_views = make_input_queues(
+      self.input_shapes, self.frame_skip, device=self.model_device, frame_copy_size=self.frame_copy_size)
     self.prev_desire[:] = 0
-    self.full_frames.clear()
-    self._blob_cache.clear()
 
 
 def main(demo=False):
   cloudlog.warning("modeld init")
 
-  USBGPU = usbgpu_present() and usbgpu_compiled()
-  if USBGPU:
+  chestnut_available = chestnut_present() and chestnut_compiled()
+  CHESTNUT = False
+  if chestnut_available:
+    poller = messaging.Poller()
+    sock = messaging.sub_sock("chestnutState", poller=poller, conflate=True)
+    deadline = time.monotonic() + 4. / SERVICE_LIST['deviceState'].frequency
+    while not CHESTNUT and (remaining := deadline - time.monotonic()) > 0.:
+      if not poller.poll(round(remaining * 1000)):
+        break
+      msg = messaging.recv_one_or_none(sock)
+      CHESTNUT = msg is not None and msg.valid and chestnut_ready(msg.chestnutState)
+  if CHESTNUT:
     os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
   params = Params()
-  params.put_bool("UsbGpuLoading", USBGPU)
-  params.remove("UsbGpuActive")
+  params.put_bool("ChestnutLoading", CHESTNUT)
+  if chestnut_available and not CHESTNUT:
+    params.put_bool("ChestnutActive", False)
+  else:
+    params.remove("ChestnutActive")
 
   config_realtime_process(7, 54)
 
@@ -253,7 +290,7 @@ def main(demo=False):
   st = time.monotonic()
   cloudlog.warning("loading model")
   model = None
-  if USBGPU:
+  if CHESTNUT:
     big_model = None
     def load_big():
       nonlocal big_model
@@ -267,23 +304,27 @@ def main(demo=False):
     loader.start()
     loader.join(BIG_MODEL_TIMEOUT)
     model = big_model
-    params.put_bool("UsbGpuActive", model is not None)
+    if model is None:
+      params.put_bool("ChestnutModelError", True)
+    params.put_bool("ChestnutActive", model is not None)
+    if model is not None:
+      params.remove("ChestnutModelError")
 
-  small_model = ModelState(vipc_client_main.width, vipc_client_main.height, False) if model is None or USBGPU else None
+  small_model = ModelState(vipc_client_main.width, vipc_client_main.height, False) if model is None or CHESTNUT else None
   if model is None:
     model = small_model
-  params.put_bool("UsbGpuLoading", False)
+  params.put_bool("ChestnutLoading", False)
   assert model is not None
   cloudlog.warning(f"models loaded in {time.monotonic() - st:.1f}s, modeld starting")
 
   # messaging
-  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if USBGPU else [])
+  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if CHESTNUT else [])
   pm = PubMaster(pub_socks)
   sm = SubMaster(["deviceState", "carState", "narrowRoadCameraState", "extrinsicsCalibration", "driverMonitoringState", "carControl", "lateralDelay"])
 
   publish_state = PublishState()
   params = Params()
-  chestnut_state = ChestnutState(pm, model.usbgpu) if USBGPU else None
+  chestnut_state = ChestnutState(pm, model.chestnut) if CHESTNUT else None
 
   # setup filter to track dropped frames
   frame_dropped_filter = FirstOrderFilter(0., 10., 1. / ModelConstants.MODEL_RUN_FREQ)
@@ -393,13 +434,16 @@ def main(demo=False):
 
     mt1 = time.perf_counter()
     try:
-      model_output = model.run(bufs, transforms, inputs)
+      send_chestnut = (chestnut_state is not None and
+                       run_count % round(ModelConstants.MODEL_RUN_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0)
+      model_output = model.run(bufs, transforms, inputs, chestnut_state.send if send_chestnut else None)
     except Exception:
-      if not params.get_bool("UsbGpuActive"):
+      if not params.get_bool("ChestnutActive"):
         raise
       # fallback to small model
       cloudlog.exception("big model failed, fall back to small")
-      params.put_bool("UsbGpuActive", False)
+      params.put_bool("ChestnutModelError", True)
+      params.put_bool("ChestnutActive", False)
       assert small_model is not None
       model = small_model
       if chestnut_state is not None:
@@ -419,18 +463,17 @@ def main(demo=False):
       fill_model_msg(modelv2_send, model_output, action,
                      publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
                      frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, extrinsics_calibration_seen)
-      modelv2_send.modelV2.big = model.usbgpu
+      modelv2_send.modelV2.big = model.chestnut
 
       desire_state = modelv2_send.modelV2.meta.desireState
       l_lane_change_prob = desire_state[log.Desire.laneChangeLeft]
       r_lane_change_prob = desire_state[log.Desire.laneChangeRight]
       lane_change_prob = l_lane_change_prob + r_lane_change_prob
-      DH.update(sm['carState'], sm['carControl'].latActive, lane_change_prob)
-      modelv2_send.modelV2.meta.laneChangeState = DH.lane_change_state
-      modelv2_send.modelV2.meta.laneChangeDirection = DH.lane_change_direction
-
       mdv2sp_send = messaging.new_message('modelDataV2SP')
       left_edge, right_edge = RELC.update_and_fill(modelv2_send.modelV2, mdv2sp_send.modelDataV2SP, v_ego)
+      DH.update(sm['carState'], sm['carControl'].latActive, lane_change_prob, left_edge, right_edge)
+      modelv2_send.modelV2.meta.laneChangeState = DH.lane_change_state
+      modelv2_send.modelV2.meta.laneChangeDirection = DH.lane_change_direction
       mdv2sp_send.modelDataV2SP.laneTurnDirection = DH.lane_turn_direction
 
       fill_driving_model_data(drivingdata_send, modelv2_send)
@@ -441,10 +484,6 @@ def main(demo=False):
       pm.send('modelDataV2SP', mdv2sp_send)
     last_vipc_frame_id = meta_main.frame_id
 
-    if chestnut_state is not None and run_count % round(ModelConstants.MODEL_RUN_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0:
-      chestnut_state.send()
-
-
 if __name__ == "__main__":
   try:
     import argparse

openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a501760a9d1d5fef0eab2b8c5d122d06124fc26dc8e0782e0aa94b82a208f0ff
-size 1757355221
+oid sha256:1791d5940b2c048d0639813426dd2cf1d6f2a6727ed51e17c8bcea8bbe754123
+size 765950064

openpilot/selfdrive/pandad/pandad.cc

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

openpilot/selfdrive/pandad/spi.cc

@@ -29,12 +29,6 @@ enum SpiError {
 
 const unsigned int SPI_ACK_TIMEOUT = 500; // milliseconds
 const std::string SPI_DEVICE = "/dev/spidev0.0";
-// TODO: fix SPI turnaround synchronization at the protocol level.
-static uint64_t spi_last_bus_activity_ns = 0;  // protected by hw_lock
-
-static void wait_for_spi_turnaround(uint64_t start_ns) {
-  while ((nanos_since_boot() - start_ns) < 400000) {}
-}
 
 class LockEx {
 public:
@@ -325,8 +319,6 @@ int PandaSpiHandle::spi_transfer(uint8_t endpoint, uint8_t *tx_data, uint16_t tx
   assert(tx_len < SPI_BUF_SIZE);
   assert(max_rx_len < SPI_BUF_SIZE);
 
-  wait_for_spi_turnaround(spi_last_bus_activity_ns);
-
   xfer_count++;
   header = {
     .sync = SPI_SYNC,
@@ -355,7 +347,6 @@ int PandaSpiHandle::spi_transfer(uint8_t endpoint, uint8_t *tx_data, uint16_t tx
   if (ret < 0) {
     goto fail;
   }
-  wait_for_spi_turnaround(nanos_since_boot());
 
   // Send data
   if (tx_data != NULL) {
@@ -398,7 +389,6 @@ int PandaSpiHandle::spi_transfer(uint8_t endpoint, uint8_t *tx_data, uint16_t tx
     memcpy(rx_data, rx_buf + 3, rx_data_len);
   }
 
-  spi_last_bus_activity_ns = nanos_since_boot();
   return rx_data_len;
 
 fail:
@@ -413,7 +403,6 @@ fail:
     }
   }
 
-  spi_last_bus_activity_ns = nanos_since_boot();
   if (ret >= 0) ret = -1;
   return ret;
 }

openpilot/selfdrive/selfdrived/alerts_offroad.json

@@ -19,6 +19,30 @@
   },
   "Offroad_ChestnutBranch": {
     "text": "Chestnut detected! Switch to the %1 branch to use chestnut-class models.",
+    "severity": -1
+  },
+  "Offroad_ChestnutNotDetected": {
+    "text": "Chestnut not detected. Check USB and 12V connections.",
+    "severity": 0
+  },
+  "Offroad_ChestnutOverheated": {
+    "text": "Chestnut overheated. Ensure good airflow. Current GPU temperature is %1.",
+    "severity": 0
+  },
+  "Offroad_ChestnutPcieUnavailable": {
+    "text": "%1",
+    "severity": 0
+  },
+  "Offroad_ChestnutUncompiled": {
+    "text": "Chestnut model not compiled. Keep ignition on and reboot the comma.",
+    "severity": 0
+  },
+  "Offroad_ChestnutUpdateFailed": {
+    "text": "Chestnut update failed. Check the USB cable.",
+    "severity": 0
+  },
+  "Offroad_ChestnutUsbSlow": {
+    "text": "Chestnut USB link is slow. Check the USB cable. The current speed is %1.",
     "severity": 0
   },
   "Offroad_UnregisteredHardware": {

openpilot/selfdrive/selfdrived/selfdrived.py

@@ -195,17 +195,18 @@ class SelfdriveD(CruiseHelper):
       self.events.add(EventName.joystickDebug)
       self.startup_event = None
 
-    loading = self.params.get_bool("UsbGpuLoading")
+    loading = self.params.get_bool("ChestnutLoading")
     if self.big_model_loading and not loading:
       self.big_model_ready_t = time.monotonic()
+      self.events_sp.add(custom.OnroadEventSP.EventName.bigModelReady)
     self.big_model_loading = loading
     if self.big_model_loading:
       self.events.add(EventName.bigModelLoading)
 
-    big_active = self.params.get("UsbGpuActive")
-    usbgpu_present = self.sm['deviceState'].chestnutPresent
+    big_active = self.params.get("ChestnutActive")
+    chestnut_present = self.sm['deviceState'].chestnutPresent
     model_unavailable = big_active is True and self.sm.seen['modelV2'] and not self.sm.alive['modelV2']
-    big_failed = big_active is False or model_unavailable or (self.big_model_active and not usbgpu_present)
+    big_failed = big_active is False or model_unavailable or (self.big_model_active and not chestnut_present)
     if big_failed and not self.big_model_failed:
       self.events.add(EventName.bigModelFailed)
     self.big_model_failed = big_failed

openpilot/selfdrive/test/longitudinal_maneuvers/plant.py

@@ -11,6 +11,15 @@ from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPl
 from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
 
 
+class PlannerSM(dict):
+  def __init__(self, radar_frame: int, services: dict):
+    super().__init__(services)
+    self.frame = radar_frame
+    self.logMonoTime = {"radarState": radar_frame}
+    self.valid = {"radarState": True}
+    self.alive = {"radarState": True}
+
+
 class Plant:
   messaging_initialized = False
 
@@ -132,7 +141,7 @@ class Plant:
     car_control.carControl.orientationNED = [0., float(pitch), 0.]
 
     # ******** get controlsState messages for plotting ***
-    sm = {'radarState': radar.radarState,
+    sm = PlannerSM(self.rk.frame, {'radarState': radar.radarState,
           'carState': car_state.carState,
           'carControl': car_control.carControl,
           'controlsState': control.controlsState,
@@ -141,7 +150,7 @@ class Plant:
           'modelV2': model.modelV2,
           'carStateSP': car_state_sp.carStateSP,
           'liveMapDataSP': live_map_data_sp.liveMapDataSP,
-          'gpsLocation': gps_data.gpsLocation}
+          'gpsLocation': gps_data.gpsLocation})
     self.planner.update(sm)
     self.acceleration = self.planner.output_a_target
     if self.planner.output_should_stop:

openpilot/selfdrive/test/process_replay/migration.py

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

openpilot/selfdrive/test/process_replay/model_replay.py

@@ -33,9 +33,9 @@ MODEL_REPLAY_BUCKET="model_replay_master"
 GITHUB = GithubUtils(API_TOKEN, DATA_TOKEN)
 
 EXEC_TIMINGS = [
-  # model, instant max, average max
-  ("modelV2", 0.05, 0.028),
-  ("driverStateV2", 0.05, 0.018),
+  # model, instant max, average max, chestnut average max
+  ("modelV2", 0.05, 0.03, 0.05),
+  ("driverStateV2", 0.05, 0.018, 0.018),
 ]
 
 def get_log_fn(test_route, ref="master"):
@@ -169,11 +169,13 @@ def model_replay(lr, frs):
   dmonitoringmodeld_msgs = replay_process(dmonitoringmodeld, dmodeld_logs, frs)
 
   msgs = modeld_msgs + dmonitoringmodeld_msgs
+  chestnut = any(m.modelV2.big for m in modeld_msgs if m.which() == "modelV2")
 
   header = ['model', 'max instant', 'max instant allowed', 'average', 'max average allowed', 'test result']
   rows = []
   timings_ok = True
-  for (s, instant_max, avg_max) in EXEC_TIMINGS:
+  for (s, instant_max, avg_max, chestnut_avg_max) in EXEC_TIMINGS:
+    avg_max = chestnut_avg_max if chestnut else avg_max
     ts = [getattr(m, s).modelExecutionTime for m in msgs if m.which() == s]
     # TODO some init can happen in first iteration
     ts = ts[1:]

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

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

openpilot/selfdrive/ui/layouts/home.py

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

openpilot/selfdrive/ui/layouts/onboarding.py

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

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

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

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

@@ -27,6 +27,12 @@ DESCRIPTIONS = {
     "In relaxed mode sunnypilot will stay further away from lead cars. On supported cars, you can cycle through these personalities with " +
     "your steering wheel distance button."
   ),
+  "AccelPersonalityEnabled": tr_noop(
+    "Lets you choose how sunnypilot starts, catches up, and settles at the cruise speed. Emergency braking and stopping are unchanged."
+  ),
+  "AccelPersonality": tr_noop(
+    "Eco is gentlest, Normal balances a prompt start with smooth catch-up, and Sport is more responsive."
+  ),
   "IsLdwEnabled": tr_noop(
     "Receive alerts to steer back into the lane when your vehicle drifts over a detected lane line " +
     "without a turn signal activated while driving over 31 mph (50 km/h)."
@@ -106,6 +112,24 @@ class TogglesLayout(Widget):
       icon="speed_limit.png"
     )
 
+    self._accel_controller_enabled = toggle_item(
+      lambda: tr("Enable Accel Controller"),
+      lambda: tr(DESCRIPTIONS["AccelPersonalityEnabled"]),
+      self._params.get_bool("AccelPersonalityEnabled"),
+      callback=self._set_accel_controller_enabled,
+      icon="speed_limit.png",
+    )
+
+    self._accel_personality_setting = multiple_button_item(
+      lambda: tr("Acceleration Profile"),
+      lambda: tr(DESCRIPTIONS["AccelPersonality"]),
+      buttons=[lambda: tr("Eco"), lambda: tr("Normal"), lambda: tr("Sport")],
+      button_width=300,
+      callback=self._set_accel_personality,
+      selected_index=self._params.get("AccelPersonality", return_default=True),
+      icon="speed_limit.png"
+    )
+
     self._toggles = {}
     self._locked_toggles = set()
     for param, (title, desc, icon, needs_restart) in self._toggle_defs.items():
@@ -135,9 +159,11 @@ class TogglesLayout(Widget):
 
       self._toggles[param] = toggle
 
-      # insert longitudinal personality after NDOG toggle
+      # insert longitudinal personality and Accel Controller settings after NDOG toggle
       if param == "DisengageOnAccelerator":
         self._toggles["LongitudinalPersonality"] = self._long_personality_setting
+        self._toggles["AccelPersonalityEnabled"] = self._accel_controller_enabled
+        self._toggles["AccelPersonality"] = self._accel_personality_setting
 
     self._update_experimental_mode_icon()
     self._scroller = Scroller(list(self._toggles.values()), line_separator=True, spacing=0)
@@ -158,6 +184,7 @@ class TogglesLayout(Widget):
 
   def _update_toggles(self):
     ui_state.update_params()
+    accel_controller_enabled = self._params.get_bool("AccelPersonalityEnabled")
 
     e2e_description = tr(
       "sunnypilot defaults to driving in chill mode. Experimental mode enables alpha-level features that aren't ready for chill mode. " +
@@ -176,11 +203,15 @@ class TogglesLayout(Widget):
         self._toggles["ExperimentalMode"].action_item.set_enabled(True)
         self._toggles["ExperimentalMode"].set_description(e2e_description)
         self._long_personality_setting.action_item.set_enabled(True)
+        self._accel_controller_enabled.action_item.set_enabled(True)
+        self._accel_personality_setting.action_item.set_enabled(True)
       else:
         # no long for now
         self._toggles["ExperimentalMode"].action_item.set_enabled(False)
         self._toggles["ExperimentalMode"].action_item.set_state(False)
         self._long_personality_setting.action_item.set_enabled(False)
+        self._accel_controller_enabled.action_item.set_enabled(False)
+        self._accel_personality_setting.action_item.set_enabled(False)
         self._params.remove("ExperimentalMode")
 
         unavailable = tr("Experimental mode is currently unavailable on this car since the car's stock ACC is used for longitudinal control.")
@@ -203,6 +234,8 @@ class TogglesLayout(Widget):
     # refresh toggles from params to mirror external changes
     for param in self._toggle_defs:
       self._toggles[param].action_item.set_state(self._params.get_bool(param))
+    self._accel_controller_enabled.action_item.set_state(accel_controller_enabled)
+    self._accel_personality_setting.action_item.set_selected_button(self._params.get("AccelPersonality", return_default=True))
 
     # these toggles need restart, block while engaged
     for toggle_def in self._toggle_defs:
@@ -247,3 +280,9 @@ class TogglesLayout(Widget):
 
   def _set_longitudinal_personality(self, button_index: int):
     self._params.put("LongitudinalPersonality", button_index, block=True)
+
+  def _set_accel_personality(self, button_index: int):
+    self._params.put("AccelPersonality", button_index, block=True)
+
+  def _set_accel_controller_enabled(self, state: bool):
+    self._params.put_bool("AccelPersonalityEnabled", state, block=True)

openpilot/selfdrive/ui/layouts/sidebar.py

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

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

@@ -1,4 +1,5 @@
 import datetime
+import math
 import time
 
 from openpilot.cereal import log
@@ -8,8 +9,8 @@ from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.layouts import HBoxLayout
 from openpilot.system.ui.widgets.icon_widget import IconWidget
 from openpilot.system.ui.widgets.label import UnifiedLabel, gui_label
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
-from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos, TextAlignment, TextAlignmentVertical
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.common.version import RELEASE_BRANCHES
 
 HEAD_BUTTON_FONT_SIZE = 40
@@ -69,8 +70,8 @@ class AlertsPill(Widget):
 
       count_rect = rl.Rectangle(self.rect.x + self.COUNT_OFFSET, self.rect.y, pill_w - self.COUNT_OFFSET, pill_h)
       gui_label(count_rect, str(alert_count), font_size=36,
-                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                alignment=TextAlignment.CENTER,
+                alignment_vertical=TextAlignmentVertical.MIDDLE)
 
 
 class NetworkIcon(Widget):
@@ -139,8 +140,10 @@ class MiciHomeLayout(Widget):
     self._version_text = self._get_version_text()
 
     self._experimental_icon = IconWidget("icons_mici/experimental_mode.png", (48, 48))
-    self._egpu_icon = IconWidget("icons_mici/egpu_green.png", (50, 37))
-    self._egpu_icon_gray = IconWidget("icons_mici/egpu_gray.png", (50, 37))
+    self._usb_icon = IconWidget("icons_mici/usb.png", (62, 40))
+    self._chestnut_icon = IconWidget("icons_mici/chestnut_green.png", (68, 40))
+    self._chestnut_loading_icon = IconWidget("icons_mici/chestnut.png", (68, 40))
+    self._chestnut_failed_icon = IconWidget("icons_mici/chestnut_orange.png", (68, 40))
     self._mic_icon = IconWidget("icons_mici/microphone.png", (32, 46))
     self._body_icon = IconWidget("icons_mici/body.png", (54, 37))
 
@@ -150,13 +153,15 @@ class MiciHomeLayout(Widget):
       IconWidget("icons_mici/settings.png", (48, 48), opacity=0.9),
       NetworkIcon(),
       self._experimental_icon,
-      self._egpu_icon,
-      self._egpu_icon_gray,
+      self._usb_icon,
+      self._chestnut_icon,
+      self._chestnut_loading_icon,
+      self._chestnut_failed_icon,
       self._body_icon,
       self._mic_icon,
     ], spacing=18)
 
-    self._openpilot_label = UnifiedLabel("sunnypilot", font_size=96, font_weight=FontWeight.DISPLAY, max_width=480, wrap_text=False)
+    self._openpilot_label = UnifiedLabel("openpilot", font_size=96, font_weight=FontWeight.DISPLAY, max_width=480, wrap_text=False)
     self._version_label = UnifiedLabel("", font_size=36, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
     self._large_version_label = UnifiedLabel("", font_size=64, text_color=rl.GRAY, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
     self._date_label = UnifiedLabel("", font_size=36, text_color=rl.GRAY, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
@@ -247,9 +252,20 @@ class MiciHomeLayout(Widget):
         self._version_commit_label.render()
 
     # ***** Center-aligned bottom section icons *****
+    usb_connected = ui_state.usb_connected
+    usb_unknown = ui_state.usb_unknown
+    chestnut_state = ui_state.chestnut_state
     self._experimental_icon.set_visible(ui_state.experimental_mode)
-    self._egpu_icon.set_visible(ui_state.sm["deviceState"].chestnutPresent and ui_state.usbgpu_compiled)
-    self._egpu_icon_gray.set_visible(ui_state.sm["deviceState"].chestnutPresent and not ui_state.usbgpu_compiled)
+    if gui_app.sunnypilot_ui():
+      self._set_chestnut_visibility()
+    else:
+      self._usb_icon.set_visible(usb_connected and usb_unknown)
+      self._chestnut_icon.set_visible(not usb_unknown and chestnut_state not in
+                                      (ChestnutState.LOADING, ChestnutState.UNCOMPILED, ChestnutState.FAILED) and
+                                      (usb_connected or chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE)))
+      self._chestnut_loading_icon.set_visible(not usb_unknown and chestnut_state == ChestnutState.LOADING)
+      self._chestnut_loading_icon.set_opacity(0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0)))
+      self._chestnut_failed_icon.set_visible(not usb_unknown and chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
     self._mic_icon.set_visible(ui_state.recording_audio)
     self._body_icon.set_visible(bool(ui_state.is_body))
 

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

@@ -14,6 +14,7 @@ from openpilot.system.ui.lib.application import gui_app
 if gui_app.sunnypilot_ui():
   from openpilot.selfdrive.ui.sunnypilot.mici.layouts.settings import SettingsLayoutSP as SettingsLayout
   from openpilot.selfdrive.ui.sunnypilot.mici.layouts.home import MiciHomeLayoutSP as MiciHomeLayout
+  from openpilot.selfdrive.ui.sunnypilot.mici.layouts.onroad import OnroadViewContainerSP as AugmentedRoadView
 
 ONROAD_DELAY = 2.5  # seconds
 
@@ -72,6 +73,9 @@ class MiciMainLayout(Scroller):
     # For scroll_to
     return self._body_onroad_layout if ui_state.is_body else self._car_onroad_layout
 
+  def _should_auto_scroll_to_onroad(self) -> bool:
+    return True
+
   def _setup_callbacks(self):
     self._home_layout.set_callbacks(
       on_settings=lambda: gui_app.push_widget(self._settings_layout),
@@ -122,13 +126,15 @@ class MiciMainLayout(Scroller):
 
     # FIXME: these two pops can interrupt user interacting in the settings
     if self._onroad_time_delay is not None and rl.get_time() - self._onroad_time_delay >= ONROAD_DELAY:
-      gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
+      if not gui_app.sunnypilot_ui() or self._should_auto_scroll_to_onroad():
+        gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
       self._onroad_time_delay = None
 
     # When car leaves standstill, pop nav stack and scroll to onroad
     CS = ui_state.sm["carState"]
     if not CS.standstill and self._prev_standstill:
-      gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
+      if not gui_app.sunnypilot_ui() or self._should_auto_scroll_to_onroad():
+        gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
     self._prev_standstill = CS.standstill
 
   def _on_interactive_timeout(self):

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

@@ -11,7 +11,7 @@ from openpilot.common.hardware import HARDWARE
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets.scroller import Scroller
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.lib.multilang import tr
 
 REFRESH_INTERVAL = 5.0  # seconds
@@ -62,12 +62,12 @@ class AlertItem(Widget):
     self._icon_green = gui_app.texture("icons_mici/offroad_alerts/green_wheel.png", self.ICON_SIZE, self.ICON_SIZE)
 
     self._title_label = UnifiedLabel(text="", font_size=32, font_weight=FontWeight.SEMI_BOLD, text_color=self.TEXT_COLOR,
-                                     alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
-                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP, line_height=0.95)
+                                     alignment=TextAlignment.LEFT,
+                                     alignment_vertical=TextAlignmentVertical.TOP, line_height=0.95)
 
     self._body_label = UnifiedLabel(text="", font_size=28, font_weight=FontWeight.ROMAN, text_color=self.TEXT_COLOR,
-                                    alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
-                                    alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM, line_height=0.95)
+                                    alignment=TextAlignment.LEFT,
+                                    alignment_vertical=TextAlignmentVertical.BOTTOM, line_height=0.95)
 
     self._title_text = ""
     self._body_text = ""
@@ -200,8 +200,8 @@ class MiciOffroadAlerts(Scroller):
 
     # Create empty state label
     self._empty_label = UnifiedLabel(tr("no alerts"), 65, FontWeight.DISPLAY, rl.WHITE,
-                                     alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                                     alignment=TextAlignment.CENTER,
+                                     alignment_vertical=TextAlignmentVertical.MIDDLE)
 
     # Build initial alert list
     self._build_alerts()

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

@@ -4,7 +4,7 @@ import pyray as rl
 from collections.abc import Callable
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.qrcode import make_texture
-from openpilot.system.ui.lib.application import FontWeight, gui_app
+from openpilot.system.ui.lib.application import FontWeight, gui_app, TextAlignment
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.button import SmallCircleIconButton
 from openpilot.system.ui.widgets.scroller import NavScroller, Scroller
@@ -35,7 +35,7 @@ class DriverCameraSetupDialog(BaseCabinCameraDialog):
 
     if not self._camera_view.frame:
       gui_label(rect, tr("camera starting"), font_size=64, font_weight=FontWeight.BOLD,
-                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
+                alignment=TextAlignment.CENTER)
       rl.end_scissor_mode()
       return
 

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

@@ -74,6 +74,10 @@ class SoftwareInfoLayoutMici(Widget):
 
 
 class CheckUpdateButton(BigButton):
+  UPDATER_PROC = "openpilot.system.updated.updated"
+  CHECK_FOR_UPDATE = "SIGUSR1"
+  DOWNLOAD_UPDATE = "SIGHUP"
+
   def __init__(self):
     self._txt_update_icon = gui_app.texture("icons_mici/settings/device/update.png", 64, 75)
     self._txt_up_to_date_icon = gui_app.texture("icons_mici/settings/device/up_to_date.png", 64, 64)
@@ -97,15 +101,20 @@ class CheckUpdateButton(BigButton):
       gui_app.push_widget(dlg)
       return
 
+    self._signal_updater(self.DOWNLOAD_UPDATE if self.get_value() == "download update" else self.CHECK_FOR_UPDATE)
+
+  def check_for_update(self):
+    self._signal_updater(self.CHECK_FOR_UPDATE)
+
+  def _signal_updater(self, sig: str):
     self.set_enabled(False)
     self._state = UpdaterState.WAITING_FOR_UPDATER
+    self._hide_value_t = None
+    self.set_value("")
     self.set_icon(self._txt_update_icon)
 
     def run():
-      if self.get_value() == "download update":
-        subprocess.run("pkill -SIGHUP -f openpilot.system.updated.updated", shell=True)
-      else:
-        subprocess.run("pkill -SIGUSR1 -f openpilot.system.updated.updated", shell=True)
+      subprocess.run(f"pkill -{sig} -f {self.UPDATER_PROC}", shell=True)
 
     threading.Thread(target=run, daemon=True).start()
 
@@ -184,7 +193,7 @@ class CheckUpdateButton(BigButton):
 
 class InstallUpdateButton(BigButton):
   def __init__(self):
-    super().__init__("install update", "", gui_app.texture("icons_mici/settings/device/reboot.png", 64, 70))
+    super().__init__("install now", "", gui_app.texture("icons_mici/settings/device/reboot.png", 64, 70))
     self.set_visible(lambda: ui_state.is_offroad() and ui_state.params.get_bool("UpdateAvailable"))
 
   def _update_state(self):
@@ -232,8 +241,9 @@ class BranchSelectPage(NavScroller):
 
 
 class TargetBranchButton(BigButton):
-  def __init__(self):
+  def __init__(self, check_update_btn: CheckUpdateButton):
     super().__init__("target branch", ui_state.params.get("UpdaterTargetBranch") or "")
+    self._check_update_btn = check_update_btn
     self.set_click_callback(self._on_click)
     self.set_visible(not ui_state.params.get_bool("IsTestedBranch"))
     self.set_enabled(lambda: ui_state.is_offroad())
@@ -246,12 +256,15 @@ class TargetBranchButton(BigButton):
       self.set_value(target)
 
   def _on_click(self):
+    if not ui_state.params.get("UpdaterAvailableBranches"):
+      gui_app.push_widget(BigDialog("", tr("Failed to get available branches. Ensure you're connected to the internet and try again.")))
+      return
     gui_app.push_widget(BranchSelectPage(self._on_select))
 
   def _on_select(self, branch: str):
     ui_state.params.put("UpdaterTargetBranch", branch, block=True)
     self.set_value(branch)
-    subprocess.run("pkill -SIGUSR1 -f openpilot.system.updated.updated", shell=True)
+    self._check_update_btn.check_for_update()
 
 
 class SoftwareLayoutMici(NavScroller):
@@ -265,10 +278,11 @@ class SoftwareLayoutMici(NavScroller):
                                                         gui_app.texture("icons_mici/settings/device/uninstall.png", 64, 64),
                                                         uninstall_openpilot_callback, exit_on_confirm=False)
 
+    check_update_btn = CheckUpdateButton()
     self._scroller.add_widgets([
       SoftwareInfoLayoutMici(),
-      CheckUpdateButton(),
+      check_update_btn,
       InstallUpdateButton(),
-      TargetBranchButton(),
+      TargetBranchButton(check_update_btn),
       uninstall_openpilot_btn,
     ])

openpilot/selfdrive/ui/mici/layouts/settings/toggles.py

@@ -42,6 +42,8 @@ class TogglesLayoutMici(NavScroller):
     super().__init__()
 
     self._personality_toggle = BigMultiParamToggle("driving personality", "LongitudinalPersonality", ["aggressive", "standard", "relaxed"])
+    self._accel_controller_enabled = BigParamControl("enable accel controller", "AccelPersonalityEnabled")
+    self._accel_personality_toggle = BigMultiParamToggle("acceleration profile", "AccelPersonality", ["eco", "normal", "sport"])
     self._experimental_btn = BigToggle("experimental mode", initial_state=ui_state.params.get_bool("ExperimentalMode"),
                                        toggle_callback=self._on_experimental_mode)
     is_metric_toggle = BigParamControl("use metric units", "IsMetric")
@@ -53,6 +55,8 @@ class TogglesLayoutMici(NavScroller):
 
     self._scroller.add_widgets([
       self._personality_toggle,
+      self._accel_controller_enabled,
+      self._accel_personality_toggle,
       self._experimental_btn,
       is_metric_toggle,
       ldw_toggle,
@@ -65,6 +69,7 @@ class TogglesLayoutMici(NavScroller):
     # Toggle lists
     self._refresh_toggles = (
       ("ExperimentalMode", self._experimental_btn),
+      ("AccelPersonalityEnabled", self._accel_controller_enabled),
       ("IsMetric", is_metric_toggle),
       ("IsLdwEnabled", ldw_toggle),
       ("AlwaysOnDM", always_on_dm_toggle),
@@ -104,17 +109,23 @@ class TogglesLayoutMici(NavScroller):
       if ui_state.has_longitudinal_control:
         self._experimental_btn.set_visible(True)
         self._personality_toggle.set_visible(True)
+        self._accel_controller_enabled.set_visible(True)
+        self._accel_personality_toggle.set_visible(True)
       else:
         # no long for now
         self._experimental_btn.set_visible(False)
         self._experimental_btn.set_checked(False)
         self._personality_toggle.set_visible(False)
+        self._accel_controller_enabled.set_visible(False)
+        self._accel_personality_toggle.set_visible(False)
         ui_state.params.remove("ExperimentalMode")
 
     # Refresh toggles from params to mirror external changes
     for key, item in self._refresh_toggles:
       item.set_checked(ui_state.params.get_bool(key))
 
+    self._accel_personality_toggle.refresh()
+
   def _on_experimental_mode(self, state: bool):
     if state and not ui_state.params.get_bool("ExperimentalModeConfirmed"):
       # Don't show enabled state until confirm

openpilot/selfdrive/ui/mici/onroad/alert_renderer.py

@@ -10,7 +10,7 @@ from opendbc.car.structs import car
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.common.filter_simple import BounceFilter, FirstOrderFilter
 from openpilot.common.hardware import COMMA_HARDWARE
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 
@@ -333,7 +333,7 @@ class AlertRenderer(Widget, SpeedLimitAlertRenderer):
     self._alert_text1_label.set_text(alert_text1)
     self._alert_text1_label.set_text_color(color)
     self._alert_text1_label.set_font_size(font_size)
-    self._alert_text1_label.set_alignment(rl.GuiTextAlignment.TEXT_ALIGN_LEFT if icon_side != 'left' else rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
+    self._alert_text1_label.set_alignment(TextAlignment.LEFT if icon_side != 'left' else TextAlignment.RIGHT)
     self._alert_text1_label.render(text_rect1)
 
     alert_text2 = alert.text2.lower()
@@ -365,5 +365,5 @@ class AlertRenderer(Widget, SpeedLimitAlertRenderer):
       self._alert_text2_label.set_text(alert_text2)
       self._alert_text2_label.set_text_color(color)
       self._alert_text2_label.set_font_size(small_font_size)
-      self._alert_text2_label.set_alignment(rl.GuiTextAlignment.TEXT_ALIGN_LEFT if icon_side != 'left' else rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
+      self._alert_text2_label.set_alignment(TextAlignment.LEFT if icon_side != 'left' else TextAlignment.RIGHT)
       self._alert_text2_label.render(text_rect2)

openpilot/selfdrive/ui/mici/onroad/augmented_road_view.py

@@ -11,7 +11,7 @@ from openpilot.selfdrive.ui.mici.onroad.hud_renderer import HudRenderer
 from openpilot.selfdrive.ui.mici.onroad.model_renderer import ModelRenderer
 from openpilot.selfdrive.ui.mici.onroad.confidence_ball import ConfidenceBall
 from openpilot.selfdrive.ui.mici.onroad.cameraview import CameraView
-from openpilot.system.ui.lib.application import FontWeight, gui_app, MousePos, MouseEvent
+from openpilot.system.ui.lib.application import FontWeight, gui_app, MousePos, MouseEvent, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets import Widget
 from openpilot.common.filter_simple import BounceFilter
@@ -158,8 +158,8 @@ class AugmentedRoadView(CameraView):
     self._confidence_ball = ConfidenceBall()
     self._offroad_label = UnifiedLabel("start the car to\nuse sunnypilot", 54, FontWeight.DISPLAY,
                                        text_color=rl.Color(255, 255, 255, int(255 * 0.9)),
-                                       alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                                       alignment=TextAlignment.CENTER,
+                                       alignment_vertical=TextAlignmentVertical.MIDDLE)
 
     self._fade_texture = gui_app.texture("icons_mici/onroad/onroad_fade.png")
 

openpilot/selfdrive/ui/mici/onroad/cabin_camera_dialog.py

@@ -4,7 +4,7 @@ from openpilot.cereal.visionipc import VisionStreamType
 from openpilot.selfdrive.ui.mici.onroad.cameraview import CameraView
 from openpilot.selfdrive.ui.mici.onroad.driver_state import DriverStateRenderer
 from openpilot.selfdrive.ui.ui_state import ui_state, device
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.nav_widget import NavWidget
@@ -76,7 +76,7 @@ class BaseCabinCameraDialog(Widget):
 
     if not self._camera_view.frame:
       gui_label(rect, tr("camera starting"), font_size=54, font_weight=FontWeight.BOLD,
-                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
+                alignment=TextAlignment.CENTER)
       rl.end_scissor_mode()
       self._publish_alert_sound(None)
       return
@@ -124,12 +124,12 @@ class BaseCabinCameraDialog(Widget):
     awareness_pct = dm_state.visionPolicyState.awarenessPercent if is_vision else dm_state.wheeltouchPolicyState.awarenessPercent
     gui_label(rl.Rectangle(rect.x + 2, rect.y + 2, rect.width, rect.height),
               f"Awareness: {awareness_pct:.0f}%", font_size=44, font_weight=FontWeight.MEDIUM,
-              alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT,
-              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+              alignment=TextAlignment.RIGHT,
+              alignment_vertical=TextAlignmentVertical.TOP,
               color=rl.Color(0, 0, 0, 180))
     gui_label(rect, f"Awareness: {awareness_pct:.0f}%", font_size=44, font_weight=FontWeight.MEDIUM,
-              alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT,
-              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+              alignment=TextAlignment.RIGHT,
+              alignment_vertical=TextAlignmentVertical.TOP,
               color=rl.Color(255, 255, 255, int(255 * 0.9)))
 
     if dm_state.alertLevel == log.DriverMonitoringState.AlertLevel.none:
@@ -137,16 +137,16 @@ class BaseCabinCameraDialog(Widget):
 
     # Show alert level
     alert_level_str = f"{'Pay Attention' if is_vision else 'Touch Wheel'} - level {dm_state.alertLevel}"
-    alignment = rl.GuiTextAlignment.TEXT_ALIGN_RIGHT if self.driver_state_renderer.is_rhd else rl.GuiTextAlignment.TEXT_ALIGN_LEFT
+    alignment = TextAlignment.RIGHT if self.driver_state_renderer.is_rhd else TextAlignment.LEFT
 
     shadow_rect = rl.Rectangle(rect.x + 2, rect.y + 2, rect.width, rect.height)
     gui_label(shadow_rect, alert_level_str, font_size=40, font_weight=FontWeight.BOLD,
               alignment=alignment,
-              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM,
+              alignment_vertical=TextAlignmentVertical.BOTTOM,
               color=rl.Color(0, 0, 0, 180))
     gui_label(rect, alert_level_str, font_size=40, font_weight=FontWeight.BOLD,
               alignment=alignment,
-              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM,
+              alignment_vertical=TextAlignmentVertical.BOTTOM,
               color=rl.Color(255, 255, 255, int(255 * 0.9)))
 
   def _load_eye_textures(self):

openpilot/selfdrive/ui/mici/onroad/hud_renderer.py

@@ -3,7 +3,7 @@ import pyray as rl
 from dataclasses import dataclass
 from openpilot.common.constants import CV
 from openpilot.selfdrive.ui.mici.onroad.torque_bar import TorqueBar
-from openpilot.selfdrive.ui.ui_state import ui_state, UIStatus
+from openpilot.selfdrive.ui.ui_state import ui_state, UIStatus, ChestnutState
 from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.lib.text_measure import measure_text_cached
@@ -107,8 +107,7 @@ class HudRenderer(Widget):
     self.speed: float = 0.0
     self.v_ego_cluster_seen: bool = False
     self._engaged: bool = False
-    self._small_model_engaged: bool = False
-    self._egpu_fade_time: float = 0
+    self._chestnut_fade_time: float = 0
 
     self._can_draw_top_icons = True
     self._show_wheel_critical = False
@@ -124,17 +123,15 @@ class HudRenderer(Widget):
     self._txt_wheel: rl.Texture = gui_app.texture('icons_mici/wheel.png', 50, 50)
     self._txt_wheel_critical: rl.Texture = gui_app.texture('icons_mici/wheel_critical.png', 50, 50)
     self._txt_exclamation_point: rl.Texture = gui_app.texture('icons_mici/exclamation_point.png', 9, 44)
-    self._txt_egpu: rl.Texture = gui_app.texture('icons_mici/egpu.png', 60, 44)
-    self._txt_egpu_green: rl.Texture = gui_app.texture('icons_mici/egpu_green.png', 60, 44)
-    self._txt_egpu_orange: rl.Texture = gui_app.texture('icons_mici/egpu_orange.png', 60, 44)
-    self._txt_egpu_crossed: rl.Texture = gui_app.texture('icons_mici/egpu_crossed.png', 60, 52)
-    self._egpu_icon: rl.Texture | None = None
-
+    self._txt_chestnut: rl.Texture = gui_app.texture('icons_mici/chestnut.png', 60, 44)
+    self._txt_chestnut_green: rl.Texture = gui_app.texture('icons_mici/chestnut_green.png', 60, 44)
+    self._txt_chestnut_orange: rl.Texture = gui_app.texture('icons_mici/chestnut_orange.png', 75, 44)
+    self._chestnut_icon: rl.Texture | None = None
     self._wheel_alpha_filter = FirstOrderFilter(0, 0.05, 1 / gui_app.target_fps)
     self._wheel_y_filter = FirstOrderFilter(0, 0.1, 1 / gui_app.target_fps)
 
     self._set_speed_alpha_filter = FirstOrderFilter(0.0, 0.1, 1 / gui_app.target_fps)
-    self._egpu_alpha_filter = FirstOrderFilter(0.0, 0.1, 1 / gui_app.target_fps)
+    self._chestnut_alpha_filter = FirstOrderFilter(0.0, 0.1, 1 / gui_app.target_fps)
 
   def set_wheel_critical_icon(self, critical: bool):
     """Set the wheel icon to critical or normal state."""
@@ -165,13 +162,10 @@ class HudRenderer(Widget):
       controls_state.deprecated.vCruise if v_cruise_cluster == 0.0 else v_cruise_cluster
     )
     engaged = sm['selfdriveState'].enabled
-    if (engaged and not self._engaged and not ui_state.usbgpu_loading and ui_state.usbgpu_active is not True and
-        ui_state.sm.recv_frame['modelV2'] > ui_state.started_frame):
-      self._small_model_engaged = True
-    if engaged != self._engaged:
-      self._egpu_fade_time = rl.get_time() if engaged else 0
     if (set_speed != self.set_speed and engaged) or (engaged and not self._engaged):
       self._set_speed_changed_time = rl.get_time()
+    if engaged != self._engaged:
+      self._chestnut_fade_time = rl.get_time() if engaged else 0
     self._engaged = engaged
     self.set_speed = set_speed
     self.is_cruise_set = 0 < self.set_speed < SET_SPEED_NA
@@ -191,8 +185,7 @@ class HudRenderer(Widget):
     if self.is_cruise_set:
       self._draw_set_speed(rect)
 
-    if ui_state.usbgpu and ui_state.usbgpu_compiled:
-      self._draw_model_source(rect)
+    self._draw_model_source(rect)
 
     self._draw_steering_wheel(rect)
 
@@ -200,30 +193,24 @@ class HudRenderer(Widget):
     if ui_state.sm.recv_frame['selfdriveState'] < ui_state.started_frame:
       return
 
-    big_failed = (ui_state.usbgpu_active is False or not ui_state.sm['deviceState'].chestnutPresent or
-                  (ui_state.usbgpu_active is True and ui_state.sm.recv_frame['modelV2'] > ui_state.started_frame and
-                   not ui_state.sm.alive['modelV2']) or
-                  (ui_state.usbgpu_active is None and ui_state.sm.recv_frame['modelV2'] > ui_state.started_frame))
-    self._small_model_engaged &= big_failed
-    loading = ui_state.usbgpu_loading or (ui_state.usbgpu_active is None and not big_failed)
+    loading = ui_state.chestnut_state == ChestnutState.LOADING
     if loading:
-      pulse = 0.5 - 0.5 * math.cos(rl.get_time() * 6.0)
-      icon = self._txt_egpu
-      opacity = 0.35 + 0.65 * pulse
-    elif self._small_model_engaged:
-      icon = self._txt_egpu_crossed
-      opacity = 0.65
-    elif big_failed:
-      icon = self._txt_egpu_orange
+      icon = self._txt_chestnut
+      opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
+    elif ui_state.chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED):
+      icon = self._txt_chestnut_orange
+      opacity = 1.0
+    elif ui_state.chestnut_state == ChestnutState.ACTIVE:
+      icon = self._txt_chestnut_green
       opacity = 1.0
     else:
-      icon = self._txt_egpu_green
-      opacity = 1.0
+      return
 
-    if icon is not self._egpu_icon:
-      self._egpu_fade_time = rl.get_time()
-      self._egpu_icon = icon
-    alpha = self._egpu_alpha_filter.update(loading or 0 < rl.get_time() - self._egpu_fade_time < SET_SPEED_PERSISTENCE)
+    if icon is not self._chestnut_icon:
+      self._chestnut_fade_time = rl.get_time()
+      self._chestnut_icon = icon
+    visible = loading or rl.get_time() - self._chestnut_fade_time < SET_SPEED_PERSISTENCE
+    alpha = self._chestnut_alpha_filter.update(visible)
     if alpha < 1e-2:
       return
 

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

@@ -154,8 +154,8 @@ class ModelRenderer(Widget, ModelRendererSP):
       self._draw_lane_lines()
       self._draw_path(sm)
 
-    # if render_lead_indicator and radar_state:
-    #   self._draw_lead_indicator()
+    if render_lead_indicator and radar_state:
+      self._draw_lead_indicator()
 
   def _update_raw_points(self, model):
     """Update raw 3D points from model data"""

openpilot/selfdrive/ui/mici/widgets/button.py

@@ -6,7 +6,7 @@ from collections.abc import Callable
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets.scroller import DO_ZOOM
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos, TextAlignmentVertical
 from openpilot.common.filter_simple import BounceFilter
 
 if TYPE_CHECKING:
@@ -125,10 +125,10 @@ class BigButton(Widget):
     self._rotate_icon_t: float | None = None
 
     self._label = UnifiedLabel(text, font_size=self._get_label_font_size(), font_weight=FontWeight.BOLD,
-                               text_color=LABEL_COLOR, alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM, scroll=scroll,
+                               text_color=LABEL_COLOR, alignment_vertical=TextAlignmentVertical.BOTTOM, scroll=scroll,
                                line_height=0.9)
     self._sub_label = UnifiedLabel(value, font_size=COMPLICATION_SIZE, font_weight=FontWeight.ROMAN,
-                                   text_color=COMPLICATION_GREY, alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
+                                   text_color=COMPLICATION_GREY, alignment_vertical=TextAlignmentVertical.BOTTOM)
     self._update_label_layout()
 
     self._load_images()
@@ -149,11 +149,15 @@ class BigButton(Widget):
   def set_touch_valid_callback(self, touch_callback: Callable[[], bool]) -> None:
     super().set_touch_valid_callback(lambda: touch_callback() and self._grow_animation_until is None)
 
-  def _width_hint(self) -> int:
-    # A value moves the title to the top, where it shares space with the icon.
+  def _title_width_hint(self) -> int:
+    # A value moves the title to the top, where it shares space with the icon
     icon_size = self._txt_icon.width if self._txt_icon and self.value else 0
     return int(self._rect.width - self.LABEL_HORIZONTAL_PADDING * 2 - icon_size)
 
+  def _subtitle_width_hint(self) -> int:
+    # Bottom aligned, so it sits below the icon
+    return int(self._rect.width - self.LABEL_HORIZONTAL_PADDING * 2)
+
   def _get_label_font_size(self):
     if len(self.text) <= 18:
       return 48
@@ -163,9 +167,9 @@ class BigButton(Widget):
   def _update_label_layout(self):
     self._label.set_font_size(self._get_label_font_size())
     if self.value:
-      self._label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP)
+      self._label.set_alignment_vertical(TextAlignmentVertical.TOP)
     else:
-      self._label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
+      self._label.set_alignment_vertical(TextAlignmentVertical.BOTTOM)
 
   def set_text(self, text: str):
     self.text = text
@@ -228,14 +232,14 @@ class BigButton(Widget):
 
     label_color = LABEL_COLOR if self.enabled else rl.Color(255, 255, 255, int(255 * 0.35))
     self._label.set_color(label_color)
-    label_rect = rl.Rectangle(label_x, btn_y + self.LABEL_VERTICAL_PADDING, self._width_hint(),
+    label_rect = rl.Rectangle(label_x, btn_y + self.LABEL_VERTICAL_PADDING, self._title_width_hint(),
                               self._rect.height - self.LABEL_VERTICAL_PADDING * 2)
     self._label.render(label_rect)
 
     if self.value:
-      label_y = btn_y + self.LABEL_VERTICAL_PADDING + self._label.get_content_height(self._width_hint())
+      label_y = label_rect.y + self._label.get_content_height(int(label_rect.width))
       sub_label_height = btn_y + self._rect.height - self.LABEL_VERTICAL_PADDING - label_y
-      sub_label_rect = rl.Rectangle(label_x, label_y, self._width_hint(), sub_label_height)
+      sub_label_rect = rl.Rectangle(label_x, label_y, self._subtitle_width_hint(), sub_label_height)
       self._sub_label.render(sub_label_rect)
 
     # ICON -------------------------------------------------------------------
@@ -312,9 +316,6 @@ class BigMultiToggle(BigToggle):
 
     self.set_value(self._options[0])
 
-  def _width_hint(self) -> int:
-    return int(self._rect.width - self.LABEL_HORIZONTAL_PADDING * 2 - self._txt_enabled_toggle.width)
-
   def _handle_mouse_release(self, mouse_pos: MousePos):
     super()._handle_mouse_release(mouse_pos)
     cur_idx = self._options.index(self.value)
@@ -355,17 +356,14 @@ class GreyBigButton(BigButton):
     self._sub_label.set_font_size(36)
     self._sub_label.set_text_color(rl.Color(255, 255, 255, int(255 * 0.9)))
     self._sub_label.set_font_weight(FontWeight.DISPLAY_REGULAR)
-    self._sub_label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE if not self._label.text else
-                                           rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
+    self._sub_label.set_alignment_vertical(TextAlignmentVertical.MIDDLE if not self._label.text else
+                                           TextAlignmentVertical.BOTTOM)
     self._sub_label.set_line_height(0.95)
 
   @property
   def LABEL_VERTICAL_PADDING(self):
     return BigButton.LABEL_VERTICAL_PADDING if self._label.text else 18
 
-  def _width_hint(self) -> int:
-    return int(self._rect.width - self.LABEL_HORIZONTAL_PADDING * 2)
-
   def _get_label_font_size(self):
     return 36
 
@@ -385,13 +383,18 @@ class BigMultiParamToggle(BigMultiToggle):
     self._load_value()
 
   def _load_value(self):
-    self.set_value(self._options[self._params.get(self._param) or 0])
+    value = self._params.get(self._param, return_default=True)
+    index = value if isinstance(value, int) else 0
+    self.set_value(self._options[max(0, min(index, len(self._options) - 1))])
 
   def _handle_mouse_release(self, mouse_pos: MousePos):
     super()._handle_mouse_release(mouse_pos)
     new_idx = self._options.index(self.value)
     self._params.put(self._param, new_idx)
 
+  def refresh(self):
+    self._load_value()
+
 
 class BigParamControl(BigToggle):
   def __init__(self, text: str, param: str, toggle_callback: Callable | None = None):

openpilot/selfdrive/ui/onroad/alert_renderer.py

@@ -4,7 +4,7 @@ from dataclasses import dataclass
 from openpilot.cereal import messaging, log
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.common.hardware import COMMA_HARDWARE
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.lib.text_measure import measure_text_cached
 from openpilot.system.ui.widgets import Widget
@@ -76,10 +76,10 @@ class AlertRenderer(Widget):
     self.font_bold: rl.Font = gui_app.font(FontWeight.BOLD)
 
     # font size is set dynamically
-    self._full_text1_label = Label("", font_size=0, font_weight=FontWeight.BOLD, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                   text_alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP)
-    self._full_text2_label = Label("", font_size=ALERT_FONT_BIG, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                   text_alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP)
+    self._full_text1_label = Label("", font_size=0, font_weight=FontWeight.BOLD, text_alignment=TextAlignment.CENTER,
+                                   text_alignment_vertical=TextAlignmentVertical.TOP)
+    self._full_text2_label = Label("", font_size=ALERT_FONT_BIG, text_alignment=TextAlignment.CENTER,
+                                   text_alignment_vertical=TextAlignmentVertical.TOP)
 
   def get_alert(self, sm: messaging.SubMaster) -> Alert | None:
     """Generate the current alert based on selfdrive state."""

openpilot/selfdrive/ui/onroad/cabin_camera_dialog.py

@@ -4,7 +4,7 @@ from openpilot.cereal.visionipc import VisionStreamType
 from openpilot.selfdrive.ui.onroad.cameraview import CameraView
 from openpilot.selfdrive.ui.onroad.driver_state import DriverStateRenderer
 from openpilot.selfdrive.ui.ui_state import ui_state, device
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets.label import gui_label
 
@@ -38,7 +38,7 @@ class CabinCameraDialog(CameraView):
         tr("camera starting"),
         font_size=100,
         font_weight=FontWeight.BOLD,
-        alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+        alignment=TextAlignment.CENTER,
       )
       return -1
 

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

@@ -6,7 +6,7 @@ See the LICENSE.md file in the root directory for more details.
 """
 import pyray as rl
 from openpilot.selfdrive.ui.layouts.home import HomeLayout, HomeLayoutState, HEAD_BUTTON_FONT_SIZE, SPACING
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment
 from openpilot.system.ui.lib.text_measure import measure_text_cached
 from openpilot.system.ui.lib.multilang import tr, trn
 from openpilot.system.ui.widgets.label import gui_label
@@ -59,7 +59,7 @@ class HomeLayoutSP(HomeLayout):
       desc_size = measure_text_cached(gui_app.font(FontWeight.NORMAL), description, BRAND_FONT_SIZE)
       desc_width = desc_size.x
       desc_rect = rl.Rectangle(version_right - desc_width, self.header_rect.y, desc_width, self.header_rect.height)
-      gui_label(desc_rect, description, BRAND_FONT_SIZE, rl.WHITE, alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
+      gui_label(desc_rect, description, BRAND_FONT_SIZE, rl.WHITE, alignment=TextAlignment.RIGHT)
 
     brand_size = measure_text_cached(gui_app.font(FontWeight.AUDIOWIDE), brand, BRAND_FONT_SIZE)
     spacing = BRAND_DESC_SPACING if description else 0

openpilot/selfdrive/ui/sunnypilot/layouts/onboarding.py

@@ -6,7 +6,7 @@ See the LICENSE.md file in the root directory for more details.
 """
 import pyray as rl
 from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.lib.application import FontWeight
+from openpilot.system.ui.lib.application import FontWeight, TextAlignment
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.button import Button, ButtonStyle
@@ -20,7 +20,7 @@ class SunnylinkConsentPage(Widget):
     self._done_callback = done_callback
     self._step = 0
 
-    self._title = self._child(Label(tr("sunnylink"), font_size=90, font_weight=FontWeight.AUDIOWIDE, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT))
+    self._title = self._child(Label(tr("sunnylink"), font_size=90, font_weight=FontWeight.AUDIOWIDE, text_alignment=TextAlignment.LEFT))
 
     self._content = [
       {
@@ -43,7 +43,7 @@ class SunnylinkConsentPage(Widget):
     self._primary_btn = self._child(Button("", button_style=ButtonStyle.PRIMARY, click_callback=lambda: self._handle_choice("enable")))
     self._secondary_btn = self._child(Button("", button_style=ButtonStyle.NORMAL, click_callback=lambda: self._handle_choice("secondary")))
     self._danger_btn = self._child(Button("", button_style=ButtonStyle.DANGER, click_callback=lambda: self._handle_choice("disable")))
-    self._desc = self._child(Label("", font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT))
+    self._desc = self._child(Label("", font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=TextAlignment.LEFT))
 
   def _handle_choice(self, choice):
     if choice == "enable":

openpilot/selfdrive/ui/sunnypilot/layouts/settings/cruise.py

@@ -143,7 +143,8 @@ class CruiseLayout(Widget):
           self.icbm_toggle.show_description(True)
 
       if has_long or has_icbm:
-        self.custom_acc_toggle.action_item.set_enabled(((has_long and not ui_state.CP.pcmCruise) or has_icbm) and ui_state.is_offroad())
+        software_cruise_speed = has_long and (not ui_state.CP.pcmCruise or not ui_state.CP_SP.pcmCruiseSpeed)
+        self.custom_acc_toggle.action_item.set_enabled((software_cruise_speed or has_icbm) and ui_state.is_offroad())
         self.dec_toggle.action_item.set_enabled(has_long)
         self.scc_v_toggle.action_item.set_enabled(True)
         self.scc_m_toggle.action_item.set_enabled(True)
@@ -169,7 +170,7 @@ class CruiseLayout(Widget):
       show_custom_acc_desc = True
     else:
       if has_long or has_icbm:
-        if has_long and ui_state.CP.pcmCruise:
+        if has_long and ui_state.CP.pcmCruise and ui_state.CP_SP.pcmCruiseSpeed:
           new_custom_acc_desc = tr(ACC_PCMCRUISE_DISABLED_DESCRIPTION)
           show_custom_acc_desc = True
         else:

openpilot/selfdrive/ui/sunnypilot/layouts/settings/models.py

@@ -10,9 +10,10 @@ import time
 import pyray as rl
 
 from openpilot.cereal import custom
-from openpilot.sunnypilot.models.default_model import get_default_model
+from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS, get_selected_bundle, resolve_bundle_by_ref
 from openpilot.common.constants import CV
 from openpilot.selfdrive.ui.ui_state import device, ui_state
+from openpilot.selfdrive.ui.sunnypilot.model_info import big_model_state, bundles_for_source, carrying_model, default_model_name, queued_name
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.widgets import DialogResult, Widget
@@ -36,7 +37,10 @@ class ModelsLayout(Widget):
     super().__init__()
     self.model_manager = None
     self.model_dialog = None
+    self._selection_source = None
     self._downloading = False
+    self._verifying = False
+    self._last_note = None
     self.last_cache_calc_time = 0
 
     self._initialize_items()
@@ -48,17 +52,24 @@ class ModelsLayout(Widget):
     self._scroller = Scroller(self.items, line_separator=True, spacing=0)
 
   def _initialize_items(self):
-    self.current_model_item = ListItemSP(
-      title=tr("Current Model"),
+    self.small_model_item = ListItemSP(
+      title=tr("Small Model"),
       description="",
       action_item=ScrollingButtonAction(tr("SELECT")),
-      callback=self._handle_current_model_clicked
+      callback=lambda: self._open_source_dialog("qcom")
+    )
+
+    self.big_model_item = ListItemSP(
+      title=tr("Big Model"),
+      action_item=ScrollingButtonAction(tr("SELECT")),
+      callback=lambda: self._open_source_dialog("chestnut")
     )
 
     self.download_item = download_status_item(lambda: tr("Download") if self._downloading else tr("Model Status"))
 
     self.refresh_item = button_item(tr("Refresh Model List"), tr("REFRESH"), "",
                                     lambda: (ui_state.params.put("ModelManager_LastSyncTime", 0),
+                                             ui_state.params.put("ModelManager_LastSyncTime_Chestnut", 0),
                                              gui_app.push_widget(alert_dialog(tr("Fetching Latest Models")))))
 
     self.clear_cache_item = ListItemSP(
@@ -68,7 +79,9 @@ class ModelsLayout(Widget):
       callback=self._clear_cache
     )
 
-    self.cancel_download_item = button_item(tr("Cancel Download"), tr("Cancel"), "", lambda: ui_state.params.remove("ModelManager_DownloadIndex"))
+    self.cancel_download_item = button_item(lambda: tr("Cancel Verification") if self._verifying else tr("Cancel Download"),
+                                            tr("Cancel"), "",
+                                            lambda: ui_state.params.remove("ModelManager_DownloadRef"))
 
     self.lane_turn_value_control = option_item_sp(tr("Adjust Lane Turn Speed"), "LaneTurnValue", 500, 2000,
                                                   tr("Set the maximum speed for lane turn desires. Default is 19 mph."),
@@ -93,7 +106,7 @@ class ModelsLayout(Widget):
                                         1, None, True, "", style.BUTTON_ACTION_WIDTH, None, True,
                                         lambda v: f"{v / 100:.2f} m")
 
-    self.items = [self.current_model_item, self.cancel_download_item, self.download_item, self.refresh_item, self.clear_cache_item,
+    self.items = [self.small_model_item, self.big_model_item, self.cancel_download_item, self.download_item, self.refresh_item, self.clear_cache_item,
                   self.lane_turn_desire_toggle, self.lane_turn_value_control, self.lagd_toggle, self.delay_control, self.camera_offset]
 
   def _update_lagd_description(self, lagd_toggle: bool):
@@ -107,16 +120,16 @@ class ModelsLayout(Widget):
       desc += f"<br>{tr('Actuator Delay:')} {cp:.2f} s + {tr('Software Delay:')} {sw:.2f} s = {tr('Total Delay:')} {cp + sw:.2f} s"
     self.lagd_toggle.set_description(desc)
 
-  def _is_downloading(self):
-    return (self.model_manager and self.model_manager.selectedBundle and
-            self.model_manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.downloading)
-
   @staticmethod
   def calculate_cache_size():
     cache_size = 0.0
     if os.path.exists(CUSTOM_MODEL_PATH):
-      cache_size = sum(os.path.getsize(os.path.join(CUSTOM_MODEL_PATH, file)) for file in os.listdir(CUSTOM_MODEL_PATH)) / (1024**2)
-    return cache_size
+      for file in os.listdir(CUSTOM_MODEL_PATH):
+        try:
+          cache_size += os.path.getsize(os.path.join(CUSTOM_MODEL_PATH, file))
+        except OSError:
+          continue
+    return cache_size / (1024**2)
 
   def _clear_cache(self):
     def _callback(response):
@@ -129,36 +142,90 @@ class ModelsLayout(Widget):
     gui_app.push_widget(dialog)
 
   def _handle_bundle_download_progress(self):
-    self.download_item.set_visible(False)
     self.cancel_download_item.set_visible(False)
     self._downloading = False
-
-    if not self.model_manager or (not self.model_manager.selectedBundle and not self.model_manager.activeBundle):
-      return
-
-    bundle = self.model_manager.selectedBundle if self._is_downloading() or (
-      self.model_manager.selectedBundle and self.model_manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.failed
-    ) else self.model_manager.activeBundle
-    if not bundle:
-      return
-
-    self.cancel_download_item.set_visible(bool(self.model_manager.selectedBundle) and ui_state.params.get("ModelManager_DownloadIndex") is not None)
+    self._verifying = False
+    self.download_item.set_visible(True)
 
     if (current_time := time.monotonic()) - self.last_cache_calc_time > 0.5:
       self.last_cache_calc_time = current_time
       self.clear_cache_item.action_item.set_value(f"{self.calculate_cache_size():.2f} MB")
 
+    bundle = self.model_manager.selectedBundle if self.model_manager else None
+    progresses = [model.artifact.downloadProgress for model in bundle.models if model.artifact.fileName] if bundle else []
+    if not progresses or bundle.status not in (custom.ModelManagerSP.DownloadStatus.downloading,
+                                               custom.ModelManagerSP.DownloadStatus.failed):
+      self.download_item.action_item.update(name="", segments=self._slot_segments())
+      return
+
+    self.cancel_download_item.set_visible(ui_state.params.get("ModelManager_DownloadRef") is not None)
     if bundle.status == custom.ModelManagerSP.DownloadStatus.downloading:
       device._reset_interactive_timeout()
 
-    # every bundle is a single chunked artifact now
-    progresses = [model.artifact.downloadProgress for model in bundle.models if model.artifact.fileName]
-    if not progresses:
-      return
-
-    self.download_item.set_visible(True)
-    self.download_item.action_item.update(**self._download_row_state(progresses, bundle.internalName))
+    state = self._download_row_state(progresses, bundle.internalName)
+    if queued := queued_name(bundle.ref):
+      state["name"] += f"  |  {queued} {tr('queued')}"
+    self.download_item.action_item.update(**state)
     self._downloading = self.download_item.action_item.downloading
+    ds = custom.ModelManagerSP.DownloadStatus
+    self._verifying = any(getattr(p.status, 'raw', p.status) == ds.verifying for p in progresses)
+
+  def _slot_segments(self):
+    """small and big slots side by side; green marks the slot whose pick is actually
+    driving (runner-matched, so a failed Default big greens neither slot), an empty
+    slot shows its default."""
+    big_state = big_model_state()
+    carry_source, carry_internal, _ = carrying_model()
+    segments = []
+    for source, label in (("qcom", tr("small")), ("chestnut", tr("big"))):
+      if segments:
+        segments.append(("|", rl.GRAY, None, None))
+      bundle = get_selected_bundle(ui_state.params, source)
+      name = bundle.internalName if bundle else default_model_name(source)
+      color = ON_COLOR if (source == carry_source and name == carry_internal) else rl.LIGHTGRAY
+      name = "● " + name
+      if source == "chestnut":
+        if big_state == 'failed':
+          color = rl.RED
+        elif big_state == 'loading':
+          color = rl.GOLD
+      segments.append((label, rl.GRAY, None, None))
+      segments.append((name, color, None, None))
+    return segments
+
+  @staticmethod
+  def _set_item_note(item, text):
+    # a description renders only while shown; hide before clearing or the
+    # empty description keeps its visible state
+    if text:
+      item.set_description(text)
+      item.show_description(True)
+    else:
+      item.show_description(False)
+      item.set_description("")
+
+  def _status_note(self) -> str:
+    """The failover story for the Model Status row. One-way big -> small, and the
+    fallback is runner-matched: a Default big can only fall back to the Default
+    small (stock modeld), a custom big has no automatic fallback yet."""
+    if not ui_state.chestnut_present:
+      return ""
+    big_bundle = get_selected_bundle(ui_state.params, "chestnut")
+    big_name = big_bundle.internalName if big_bundle else default_model_name("chestnut")
+    big_is_default = big_bundle is None
+    fallback_name = default_model_name("qcom")
+    state = big_model_state()
+    if state == 'failed':
+      if big_is_default:
+        return tr("Big model unavailable, {} is driving until the next drive.").format(fallback_name)
+      return tr("Big model unavailable until the next drive.")
+    if state == 'loading':
+      if big_is_default:
+        return tr("{} drives until the big model is ready.").format(fallback_name)
+      return tr("Getting the big model ready.")
+    if big_is_default:
+      return tr("{} will drive. If it fails during a drive, {} takes over until the next drive.").format(big_name, fallback_name)
+    return tr("{} will drive when the chestnut is ready.").format(big_name)
 
   @staticmethod
   def _download_row_state(progresses, name: str) -> dict:
@@ -171,6 +238,8 @@ class ModelsLayout(Widget):
     if ds.failed in statuses:
       # close.png is authored black and a tint cannot lift it, hence close2
       return {"name": name, "status_text": tr("download failed"), "text_color": rl.RED, "icon": "icons/close2.png"}
+    if ds.verifying in statuses:
+      return {"name": name, "downloading": True, "progress": progress, "status_text": tr("verifying")}
     if ds.downloading in statuses:
       return {"name": name, "downloading": True, "progress": progress}
     if statuses <= {ds.downloaded, ds.cached}:
@@ -178,65 +247,73 @@ class ModelsLayout(Widget):
     # circled_slash is authored grey; tinting it again only darkens it
     return {"name": name, "text_color": rl.GRAY, "icon": "icons/circled_slash.png", "icon_color": rl.WHITE}
 
-  @staticmethod
-  def _show_reset_params_dialog():
-    def _callback(response):
-      if response == DialogResult.CONFIRM:
-        ui_state.params.remove("CalibrationParams")
-        ui_state.params.remove("LiveTorqueParameters")
-    msg = tr("Model download has started in the background. We suggest resetting calibration. Would you like to do that now?")
-    dialog = ConfirmDialog(msg, tr("Reset Calibration"), callback=_callback)
-    gui_app.push_widget(dialog)
-
   def _on_model_selected(self, result):
     if result != DialogResult.CONFIRM:
+      self.model_dialog = None
       return
     selected_ref = self.model_dialog.selection_ref
-    if selected_ref == "Default":
-      ui_state.params.remove("ModelManager_ActiveBundle")
-      self._show_reset_params_dialog()
-    elif selected_bundle := next((bundle for bundle in self.model_manager.availableBundles if bundle.ref == selected_ref), None):
-      ui_state.params.put("ModelManager_DownloadIndex", selected_bundle.index)
-      if self.model_manager.activeBundle and selected_bundle.generation != self.model_manager.activeBundle.generation:
-        self._show_reset_params_dialog()
     self.model_dialog = None
+    if selected_ref == "Default":
+      if self._selection_source in ACTIVE_BUNDLE_KEYS:
+        ui_state.params.remove(ACTIVE_BUNDLE_KEYS[self._selection_source])
+      return
+    if selected_bundle := self._resolve_selected_bundle(selected_ref):
+      ui_state.params.put("ModelManager_DownloadRef", selected_bundle.ref)
+
+  def _resolve_selected_bundle(self, ref):
+    source_bundles = {source: bundles_for_source(source) for source in ("qcom", "chestnut")}
+    resolved = resolve_bundle_by_ref(ref, source_bundles)
+    return resolved[0] if resolved else None
 
   @staticmethod
   def _bundle_to_node(bundle):
     return TreeNode(bundle.ref, {'display_name': bundle.displayName, 'short_name': bundle.internalName})
 
-  def _get_folders(self, favorites):
-    bundles = self.model_manager.availableBundles
+  def _get_folders(self, favorites, bundles):
     folders = {}
     for bundle in bundles:
       folders.setdefault(next((ov_ride.value for ov_ride in bundle.overrides if ov_ride.key == "folder"), ""), []).append(bundle)
 
-    folders_list = [TreeFolder("", [TreeNode("Default", {'display_name': f"{get_default_model()} (Default)",
-                                                         'short_name': "Default"})])]
+    folders_list = []
     for folder, folder_bundles in sorted(folders.items(), key=lambda x: max((bundle.index for bundle in x[1]), default=-1), reverse=True):
       folder_bundles.sort(key=lambda bundle: bundle.index, reverse=True)
       name = folder + (f" - (Updated: {m.group(1)})" if folder_bundles and (m := re.search(r'\(([^)]*)\)[^(]*$', folder_bundles[0].displayName)) else "")
       folders_list.append(TreeFolder(name, [self._bundle_to_node(bundle) for bundle in folder_bundles]))
 
     if favorites and (fav_bundles := [bundle for bundle in bundles if bundle.ref in favorites]):
-      folders_list.insert(1, TreeFolder("Favorites", [self._bundle_to_node(bundle) for bundle in fav_bundles]))
+      folders_list.insert(0, TreeFolder("Favorites", [self._bundle_to_node(bundle) for bundle in fav_bundles]))
     return folders_list
 
-  def _handle_current_model_clicked(self):
+  def _open_source_dialog(self, source):
+    self._selection_source = source
     favs = ui_state.params.get("ModelManager_Favs")
     favorites = set(favs.split(';')) if favs else set()
-    folders_list = self._get_folders(favorites)
-
-    active_ref = self.model_manager.activeBundle.ref if self.model_manager.activeBundle else "Default"
-    self.model_dialog = TreeOptionDialog(tr("Select a Model"), folders_list, active_ref, "ModelManager_Favs",
-                                         get_folders_fn=self._get_folders, on_exit=self._on_model_selected)
+    folders_list = self._source_folders(favorites, source)
+    if not folders_list:
+      gui_app.push_widget(alert_dialog(tr("No models are available for this hardware yet. Connect to the internet and refresh the model list.")))
+      return
+    self.model_dialog = TreeOptionDialog(tr("Select a Model"), folders_list, self._slot_active_ref(source), "ModelManager_Favs",
+                                         get_folders_fn=lambda favs: self._source_folders(favs, source), on_exit=self._on_model_selected)
     gui_app.push_widget(self.model_dialog)
 
+  def _source_folders(self, favorites, source):
+    bundles = bundles_for_source(source)
+    if not bundles:
+      return []
+    folders_list = [TreeFolder("", [TreeNode("Default", {'display_name': default_model_name(source)})])]
+    folders_list.extend(self._get_folders(favorites, bundles))
+    return folders_list
+
+  @staticmethod
+  def _slot_active_ref(source: str) -> str:
+    bundle = get_selected_bundle(ui_state.params, source)
+    return bundle.ref if bundle else "Default"
+
   def _update_state(self):
     advanced_controls: bool = ui_state.params.get_bool("ShowAdvancedControls")
     turn_desire: bool = ui_state.params.get_bool("LaneTurnDesire")
     live_delay: bool = ui_state.params.get_bool("LagdToggle")
-    camera_offset: bool = ui_state.params.get("ModelManager_ActiveBundle") is not None
+    camera_offset: bool = ui_state.active_bundle is not None
 
     self.lane_turn_desire_toggle.action_item.set_state(turn_desire)
     self.lane_turn_value_control.set_visible(turn_desire and advanced_controls)
@@ -250,19 +327,27 @@ class ModelsLayout(Widget):
     self._update_lagd_description(live_delay)
     self.model_manager = ui_state.sm["modelManagerSP"]
     self._handle_bundle_download_progress()
-    default_label = f"{get_default_model()} (Default)"
-    active_name = self.model_manager.activeBundle.displayName if self.model_manager and self.model_manager.activeBundle.ref else default_label
-    self.current_model_item.action_item.set_value(active_name)
 
-    if not ui_state.is_offroad():
-      self.current_model_item.action_item.set_enabled(False)
-      self.current_model_item.set_description(tr("Only available when vehicle is off, or always offroad mode is on"))
-    else:
-      self.current_model_item.action_item.set_enabled(True)
-      self.current_model_item.set_description("")
+    carry_source, _, carry_display = carrying_model()
+    for item, item_source in ((self.small_model_item, "qcom"), (self.big_model_item, "chestnut")):
+      bundle = get_selected_bundle(ui_state.params, item_source)
+      name = bundle.displayName if bundle else default_model_name(item_source)
+      color = ON_COLOR if (item_source == carry_source and name == carry_display) else style.ITEM_TEXT_VALUE_COLOR
+      item.action_item.set_value(name, color)
+
+    note = self._status_note()
+    if note != self._last_note:
+      self._last_note = note
+      self._set_item_note(self.download_item, note)
+
+    offroad = ui_state.is_offroad()
+    self.small_model_item.action_item.set_enabled(offroad)
+    self.big_model_item.action_item.set_enabled(offroad)
+    self.small_model_item.set_description("" if offroad else tr("Only available when vehicle is off, or always offroad mode is on"))
 
   def _render(self, rect):
     self._scroller.render(rect)
 
   def show_event(self):
     self._scroller.show_event()
+    self._last_note = None  # re-expand the failover note every time the page opens

openpilot/selfdrive/ui/sunnypilot/layouts/settings/osm.py

@@ -8,7 +8,6 @@ import datetime
 import os
 import platform
 import requests
-import shutil
 import threading
 from pathlib import Path
 from time import monotonic
@@ -75,22 +74,12 @@ class OSMLayout(Widget):
   def _update_map_size(self):
     threading.Thread(target=self.calculate_size, daemon=True).start()
 
-  def _do_delete_maps(self):
-    if MAP_PATH.exists():
-      shutil.rmtree(MAP_PATH)
-
-    for param in ("OsmDownloadedDate", "OsmLocal", "OsmLocationName", "OsmLocationTitle", "OsmStateName", "OsmStateTitle"):
-      ui_state.params.remove(param)
-
+  def _on_confirm_delete_maps(self):
+    ui_state.params.put_bool("Mapd_ClearCache", True)
     self._delete_maps_btn.action_item.set_enabled(True)
     self._delete_maps_btn.action_item.set_text(tr("DELETE"))
     self._update_map_size()
 
-  def _on_confirm_delete_maps(self):
-    self._delete_maps_btn.action_item.set_enabled(False)
-    self._delete_maps_btn.action_item.set_text("DELETING...")
-    threading.Thread(target=self._do_delete_maps).start()
-
   def _delete_maps(self):
     self._show_confirm(tr("This will delete ALL downloaded maps\n\nAre you sure you want to delete all maps?"),
                        tr("Yes, delete all maps"), self._on_confirm_delete_maps)

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

@@ -9,7 +9,7 @@ from openpilot.cereal import custom
 from openpilot.selfdrive.ui.sunnypilot.layouts.onboarding import SunnylinkConsentPage
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.sunnypilot.sunnylink.api import UNREGISTERED_SUNNYLINK_DONGLE_ID
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.sunnypilot.widgets.list_view import button_item_sp
 from openpilot.system.ui.sunnypilot.widgets.list_view import toggle_item_sp
@@ -32,8 +32,8 @@ class SunnylinkHeader(Widget):
       font_size=90,
       font_weight=FontWeight.AUDIOWIDE,
       text_color=rl.WHITE,
-      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+      alignment=TextAlignment.CENTER,
+      alignment_vertical=TextAlignmentVertical.TOP,
       wrap_text=False,
       elide=False
     )
@@ -43,8 +43,8 @@ class SunnylinkHeader(Widget):
       font_size=40,
       font_weight=FontWeight.NORMAL,
       text_color=rl.Color(0, 255, 0, 255),  # Green
-      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+      alignment=TextAlignment.CENTER,
+      alignment_vertical=TextAlignmentVertical.TOP,
       wrap_text=True,
       elide=False
     )
@@ -55,8 +55,8 @@ class SunnylinkHeader(Widget):
       font_size=35,
       font_weight=FontWeight.NORMAL,
       text_color=rl.Color(255, 165, 0, 255),  # Orange
-      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+      alignment=TextAlignment.CENTER,
+      alignment_vertical=TextAlignmentVertical.TOP,
       wrap_text=True,
       elide=False
     )
@@ -109,8 +109,8 @@ class SunnylinkDescriptionItem(Widget):
       font_size=40,
       font_weight=FontWeight.NORMAL,
       text_color=rl.WHITE,
-      alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
-      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+      alignment=TextAlignment.LEFT,
+      alignment_vertical=TextAlignmentVertical.TOP,
       wrap_text=True,
       elide=False,
     )

openpilot/selfdrive/ui/sunnypilot/layouts/settings/vehicle/brands/toyota.py

@@ -23,7 +23,7 @@ DESCRIPTIONS = {
   'stop_and_go_hack': tr_noop(
     'sunnypilot will allow some Toyota/Lexus cars to auto resume during stop and go traffic. ' +
     'This feature is only applicable to certain models that are able to use longitudinal control. This is an alpha feature. Use at your own risk.'
-  )
+  ),
 }
 
 

openpilot/selfdrive/ui/sunnypilot/layouts/sidebar.py

@@ -4,11 +4,14 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
+import math
+
 import pyray as rl
 import time
 from dataclasses import dataclass
-from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.sunnypilot.sunnylink.api import UNREGISTERED_SUNNYLINK_DONGLE_ID
+from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.lib.multilang import tr_noop
 
 
@@ -18,6 +21,9 @@ METRIC_MARGIN = 30
 METRIC_START_Y = 300
 HOME_BTN = rl.Rectangle(60, 860, 180, 180)
 
+CHESTNUT_ICON_WIDTH = 180
+CHESTNUT_ICON_HEIGHT = 133
+
 
 # Color scheme
 class Colors:
@@ -53,6 +59,9 @@ class MetricData:
 class SidebarSP:
   def __init__(self):
     self._sunnylink_status = MetricData(tr_noop("SUNNYLINK"), tr_noop("OFFLINE"), Colors.WARNING)
+    self._chestnut_green_img = gui_app.texture("icons_mici/chestnut_green.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)
+    self._chestnut_default_img = gui_app.texture("icons_mici/chestnut.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)
+    self._chestnut_orange_img = gui_app.texture("icons_mici/chestnut_orange.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)
 
   def _update_sunnylink_status(self):
     if not ui_state.params.get_bool("SunnylinkEnabled"):
@@ -78,6 +87,24 @@ class SidebarSP:
 
     self._sunnylink_status.update(tr_noop("SUNNYLINK"), status, color)
 
+  def _get_home_icon(self, default_img: rl.Texture) -> tuple[rl.Texture, rl.Vector2, float]:
+    default_pos = rl.Vector2(HOME_BTN.x, HOME_BTN.y)
+    state = ui_state.chestnut_state
+    if state == ChestnutState.DISCONNECTED:
+      return default_img, default_pos, 1.0
+
+    if state == ChestnutState.LOADING:
+      icon = self._chestnut_default_img
+      opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
+    elif state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED):
+      icon, opacity = self._chestnut_orange_img, 1.0
+    else:
+      icon, opacity = self._chestnut_green_img, 1.0
+
+    x = HOME_BTN.x + (HOME_BTN.width - icon.width) / 2
+    y = HOME_BTN.y + (HOME_BTN.height - icon.height) / 2
+    return icon, rl.Vector2(x, y), opacity
+
   def _draw_metrics_w_sunnylink(self, rect: rl.Rectangle, _temp, _panda, _connect):
     metrics = [_temp, _panda, _connect, self._sunnylink_status]
     start_y = int(rect.y) + METRIC_START_Y

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

@@ -4,7 +4,12 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
+import math
+
+import pyray as rl
+
 from openpilot.selfdrive.ui.mici.layouts.home import MiciHomeLayout
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.system.ui.lib.application import FontWeight
 from openpilot.system.ui.widgets.label import UnifiedLabel
 
@@ -13,3 +18,16 @@ class MiciHomeLayoutSP(MiciHomeLayout):
   def __init__(self):
     super().__init__()
     self._openpilot_label = UnifiedLabel("sunnypilot", font_size=88, font_weight=FontWeight.AUDIOWIDE, max_width=480, wrap_text=False)
+
+  def _set_chestnut_visibility(self):
+    usb_connected = ui_state.usb_connected
+    usb_unknown = ui_state.usb_unknown
+    chestnut_state = ui_state.chestnut_state
+    loading = chestnut_state == ChestnutState.LOADING
+
+    self._usb_icon.set_visible(usb_connected and usb_unknown)
+    self._chestnut_loading_icon.set_opacity(0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0)))
+    self._chestnut_loading_icon.set_visible(not usb_unknown and loading)
+    self._chestnut_icon.set_visible(not usb_unknown and not loading and
+                                    chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE))
+    self._chestnut_failed_icon.set_visible(not usb_unknown and chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))

openpilot/selfdrive/ui/sunnypilot/mici/layouts/main.py

@@ -0,0 +1,19 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from openpilot.selfdrive.ui.mici.layouts.main import MiciMainLayout
+from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
+
+
+class MiciMainLayoutSP(MiciMainLayout):
+  def __init__(self):
+    super().__init__()
+    scroller = self._scroller
+    scroller.scroll_panel = GuiScrollPanel2SP(scroller._horizontal, handle_out_of_bounds=not scroller._snap_items)
+
+  def _should_auto_scroll_to_onroad(self) -> bool:
+    return not self._onroad_layout.is_on_info_panel()

openpilot/selfdrive/ui/sunnypilot/mici/layouts/models.py

@@ -7,16 +7,37 @@ See the LICENSE.md file in the root directory for more details.
 import pyray as rl
 
 from openpilot.cereal import custom
-from openpilot.sunnypilot.models.default_model import get_default_model
+from openpilot.selfdrive.ui.mici.widgets.dialog import BigDialog
+from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS, get_selected_bundle
 from openpilot.selfdrive.ui.mici.widgets.button import BigButton
-from openpilot.selfdrive.ui.sunnypilot.layouts.settings.models import ModelsLayout
 from openpilot.selfdrive.ui.ui_state import ui_state, device
+from openpilot.selfdrive.ui.sunnypilot.model_info import (active_source, big_model_state, bundles_for_source, carrying_model,
+                                                           default_model_name, model_info, queued_name)
 from openpilot.system.ui.lib.application import FontWeight, gui_app
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets.scroller import NavScroller
 
+def _model_info() -> tuple[str, str, str]:
+  """(active model, info header, info text) for the panel. Runner-matched: the
+  active line names what actually drives, and a notable big-model state takes
+  the info pair."""
+  source, active_name, other_name = model_info()
+  state = big_model_state()
+  _, _, carry_display = carrying_model()
+  if carry_display is None:
+    big = get_selected_bundle(ui_state.params, "chestnut")
+    carry_display = big.displayName if big else default_model_name("chestnut")
+  active_text = (carry_display or active_name).lower()
+  if state == 'failed':
+    return active_text, tr("big model"), tr("unavailable")
+  if state == 'loading':
+    return active_text, tr("big model"), tr("getting ready")
+  header = tr("small model") if source == "chestnut" else tr("big model")
+  return active_text, header, other_name.lower()
+
+
 class CurrentModelInfo(Widget):
   def __init__(self):
     super().__init__()
@@ -26,12 +47,12 @@ class CurrentModelInfo(Widget):
     header_color = rl.Color(255, 255, 255, int(255 * 0.9))
     subheader_color = rl.Color(255, 255, 255, int(255 * 0.9 * 0.65))
     max_width = int(self._rect.width - 20)
+    active_text, info_header, info_text = _model_info()
     self.current_model_header = UnifiedLabel(tr("active model"), 48, max_width=max_width, text_color=header_color, font_weight=FontWeight.DISPLAY)
-    default_text = f"{get_default_model()} (Default)".lower()
-    self.current_model_text = UnifiedLabel(default_text, 32, max_width=max_width, text_color=subheader_color, font_weight=FontWeight.ROMAN, scroll=True)
+    self.current_model_text = UnifiedLabel(active_text, 32, max_width=max_width, text_color=subheader_color, font_weight=FontWeight.ROMAN, scroll=True)
 
-    self.info_header = UnifiedLabel("cache size", 48, max_width=max_width, text_color=header_color, font_weight=FontWeight.DISPLAY)
-    self.info_text = UnifiedLabel("0 mb", 32, max_width=max_width, text_color=subheader_color, font_weight=FontWeight.ROMAN)
+    self.info_header = UnifiedLabel(info_header, 48, max_width=max_width, text_color=header_color, font_weight=FontWeight.DISPLAY)
+    self.info_text = UnifiedLabel(info_text, 32, max_width=max_width, text_color=subheader_color, font_weight=FontWeight.ROMAN, scroll=True)
 
   def _render(self, _):
     self.current_model_header.set_position(self._rect.x + 20, self._rect.y - 10)
@@ -55,12 +76,13 @@ class ModelsLayoutMici(NavScroller):
     self._download_progress = "."
     self._download_frame = 0
     self._was_downloading = False
+    self._selection_source: str | None = None
 
     self.select_model_btn = BigButton(tr("select model"))
     self.select_model_btn.set_click_callback(self._show_folders)
 
     self.cancel_download_btn = BigButton(tr("cancel download"))
-    self.cancel_download_btn.set_click_callback(lambda: ui_state.params.remove("ModelManager_DownloadIndex"))
+    self.cancel_download_btn.set_click_callback(lambda: ui_state.params.remove("ModelManager_DownloadRef"))
 
     self.main_items = [self.current_model_info, self.select_model_btn, self.cancel_download_btn]
     self._scroller.add_widgets(self.main_items)
@@ -69,8 +91,7 @@ class ModelsLayoutMici(NavScroller):
   def model_manager(self):
     return ui_state.sm["modelManagerSP"]
 
-  def _get_grouped_bundles(self, favorites = None):
-    bundles = self.model_manager.availableBundles
+  def _get_grouped_bundles(self, bundles, favorites = None):
     folders = {}
     for bundle in bundles:
       folder = next((override.value for override in bundle.overrides if override.key == "folder"), "")
@@ -90,47 +111,70 @@ class ModelsLayoutMici(NavScroller):
   def _show_folders(self):
     self.focused_widget = self.select_model_btn
 
+    hardware_btns = []
+    active = active_source()
+    for source, label in (("qcom", tr("small models")), ("chestnut", tr("big models"))):
+      bundle = get_selected_bundle(ui_state.params, source)
+      value = (bundle.internalName if bundle else default_model_name(source)).lower()
+      if source == active:
+        value += f" ({tr('active')})"
+      btn = BigButton(label.lower(), value=value)
+      btn.set_click_callback(lambda s=source: self._select_hardware(s))
+      hardware_btns.append(btn)
+    self._push_selection_view(hardware_btns)
+
+  def _select_hardware(self, source):
+    self._selection_source = source
+
     favs = ui_state.params.get("ModelManager_Favs")
     favorites = set(favs.split(';')) if favs else set()
 
-    folders = self._get_grouped_bundles(favorites)
+    bundles = bundles_for_source(source)
+    if not bundles:
+      gui_app.push_widget(BigDialog(title=tr("No models available"),
+                                    description=tr("No models are available for this hardware yet. Connect to the internet and refresh the model list.")))
+      return
+    folders = self._get_grouped_bundles(bundles, favorites)
+
     folder_buttons = []
-    default_btn = BigButton(f"{get_default_model()} (Default)".lower())
-    default_btn.set_click_callback(self._select_default)
+    default_btn = BigButton(default_model_name(source).lower())
+    default_btn.set_click_callback(lambda s=source: self._select_default(s))
     folder_buttons.append(default_btn)
 
     for folder in sorted(folders.keys(), key=lambda f: max((bundle.index for bundle in folders[f]), default=-1), reverse=True):
-      if folder.lower() in ["release models", "master models", "favorites"]:
-        btn = BigButton(folder.lower())
-        btn.set_click_callback(lambda f=folder: self._select_folder(f))
-        if folder.lower() == "favorites":
-          folder_buttons.insert(0, btn)
-        else:
-          folder_buttons.append(btn)
+      btn = BigButton(folder.lower())
+      btn.set_click_callback(lambda f=folder: self._select_folder(f))
+      if folder.lower() == "favorites":
+        folder_buttons.insert(0, btn)
+      else:
+        folder_buttons.append(btn)
     self._push_selection_view(folder_buttons)
 
   def _pop_to_main(self):
     gui_app.pop_widgets_to(self)
+    self._scroller.scroll_panel.set_offset(0.0)
 
   def _select_model(self, bundle):
-    ui_state.params.put("ModelManager_DownloadIndex", bundle.index)
+    ui_state.params.put("ModelManager_DownloadRef", bundle.ref)
     self._pop_to_main()
 
-  def _select_default(self):
-    ui_state.params.remove("ModelManager_ActiveBundle")
+  def _select_default(self, source):
+    ui_state.params.remove(ACTIVE_BUNDLE_KEYS[source])
     self._pop_to_main()
 
   def _select_folder(self, folder_name):
+    source = self._selection_source
+    if source is None:  # folders are only reachable after picking a hardware
+      return
     favs = ui_state.params.get("ModelManager_Favs")
     favorites = set(favs.split(';')) if favs else set()
 
-    folders = self._get_grouped_bundles(favorites)
+    folders = self._get_grouped_bundles(bundles_for_source(source), favorites)
     bundles = sorted(folders.get(folder_name, []), key=lambda b: b.index, reverse=True)
 
     btns = []
     for bundle in bundles:
-      txt = bundle.displayName.lower()
-      btn = BigButton(txt)
+      btn = BigButton(bundle.displayName.lower())
       btn.set_click_callback(lambda b=bundle: self._select_model(b))
       btns.append(btn)
     self._push_selection_view(btns)
@@ -162,11 +206,10 @@ class ModelsLayoutMici(NavScroller):
     self._was_downloading = is_downloading
 
     self.current_model_info.current_model_header.set_text(tr("active model"))
-    default_model_text = f"{get_default_model()} (Default)".lower()
-    model_text = manager.activeBundle.displayName.lower() if manager.activeBundle.ref else default_model_text
-    self.current_model_info.current_model_text.set_text(model_text)
-    self.current_model_info.info_header.set_text(tr("cache size"))
-    self.current_model_info.info_text.set_text(f"{ModelsLayout.calculate_cache_size():.2f} MB")
+    active_text, info_header, info_text = _model_info()
+    self.current_model_info.current_model_text.set_text(active_text)
+    self.current_model_info.info_header.set_text(info_header)
+    self.current_model_info.info_text.set_text(info_text)
 
     if manager.selectedBundle and manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.failed:
       self.current_model_info.info_header.set_text(tr("error") + self._download_progress)
@@ -177,18 +220,29 @@ class ModelsLayoutMici(NavScroller):
       device.set_override_interactive_timeout(5)
       progress = 0.0
       count = 0
+      verifying = False
       for model in manager.selectedBundle.models:
         count += 1
         p = model.artifact.downloadProgress
-        if p.status == custom.ModelManagerSP.DownloadStatus.downloading:
+        if p.status in (custom.ModelManagerSP.DownloadStatus.downloading,
+                        custom.ModelManagerSP.DownloadStatus.verifying):
           progress += p.progress
+          verifying = verifying or p.status == custom.ModelManagerSP.DownloadStatus.verifying
         elif p.status in (custom.ModelManagerSP.DownloadStatus.downloaded,
                           custom.ModelManagerSP.DownloadStatus.cached):
           progress += 100.0
 
-      self.current_model_info.current_model_header.set_text(tr("downloading"))
+      self.current_model_info.current_model_header.set_text(tr("verifying") if verifying else tr("downloading"))
+      self.cancel_download_btn.set_text(tr("cancel verification") if verifying else tr("cancel download"))
       self.current_model_info.current_model_header._shimmer = True
-      self.current_model_info.current_model_text.set_text(f"{manager.selectedBundle.internalName.lower()}")
+      name_text = manager.selectedBundle.internalName.lower()
+      if queued := queued_name(manager.selectedBundle.ref):
+        name_text += f"  |  {queued.lower()} {tr('queued')}"
+      self.current_model_info.current_model_text.set_text(name_text)
       self.current_model_info.info_header.set_text(tr("progress") + self._download_progress)
       self.current_model_info.info_header._shimmer = True
       self.current_model_info.info_text.set_text(f"{progress/count:.2f}%")
+
+    elif manager.selectedBundle and manager.selectedBundle.status == custom.ModelManagerSP.DownloadStatus.downloaded:
+      self.current_model_info.info_header.set_text(tr("downloaded"))
+      self.current_model_info.info_text.set_text(tr("downloaded"))

openpilot/selfdrive/ui/sunnypilot/mici/layouts/onroad.py

@@ -0,0 +1,64 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+from collections.abc import Callable
+import pyray as rl
+from openpilot.system.ui.lib.application import gui_app
+from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroller_sp import ScrollerSP
+from openpilot.selfdrive.ui.sunnypilot.mici.onroad.augmented_road_view import AugmentedRoadViewSP
+from openpilot.selfdrive.ui.sunnypilot.mici.layouts.onroad_info_panel import OnroadInfoPanel
+
+CONFIDENCE_BALL_VISIBLE_RATIO = 0.4
+HORIZONTAL_SETTLE_PX = 5
+HORIZONTAL_RESET_RATIO = 0.5
+
+
+class OnroadViewContainerSP(ScrollerSP):
+  def __init__(self, bookmark_callback=None):
+    super().__init__(horizontal=False, snap_items=True, spacing=0, pad=0, scroll_indicator=False, edge_shadows=False)
+    self.road_view = AugmentedRoadViewSP(bookmark_callback=bookmark_callback)
+    self.onroad_info_panel = OnroadInfoPanel(bookmark_callback=bookmark_callback)
+
+    self._scroller.add_widgets([
+      self.road_view,
+      self.onroad_info_panel,
+    ])
+    self._scroller.set_reset_scroll_at_show(False)
+    self._scroller.set_scrolling_enabled(lambda: abs(self.rect.x) < HORIZONTAL_SETTLE_PX)
+
+    for child in (self.road_view, self.onroad_info_panel):
+      inner_touch_valid = child._touch_valid_callback
+      child.set_touch_valid_callback(
+        lambda inner=inner_touch_valid: self._touch_valid() and (inner() if inner else True)
+      )
+
+  def set_rect(self, rect: rl.Rectangle):
+    super().set_rect(rect)
+    self.road_view.set_rect(rect)
+    self.onroad_info_panel.set_rect(rect)
+    return self
+
+  def is_swiping_left(self) -> bool:
+    return self.road_view.is_swiping_left() or self.onroad_info_panel.is_swiping_left()
+
+  def set_click_callback(self, click_callback: Callable[[], None] | None) -> None:
+    self.road_view.set_click_callback(click_callback)
+    self.onroad_info_panel.set_click_callback(click_callback)
+
+  def is_on_info_panel(self) -> bool:
+    """True when scrolled past halfway toward onroad_info_panel (used by main layout
+    to skip auto-pop-back-to-camera while user is reading the info panel)."""
+    return abs(self._scroller.scroll_panel.get_offset()) > self._rect.height / 2
+
+  def _render(self, rect: rl.Rectangle):
+    if abs(self.rect.x) > gui_app.width * HORIZONTAL_RESET_RATIO:
+      self._scroller.scroll_panel.set_offset(0)
+
+    vertical_offset = self._scroller.scroll_panel.get_offset()
+    show_ball = abs(vertical_offset) < rect.height * CONFIDENCE_BALL_VISIBLE_RATIO
+    self.road_view.set_show_confidence_ball(show_ball)
+
+    super()._render(rect)

openpilot/selfdrive/ui/sunnypilot/mici/layouts/onroad_info_panel.py

@@ -0,0 +1,403 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import pyray as rl
+from dataclasses import dataclass, field
+from openpilot.common.constants import CV
+from openpilot.common.filter_simple import FirstOrderFilter
+from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
+from openpilot.system.ui.lib.multilang import tr
+from openpilot.system.ui.lib.text_measure import measure_text_cached
+from openpilot.system.ui.widgets import Widget
+from openpilot.selfdrive.ui.mici.onroad.alert_renderer import AlertRenderer
+from openpilot.selfdrive.ui.mici.onroad.augmented_road_view import BookmarkIcon
+
+METER_TO_KM = 0.001
+METER_TO_MILE = 0.000621371
+
+CONTENT_MARGIN = 16
+SPEED_LIMIT_SIGN_WIDTH = 146
+VIENNA_SIGN_SIZE = 146
+MUTCD_SIGN_HEIGHT = 178
+OFFSET_BADGE_SIZE = 50
+OFFSET_BADGE_PANEL_PADDING = 4
+MUTCD_OFFSET_SIGN_Y_SHIFT = 6
+VIENNA_BADGE_X_RATIO = 0.80
+VIENNA_BADGE_UPCOMING_X_RATIO = 0.70
+VIENNA_BADGE_Y_RATIO = -0.82
+UPCOMING_SIGN_SIZE_RATIO = 0.76
+UPCOMING_SIGN_OVERLAP_RATIO = 0.05
+UNIT_FONT_SIZE = 40
+SPEED_FONT_SIZE = 114
+ROAD_FONT_SIZE = 32
+SCC_TAG_WIDTH = 78
+SCC_TAG_HEIGHT = 30
+SCC_TAG_GAP = 5
+COLUMN_GAP = 12
+
+
+@dataclass(frozen=True)
+class OnroadInfoPanelColors:
+  white: rl.Color = rl.WHITE
+  black: rl.Color = rl.BLACK
+  red: rl.Color = field(default_factory=lambda: rl.Color(255, 0, 0, 255))
+  green: rl.Color = field(default_factory=lambda: rl.Color(0, 255, 0, 255))
+  grey: rl.Color = field(default_factory=lambda: rl.Color(190, 195, 190, 255))
+  light_grey: rl.Color = field(default_factory=lambda: rl.Color(200, 200, 200, 255))
+  dark_grey: rl.Color = field(default_factory=lambda: rl.Color(100, 100, 100, 255))
+  bg_dark: rl.Color = field(default_factory=lambda: rl.Color(0, 0, 0, 255))
+  card_bg: rl.Color = field(default_factory=lambda: rl.Color(50, 50, 50, 200))
+  badge_bg: rl.Color = field(default_factory=lambda: rl.Color(60, 60, 60, 255))
+
+
+COLORS = OnroadInfoPanelColors()
+
+
+class OnroadInfoPanel(Widget):
+  def __init__(self, bookmark_callback=None):
+    super().__init__()
+    self.speed_limit: float = 0.0
+    self.speed_limit_valid: bool = False
+    self.speed_limit_offset: float = 0.0
+    self.next_speed_limit: float = 0.0
+    self.next_speed_limit_distance: float = 0.0
+    self.road_name: str = ""
+    self.current_speed: float = 0.0
+    self.set_speed: float = 0.0
+    self.cruise_enabled: bool = False
+
+    self._sign_slide: float = 0.0
+
+    self._font_bold: rl.Font = gui_app.font(FontWeight.BOLD)
+    self._font_semi_bold: rl.Font = gui_app.font(FontWeight.SEMI_BOLD)
+    self._font_medium: rl.Font = gui_app.font(FontWeight.MEDIUM)
+
+    self._marquee_offset: float = 0.0
+    self._marquee_direction: int = 1
+    self._marquee_pause_timer: float = 0.0
+    self._marquee_speed: float = 40.0
+    self._marquee_pause_duration: float = 1.5
+
+    self._alert_renderer = AlertRenderer()
+    self._alert_alpha_filter = FirstOrderFilter(0, 0.05, 1 / gui_app.target_fps)
+
+    self._bookmark_icon = BookmarkIcon(bookmark_callback)
+
+  def is_swiping_left(self) -> bool:
+    return self._bookmark_icon.is_swiping_left()
+
+  def _handle_mouse_release(self, mouse_pos: MousePos) -> None:
+    # Mirror stock AugmentedRoadView: suppress click while bookmark gesture active
+    if not self._bookmark_icon.interacting():
+      super()._handle_mouse_release(mouse_pos)
+
+  def _update_state(self) -> None:
+    sm = ui_state.sm
+    speed_conv = CV.MS_TO_KPH if ui_state.is_metric else CV.MS_TO_MPH
+
+    if sm.valid["longitudinalPlanSP"]:
+      lp_sp = sm["longitudinalPlanSP"]
+      resolver = lp_sp.speedLimit.resolver
+      self.speed_limit = resolver.speedLimit * speed_conv
+      self.speed_limit_valid = resolver.speedLimitValid
+      self.speed_limit_offset = resolver.speedLimitOffset * speed_conv
+
+    if sm.valid["liveMapDataSP"]:
+      lmd = sm["liveMapDataSP"]
+      self.next_speed_limit = lmd.speedLimitAhead * speed_conv
+      self.next_speed_limit_distance = lmd.speedLimitAheadDistance
+      self.road_name = lmd.roadName
+
+    if sm.updated["carState"]:
+      self.current_speed = sm["carState"].vEgo * speed_conv
+
+    if sm.valid["carState"] and sm.valid["controlsState"]:
+      self.cruise_enabled = sm["carState"].cruiseState.enabled
+      v_cruise_cluster = sm["carState"].vCruiseCluster
+      set_speed_kph = sm["controlsState"].vCruiseDEPRECATED if v_cruise_cluster == 0.0 else v_cruise_cluster
+      self.set_speed = set_speed_kph * (METER_TO_MILE / METER_TO_KM) if not ui_state.is_metric else set_speed_kph
+
+  def _render(self, rect: rl.Rectangle) -> None:
+    self._update_state()
+
+    rl.draw_rectangle(int(rect.x), int(rect.y), int(rect.width), int(rect.height), COLORS.bg_dark)
+
+    left_x = rect.x + CONTENT_MARGIN
+
+    if self.cruise_enabled:
+      unit = tr("MAX")
+      display_speed = self.set_speed
+    else:
+      unit = tr("km/h") if ui_state.is_metric else tr("MPH")
+      display_speed = self.current_speed
+
+    display_speed_text = str(round(display_speed))
+    if self.speed_limit_valid and display_speed > self.speed_limit:
+      speed_color = COLORS.red
+    else:
+      speed_color = COLORS.white
+
+    sign_width = min(SPEED_LIMIT_SIGN_WIDTH, rect.width * 0.30)
+    sign_height = VIENNA_SIGN_SIZE if ui_state.is_metric else MUTCD_SIGN_HEIGHT
+
+    has_upcoming_limit = self.next_speed_limit > 0 and self.next_speed_limit != self.speed_limit
+    target_sign_slide = 1.0 if has_upcoming_limit else 0.0
+    slide_speed = 3.0 * rl.get_frame_time()
+    if self._sign_slide < target_sign_slide:
+      self._sign_slide = min(self._sign_slide + slide_speed, target_sign_slide)
+    elif self._sign_slide > target_sign_slide:
+      self._sign_slide = max(self._sign_slide - slide_speed, target_sign_slide)
+
+    upcoming_width = int(sign_width * UPCOMING_SIGN_SIZE_RATIO)
+    upcoming_height = int(sign_height * UPCOMING_SIGN_SIZE_RATIO)
+    upcoming_reserved_width = int(upcoming_width * 0.85) + 5
+    sign_x_without_upcoming = rect.x + rect.width - sign_width - CONTENT_MARGIN
+    sign_x_with_upcoming = rect.x + rect.width - sign_width - CONTENT_MARGIN - upcoming_reserved_width
+    sign_x = sign_x_without_upcoming + (sign_x_with_upcoming - sign_x_without_upcoming) * self._sign_slide
+    sign_y = rect.y + (rect.height - sign_height) / 2
+    if not ui_state.is_metric and self.speed_limit_offset != 0 and self.speed_limit_valid:
+      sign_y += MUTCD_OFFSET_SIGN_Y_SHIFT
+
+    readout_right = sign_x - COLUMN_GAP
+    readout_width = max(1, readout_right - left_x)
+    road_y = rect.y + rect.height - 44
+
+    unit_font_size = self._fit_font_size(self._font_semi_bold, unit, readout_width, 46, UNIT_FONT_SIZE, 28)
+    speed_font_size = self._fit_font_size(self._font_bold, display_speed_text, readout_width, road_y - (rect.y + 54) - 8,
+                                          SPEED_FONT_SIZE, 76)
+    speed_size = measure_text_cached(self._font_bold, display_speed_text, speed_font_size)
+    speed_y = min(rect.y + 54, road_y - speed_size.y - 8)
+    unit_y = max(rect.y + 14, speed_y - unit_font_size - 6)
+
+    rl.draw_text_ex(self._font_semi_bold, unit, rl.Vector2(left_x, unit_y), unit_font_size, 0, COLORS.grey)
+    rl.draw_text_ex(self._font_bold, display_speed_text, rl.Vector2(left_x, speed_y), speed_font_size, 0, speed_color)
+    self._draw_road_name(left_x, road_y, readout_width)
+
+    if has_upcoming_limit and self._sign_slide > 0.01:
+      upcoming_speed_text = str(round(self.next_speed_limit))
+      distance_text = self._format_distance(self.next_speed_limit_distance)
+      upcoming_x = sign_x + sign_width - int(upcoming_width * UPCOMING_SIGN_OVERLAP_RATIO)
+      upcoming_y = sign_y + (sign_height - upcoming_height) / 2
+
+      upcoming_speed_color = COLORS.black
+      if ui_state.is_metric:
+        self._draw_vienna_sign(upcoming_x, upcoming_y, upcoming_width, upcoming_height, upcoming_speed_text, upcoming_speed_color, is_upcoming=True)
+      else:
+        self._draw_mutcd_sign(upcoming_x, upcoming_y, upcoming_width, upcoming_height, upcoming_speed_text, upcoming_speed_color, is_upcoming=True)
+
+      distance_font_size = self._fit_font_size(self._font_medium, distance_text, upcoming_width, 30, 24, 16)
+      distance_size = measure_text_cached(self._font_medium, distance_text, distance_font_size)
+      rl.draw_text_ex(self._font_medium, distance_text, rl.Vector2(upcoming_x + upcoming_width / 2 - distance_size.x / 2, upcoming_y + upcoming_height),
+                      distance_font_size, 0, COLORS.grey)
+
+    self._draw_speed_limit_sign(sign_x, sign_y, sign_width, sign_height)
+
+    if self.speed_limit_offset != 0 and self.speed_limit_valid:
+      offset_text = str(abs(round(self.speed_limit_offset)))
+      badge_size = OFFSET_BADGE_SIZE
+      badge_rect = self._offset_badge_rect(rect, sign_x, sign_y, sign_width, sign_height, badge_size, has_upcoming_limit)
+
+      if ui_state.is_metric:
+        badge_radius = badge_size / 2
+        badge_center_x = badge_rect.x + badge_radius
+        badge_center_y = badge_rect.y + badge_radius
+        rl.draw_circle(int(badge_center_x), int(badge_center_y), badge_radius + 2, COLORS.dark_grey)
+        rl.draw_circle(int(badge_center_x), int(badge_center_y), badge_radius, COLORS.badge_bg)
+        self._draw_text_centered_fit(self._font_bold, offset_text, 32, rl.Vector2(badge_center_x, badge_center_y), COLORS.white,
+                                     badge_size - 10, badge_size - 8, min_size=24)
+      else:
+        rl.draw_rectangle_rounded(badge_rect, 0.25, 10, COLORS.badge_bg)
+        rl.draw_rectangle_rounded_lines_ex(badge_rect, 0.25, 10, 2, COLORS.dark_grey)
+        self._draw_text_centered_fit(self._font_bold, offset_text, 32, rl.Vector2(badge_rect.x + badge_size / 2, badge_rect.y + badge_size / 2),
+                                     COLORS.white, badge_size - 10, badge_size - 8, min_size=24)
+
+    scc_tag_x = min(left_x + speed_size.x + COLUMN_GAP, readout_right - SCC_TAG_WIDTH)
+    scc_tag_y = speed_y + (speed_size.y - (SCC_TAG_HEIGHT * 2 + SCC_TAG_GAP)) / 2
+    if scc_tag_x >= left_x + speed_size.x + 8:
+      self._draw_scc_icons(scc_tag_x, scc_tag_y, readout_right)
+
+    self._bookmark_icon.render(rect)
+
+    if ui_state.started:
+      alert_obj, no_alert = self._alert_renderer.will_render()
+      self._alert_alpha_filter.update(0 if no_alert else 1)
+      alpha = self._alert_alpha_filter.x
+      if alpha > 0.01:
+        rl.draw_rectangle(int(rect.x), int(rect.y), int(rect.width), int(rect.height), rl.Color(0, 0, 0, int(150 * alpha)))
+      self._alert_renderer.render(rect)
+
+  def _draw_scc_icons(self, x: float, y: float, right_limit: float) -> None:
+    sm = ui_state.sm
+    if not sm.valid["longitudinalPlanSP"]:
+      return
+    scc = sm["longitudinalPlanSP"].smartCruiseControl
+
+    drawn = 0
+
+    for label, active in [("SCC-V", scc.vision.active), ("SCC-M", scc.map.active)]:
+      if not active:
+        continue
+      tag_x = x
+      if tag_x + SCC_TAG_WIDTH > right_limit:
+        return
+      tag_y = y + drawn * (SCC_TAG_HEIGHT + SCC_TAG_GAP)
+      rl.draw_rectangle_rounded(rl.Rectangle(tag_x, tag_y, SCC_TAG_WIDTH, SCC_TAG_HEIGHT), 0.3, 10, COLORS.green)
+      self._draw_text_centered_fit(self._font_bold, label, 18, rl.Vector2(tag_x + SCC_TAG_WIDTH / 2, tag_y + SCC_TAG_HEIGHT / 2), COLORS.black,
+                                   SCC_TAG_WIDTH - 10, SCC_TAG_HEIGHT - 4, min_size=14)
+      drawn += 1
+
+  def _draw_speed_limit_sign(self, x: float, y: float, sign_width: float, sign_height: float) -> None:
+    speed_str = str(round(self.speed_limit)) if self.speed_limit_valid and self.speed_limit > 0 else "--"
+    speed_color = COLORS.black if not self.speed_limit_valid or self.current_speed <= self.speed_limit else COLORS.red
+
+    if ui_state.is_metric:
+      self._draw_vienna_sign(x, y, sign_width, sign_height, speed_str, speed_color, is_upcoming=False)
+    else:
+      self._draw_mutcd_sign(x, y, sign_width, sign_height, speed_str, speed_color, is_upcoming=False)
+
+  def _draw_road_name(self, x: float, y: float, width: float) -> None:
+    if width <= 0:
+      return
+
+    road_display = self.road_name if self.road_name else "--"
+    font_size = self._fit_font_size(self._font_semi_bold, road_display, width, 38, ROAD_FONT_SIZE, 28)
+    road_size = measure_text_cached(self._font_semi_bold, road_display, font_size)
+    text_width = road_size.x
+
+    if text_width <= width:
+      self._marquee_offset = 0.0
+      self._marquee_direction = 1
+      self._marquee_pause_timer = 0.0
+      rl.draw_text_ex(self._font_semi_bold, road_display, rl.Vector2(x, y), font_size, 0, COLORS.white)
+    else:
+      overflow = text_width - width
+      dt = rl.get_frame_time()
+
+      if self._marquee_pause_timer > 0:
+        self._marquee_pause_timer -= dt
+      else:
+        self._marquee_offset += self._marquee_direction * self._marquee_speed * dt
+
+        if self._marquee_offset >= overflow:
+          self._marquee_offset = overflow
+          self._marquee_direction = -1
+          self._marquee_pause_timer = self._marquee_pause_duration
+        elif self._marquee_offset <= 0:
+          self._marquee_offset = 0
+          self._marquee_direction = 1
+          self._marquee_pause_timer = self._marquee_pause_duration
+
+      rl.begin_scissor_mode(int(x), int(y), int(width), int(road_size.y + 4))
+      text_pos = rl.Vector2(x - self._marquee_offset, y)
+      rl.draw_text_ex(self._font_semi_bold, road_display, text_pos, font_size, 0, COLORS.white)
+      rl.end_scissor_mode()
+
+  def _draw_vienna_sign(self, x: float, y: float, width: float, height: float, speed_str: str, speed_color: rl.Color, is_upcoming: bool = False) -> None:
+    center = rl.Vector2(x + width / 2, y + height / 2)
+    outer_radius = min(width, height) / 2
+
+    rl.draw_circle_v(center, outer_radius, COLORS.white)
+    ring_width = outer_radius * 0.18
+    rl.draw_ring(center, outer_radius - ring_width, outer_radius, 0, 360, 36, COLORS.red)
+
+    font_size = outer_radius * (0.7 if len(speed_str) >= 3 else 0.9)
+    self._draw_text_centered_fit(self._font_bold, speed_str, int(font_size), center, speed_color, width * 0.72, height * 0.50, min_size=24)
+
+  def _draw_mutcd_sign(self, x: float, y: float, width: float, height: float, speed_str: str, speed_color: rl.Color, is_upcoming: bool = False) -> None:
+    sign_rect = rl.Rectangle(x, y, width, height)
+    rl.draw_rectangle_rounded(sign_rect, 0.35, 10, COLORS.white)
+
+    inset = max(4, width * 0.05)
+    inner_rect = rl.Rectangle(x + inset, y + inset, width - inset * 2, height - inset * 2)
+    outer_radius = 0.35 * width / 2.0
+    inner_radius = outer_radius - inset
+    inner_roundness = inner_radius / (inner_rect.width / 2.0)
+    rl.draw_rectangle_rounded_lines_ex(inner_rect, inner_roundness, 10, 3, COLORS.black)
+
+    mid_x = x + width / 2
+    label_size = max(18, int(width * 0.26))
+    if is_upcoming:
+      self._draw_text_centered_fit(self._font_bold, tr("AHEAD"), int(width * 0.34), rl.Vector2(mid_x, y + height * 0.28), COLORS.black,
+                                   width * 0.94, height * 0.32, min_size=20)
+    else:
+      self._draw_text_centered_fit(self._font_bold, tr("SPEED"), label_size, rl.Vector2(mid_x, y + height * 0.20), COLORS.black,
+                                   width * 0.84, height * 0.24, min_size=16)
+      self._draw_text_centered_fit(self._font_bold, tr("LIMIT"), label_size, rl.Vector2(mid_x, y + height * 0.40), COLORS.black,
+                                   width * 0.84, height * 0.24, min_size=16)
+
+    speed_font_size = int(width * 0.60) if len(speed_str) >= 3 else int(width * 0.72)
+    self._draw_text_centered_fit(self._font_bold, speed_str, speed_font_size, rl.Vector2(mid_x, y + height * 0.72), speed_color,
+                                 width * 0.90, height * 0.52, min_size=32)
+
+  def _draw_text_centered(self, font, text, size, pos_center, color):
+    sz = measure_text_cached(font, text, size)
+    rl.draw_text_ex(font, text, rl.Vector2(pos_center.x - sz.x / 2, pos_center.y - sz.y / 2), size, 0, color)
+
+  def _draw_text_centered_fit(self, font, text, size, pos_center, color, max_width: float, max_height: float, min_size: int = 10):
+    size = self._fit_font_size(font, text, max_width, max_height, size, min_size)
+    self._draw_text_centered(font, text, size, pos_center, color)
+
+  def _fit_font_size(self, font, text: str, max_width: float, max_height: float, max_size: int | float, min_size: int) -> int:
+    size = int(max_size)
+    while size > min_size:
+      text_size = measure_text_cached(font, text, size)
+      if text_size.x <= max_width and text_size.y <= max_height:
+        return size
+      size -= 2
+    return min_size
+
+  def _offset_badge_rect(self, panel_rect: rl.Rectangle, sign_x: float, sign_y: float, sign_width: float, sign_height: float,
+                         badge_size: float, has_upcoming_limit: bool) -> rl.Rectangle:
+    if ui_state.is_metric:
+      radius = min(sign_width, sign_height) / 2
+      center_x = sign_x + sign_width / 2
+      center_y = sign_y + sign_height / 2
+      badge_x_ratio = VIENNA_BADGE_UPCOMING_X_RATIO if has_upcoming_limit else VIENNA_BADGE_X_RATIO
+      badge_center_x = center_x + radius * badge_x_ratio
+      badge_center_y = center_y + radius * VIENNA_BADGE_Y_RATIO
+      badge_x = badge_center_x - badge_size / 2
+      badge_y = badge_center_y - badge_size / 2
+    else:
+      badge_x = sign_x + sign_width - badge_size * 0.45
+      badge_y = sign_y - badge_size * 0.75
+
+    return rl.Rectangle(
+      self._clamp(
+        badge_x,
+        panel_rect.x + OFFSET_BADGE_PANEL_PADDING,
+        panel_rect.x + panel_rect.width - badge_size - OFFSET_BADGE_PANEL_PADDING,
+      ),
+      self._clamp(
+        badge_y,
+        panel_rect.y + OFFSET_BADGE_PANEL_PADDING,
+        panel_rect.y + panel_rect.height - badge_size - OFFSET_BADGE_PANEL_PADDING,
+      ),
+      badge_size,
+      badge_size,
+    )
+
+  @staticmethod
+  def _clamp(value: float, min_value: float, max_value: float) -> float:
+    return max(min_value, min(max_value, value))
+
+  def _format_distance(self, distance: float) -> str:
+    if ui_state.is_metric:
+      if distance < 50:
+        return tr("Near")
+      if distance >= 1000:
+        return f"{distance * METER_TO_KM:.1f}" + tr("km")
+      if distance < 200:
+        rounded = max(10, int(distance / 10) * 10)
+      else:
+        rounded = int(distance / 100) * 100
+      return str(rounded) + tr("m")
+    else:
+      distance_mi = distance * METER_TO_MILE
+      if distance_mi < 0.1:
+        return tr("Near")
+      return f"{distance_mi:.1f}" + tr("mi")

openpilot/selfdrive/ui/sunnypilot/mici/layouts/settings.py

@@ -12,13 +12,23 @@ from openpilot.selfdrive.ui.mici.widgets.dialog import BigConfirmationDialog, Bi
 from openpilot.selfdrive.ui.sunnypilot.mici.layouts.sunnylink import SunnylinkLayoutMici
 from openpilot.selfdrive.ui.sunnypilot.mici.layouts.models import ModelsLayoutMici
 from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.lib.application import gui_app
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.lib.multilang import tr
 
 ICON_SIZE = 70
 BIG_ICON_SIZE = 110
 
 
+class SunnylinkBigButton(SettingsBigButton):
+  def __init__(self, *args, **kwargs):
+    super().__init__(*args, **kwargs)
+    self._label.set_font_weight(FontWeight.AUDIOWIDE)
+
+  def _get_label_font_size(self):
+    # Audiowide runs wider than Inter: "sunnylink" wraps to two lines at 64
+    return 56
+
+
 class SettingsLayoutSP(OP.SettingsLayout):
   def __init__(self):
     OP.SettingsLayout.__init__(self)
@@ -33,7 +43,7 @@ class SettingsLayoutSP(OP.SettingsLayout):
     self.icon_offroad_slider = gui_app.texture("icons_mici/settings/device/lkas.png", BIG_ICON_SIZE, BIG_ICON_SIZE)
 
     sunnylink_panel = SunnylinkLayoutMici()
-    sunnylink_btn = SettingsBigButton(tr("sunnylink"), "", gui_app.texture("icons_mici/settings/developer/ssh.png", 55, 55))
+    sunnylink_btn = SunnylinkBigButton(tr("sunnylink"), "", gui_app.texture("../../sunnypilot/selfdrive/assets/icons_mici/sunnylink.png", 76, 44))
     sunnylink_btn.set_click_callback(lambda: gui_app.push_widget(sunnylink_panel))
 
     models_panel = ModelsLayoutMici()
@@ -56,8 +66,8 @@ class SettingsLayoutSP(OP.SettingsLayout):
 
     items = self._scroller._items.copy()
 
-    items.insert(1, sunnylink_btn)
-    items.insert(2, models_btn)
+    items.insert(1, models_btn)
+    items.insert(5, sunnylink_btn)
 
     # front slots (only one ever visible at a time): exit-always-offroad, then enable-onroad
     items.insert(0, self._enable_offroad_btn_onroad)

openpilot/selfdrive/ui/sunnypilot/mici/onroad/augmented_road_view.py

@@ -0,0 +1,29 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from openpilot.selfdrive.ui.mici.onroad.augmented_road_view import AugmentedRoadView
+
+
+class _SuppressedConfidenceBall:
+  def render(self, *_):
+    pass
+
+
+class AugmentedRoadViewSP(AugmentedRoadView):
+  def __init__(self, **kwargs):
+    super().__init__(**kwargs)
+    self._show_confidence_ball: bool = True
+    self._real_confidence_ball = self._confidence_ball
+    self._confidence_ball = _SuppressedConfidenceBall()
+
+  def set_show_confidence_ball(self, show: bool) -> None:
+    self._show_confidence_ball = show
+
+  def _render(self, _) -> None:
+    super()._render(_)
+    if self._show_confidence_ball:
+      self._real_confidence_ball.render(self.rect)

openpilot/selfdrive/ui/sunnypilot/mici/tests/test_scroller_sp.py

@@ -0,0 +1,83 @@
+import pyray as rl
+
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.system.ui.lib.application import MouseEvent, MousePos, gui_app
+from openpilot.system.ui.lib.scroll_panel2 import ScrollState
+from openpilot.system.ui.widgets import Widget
+from openpilot.system.ui.widgets import scroller as scroller_mod
+from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
+
+
+class DummyScrollIndicator:
+  def update(self, *_) -> None:
+    pass
+
+  def render(self) -> None:
+    pass
+
+
+class DummyWidget(Widget):
+  def __init__(self, rect: rl.Rectangle):
+    super().__init__()
+    self.set_rect(rect)
+
+  def _render(self, _) -> None:
+    pass
+
+
+def _mouse_event(x: float, y: float, *, pressed: bool = False, released: bool = False,
+                 down: bool = True, t: float = 0.0) -> MouseEvent:
+  return MouseEvent(MousePos(x, y), 0, pressed, released, down, t)
+
+
+class TestScrollerSP(OpenpilotTestCase):
+  def test_vertical_snap_items_are_supported(self, monkeypatch):
+    monkeypatch.setattr(scroller_mod, "ScrollIndicator", DummyScrollIndicator)
+
+    scroller = scroller_mod._Scroller([], horizontal=False, snap_items=True, scroll_indicator=False)
+    scroller.set_rect(rl.Rectangle(0, 0, 100, 100))
+    scroller.scroll_panel.set_offset(-60)
+
+    captured_snap_target = None
+
+    def update(_, __, snap_target=None):
+      nonlocal captured_snap_target
+      captured_snap_target = snap_target
+      return scroller.scroll_panel.get_offset()
+
+    monkeypatch.setattr(scroller.scroll_panel, "update", update)
+
+    visible_items: list[Widget] = [
+      DummyWidget(rl.Rectangle(0, -60, 100, 100)),
+      DummyWidget(rl.Rectangle(0, 40, 100, 100)),
+    ]
+    scroller._get_scroll(visible_items, 200)
+
+    assert captured_snap_target == -100
+
+  def test_scroll_panel_sp_rejects_orthogonal_drags(self, monkeypatch):
+    panel = GuiScrollPanel2SP(horizontal=True)
+    bounds = rl.Rectangle(0, 0, 100, 100)
+
+    monkeypatch.setattr(gui_app, "_mouse_events", [_mouse_event(10, 10, pressed=True, t=1.0)])
+    panel.update(bounds, 200)
+    assert panel.state == ScrollState.PRESSED
+
+    monkeypatch.setattr(gui_app, "_mouse_events", [_mouse_event(23, 60, t=1.1)])
+    panel.update(bounds, 200)
+
+    assert panel.state == ScrollState.STEADY
+    assert panel.get_offset() == 0
+
+  def test_scroll_panel_sp_can_disable_out_of_bounds_handling(self, monkeypatch):
+    panel = GuiScrollPanel2SP(horizontal=False, handle_out_of_bounds=False)
+    bounds = rl.Rectangle(0, 0, 100, 100)
+    monkeypatch.setattr(gui_app, "_mouse_events", [])
+
+    panel.set_offset(20)
+    panel.update(bounds, 200)
+    assert panel.get_offset() == 0
+
+    panel.set_offset(-150)
+    panel.update(bounds, 200)
+    assert panel.get_offset() == -100

openpilot/selfdrive/ui/sunnypilot/mici/widgets/scroll_panel_sp.py

@@ -0,0 +1,33 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import pyray as rl
+from openpilot.system.ui.lib.application import MouseEvent
+from openpilot.system.ui.lib.scroll_panel2 import GuiScrollPanel2, ScrollState
+
+
+class GuiScrollPanel2SP(GuiScrollPanel2):
+  """Scroll panel behavior for nested Mici pagers."""
+
+  def __init__(self, horizontal: bool = True, handle_out_of_bounds: bool = True) -> None:
+    super().__init__(horizontal, handle_out_of_bounds=handle_out_of_bounds)
+
+  def _handle_mouse_event(self, mouse_event: MouseEvent, bounds: rl.Rectangle, bounds_size: float,
+                          content_size: float) -> None:
+    state_before_update = self._state
+    super()._handle_mouse_event(mouse_event, bounds, bounds_size, content_size)
+
+    if self._state == ScrollState.MANUAL_SCROLL and state_before_update == ScrollState.PRESSED and \
+       self._initial_click_event is not None:
+      drag_x = abs(mouse_event.pos.x - self._initial_click_event.pos.x)
+      drag_y = abs(mouse_event.pos.y - self._initial_click_event.pos.y)
+      primary_drag = drag_x if self._horizontal else drag_y
+      cross_drag = drag_y if self._horizontal else drag_x
+      if cross_drag > primary_drag:
+        self._state = ScrollState.STEADY
+        self._velocity = 0.0
+        self._velocity_buffer.clear()

openpilot/selfdrive/ui/sunnypilot/mici/widgets/scroller_sp.py

@@ -0,0 +1,16 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from openpilot.system.ui.widgets.scroller import Scroller
+from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
+
+
+class ScrollerSP(Scroller):
+  def __init__(self, **kwargs):
+    super().__init__(**kwargs)
+    inner = self._scroller
+    inner.scroll_panel = GuiScrollPanel2SP(inner._horizontal, handle_out_of_bounds=not inner._snap_items)

openpilot/selfdrive/ui/sunnypilot/model_info.py

@@ -0,0 +1,85 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
+from openpilot.sunnypilot.models.fetcher import get_cached_bundles
+from openpilot.sunnypilot.models.helpers import get_active_source, get_selected_bundle, resolve_bundle_by_ref
+from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL, DEFAULT_MODEL
+
+
+def active_source() -> str:
+  return get_active_source(chestnut=ui_state.chestnut_present,
+                           chestnut_active=ui_state.chestnut_active, chestnut_loading=ui_state.chestnut_loading,
+                           offroad=ui_state.is_offroad())
+
+
+def bundles_for_source(source: str):
+  if source == active_source():
+    return ui_state.sm["modelManagerSP"].availableBundles
+  return get_cached_bundles(ui_state.params, source)
+
+
+def default_model(source: str) -> str:
+  return DEFAULT_BIG_MODEL if source == 'chestnut' else DEFAULT_MODEL
+
+
+def default_model_name(source: str) -> str:
+  return f"{default_model(source)} (Default)"
+
+
+def big_model_state() -> str | None:
+  """'failed' | 'loading' | None, from the same state the icons render."""
+  return {ChestnutState.UNCOMPILED: 'failed',
+          ChestnutState.FAILED: 'failed',
+          ChestnutState.LOADING: 'loading'}.get(ui_state.chestnut_state)
+
+
+def carrying_model() -> tuple[str | None, str | None, str | None]:
+  """(source, internal name, display name) of what actually drives. Runner-matched:
+  when a Default big cannot carry, stock modeld runs the Default small, never the
+  small slot's pick; a custom big has no automatic fallback yet -> (None, None, None)."""
+  source = active_source()
+  if source == "chestnut":
+    bundle = get_selected_bundle(ui_state.params, "chestnut")
+    if bundle:
+      return "chestnut", bundle.internalName, bundle.displayName
+    name = default_model_name("chestnut")
+    return "chestnut", name, name
+  if ui_state.chestnut_present:
+    if get_selected_bundle(ui_state.params, "chestnut") is None:
+      name = default_model_name("qcom")
+      return "qcom", name, name
+    return None, None, None
+  bundle = get_selected_bundle(ui_state.params, "qcom")
+  if bundle:
+    return "qcom", bundle.internalName, bundle.displayName
+  name = default_model_name("qcom")
+  return "qcom", name, name
+
+
+def queued_name(current_ref) -> str | None:
+  ref = ui_state.params.get("ModelManager_DownloadRef")
+  if ref and ref != current_ref:
+    source_bundles = {source: bundles_for_source(source) for source in ("qcom", "chestnut")}
+    if resolved := resolve_bundle_by_ref(ref, source_bundles):
+      return resolved[0].internalName
+  return None
+
+
+def model_info() -> tuple[str, str, str]:
+  """returns (active source, active model name, other model name)
+
+  Names come from the params slots, never modelManagerSP.activeBundle — the
+  manager republishes a tick after a chestnut change, so the stale bundle
+  would flash the wrong model."""
+  source = active_source()
+  other = "qcom" if source == "chestnut" else "chestnut"
+  active_bundle = get_selected_bundle(ui_state.params, source)
+  other_bundle = get_selected_bundle(ui_state.params, other)
+
+  active_name = active_bundle.displayName if active_bundle else default_model_name(source)
+  other_name = other_bundle.displayName if other_bundle else default_model_name(other)
+  return source, active_name, other_name

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

@@ -8,6 +8,7 @@ from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.selfdrive.ui.ui_state import ui_state, UIStatus
 from openpilot.selfdrive.ui.sunnypilot.onroad.chevron_metrics import ChevronMetrics
 from openpilot.selfdrive.ui.sunnypilot.onroad.rainbow_path import RainbowPath
+from openpilot.selfdrive.ui.sunnypilot.ui_state import MADSState
 from openpilot.system.ui.lib.application import gui_app
 
 
@@ -19,6 +20,11 @@ class ModelRendererSP:
 
   @property
   def _lateral_active(self) -> bool:
+    sm = ui_state.sm
+    if sm.valid["selfdriveStateSP"]:
+      mads = sm["selfdriveStateSP"].mads
+      if mads.available:
+        return mads.enabled and mads.state != MADSState.paused
     return ui_state.status in (UIStatus.ENGAGED, UIStatus.LAT_ONLY)
 
   def _get_path_half_width(self) -> float:

openpilot/selfdrive/ui/sunnypilot/ui_state.py

@@ -10,6 +10,7 @@ from openpilot.cereal import messaging, log, custom
 from opendbc.car.structs import car
 from openpilot.common.params import Params
 from openpilot.selfdrive.ui.sunnypilot.layouts.settings.display import OnroadBrightness
+from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS, get_active_source
 from openpilot.sunnypilot.sunnylink.sunnylink_state import SunnylinkState
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.sunnypilot.widgets.screen_saver import ScreenSaverSP
@@ -43,6 +44,7 @@ class UIStateSP:
     self.screensaver_enabled: bool = False
 
     self.active_bundle = None
+    self.model_runner_tinygrad: bool = False
     self.blindspot: bool = False
     self.chevron_metrics = None
     self.custom_interactive_timeout: int = 0
@@ -150,7 +152,13 @@ class UIStateSP:
       self.has_icbm = self.CP_SP.intelligentCruiseButtonManagementAvailable and self.params.get_bool("IntelligentCruiseButtonManagement")
 
     self._enforce_constraints()
-    self.active_bundle = self.params.get("ModelManager_ActiveBundle")
+    source = get_active_source(chestnut=self.chestnut_present, chestnut_active=self.chestnut_active,
+                               chestnut_loading=self.chestnut_loading, offroad=self.is_offroad())
+    self.active_bundle = self.params.get(ACTIVE_BUNDLE_KEYS[source])
+    self.model_runner_tinygrad = self.active_bundle is not None and self.active_bundle.get("runner") == "tinygrad"
+    # stock only counts the default big model's compiled pkl. a downloaded big bundle runs on the
+    # chestnut just the same, so ChestnutState has to see it as available too.
+    self.chestnut_compiled = self.chestnut_compiled or self.model_runner_tinygrad
     self.blindspot = self.params.get_bool("BlindSpot")
     self.chevron_metrics = self.params.get("ChevronInfo")
     self.custom_interactive_timeout = self.params.get("InteractivityTimeout", return_default=True)

openpilot/selfdrive/ui/ui.py

@@ -10,6 +10,9 @@ from openpilot.selfdrive.ui.layouts.main import MainLayout
 from openpilot.selfdrive.ui.mici.layouts.main import MiciMainLayout
 from openpilot.selfdrive.ui.ui_state import ui_state
 
+if gui_app.sunnypilot_ui():
+  from openpilot.selfdrive.ui.sunnypilot.mici.layouts.main import MiciMainLayoutSP as MiciMainLayout
+
 BIG_UI = gui_app.big_ui()
 
 

openpilot/selfdrive/ui/ui_state.py

@@ -12,7 +12,8 @@ from openpilot.common.swaglog import cloudlog
 from openpilot.selfdrive.ui.lib.prime_state import PrimeState
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.common.hardware import HARDWARE, PC
-from openpilot.selfdrive.modeld.helpers import usbgpu_compiled
+from openpilot.common.hardware.usb import TYPEC_CC_ORIENTATION_PATH, get_usb_state, is_chestnut_usb_id, read_int
+from openpilot.selfdrive.modeld.helpers import chestnut_compiled
 
 from openpilot.selfdrive.ui.sunnypilot.ui_state import UIStateSP, DeviceSP
 
@@ -28,6 +29,15 @@ class UIStatus(Enum):
   LONG_ONLY = "long_only"
 
 
+class ChestnutState(Enum):
+  DISCONNECTED = "disconnected"
+  UNCOMPILED = "uncompiled"
+  READY = "ready"
+  LOADING = "loading"
+  ACTIVE = "active"
+  FAILED = "failed"
+
+
 class UIState(UIStateSP):
   _instance: 'UIState | None' = None
 
@@ -82,10 +92,15 @@ class UIState(UIStateSP):
     self.always_on_dm: bool = self.params.get_bool("AlwaysOnDM")
     self.experimental_mode: bool = self.params.get_bool("ExperimentalMode")
     self.experimental_mode_confirmed: bool = self.params.get_bool("ExperimentalModeConfirmed")
-    self.usbgpu: bool = False
-    self.usbgpu_compiled: bool = usbgpu_compiled()
-    self.usbgpu_active: bool | None = self.params.get("UsbGpuActive")
-    self.usbgpu_loading: bool = self.params.get_bool("UsbGpuLoading")
+    self.chestnut_present: bool = False
+    self.chestnut_compiled: bool = chestnut_compiled()
+    self.chestnut_active: bool | None = None
+    self.chestnut_loading: bool = False
+    self.usb_connected: bool = False
+    self.usb_connected_ts: float | None = None
+    self.usb_disconnected_ts: float | None = None
+    self.usb_unknown: bool = False
+    self.chestnut_state = ChestnutState.DISCONNECTED
     self.started: bool = False
     self.ignition: bool = False
     self.recording_audio: bool = False
@@ -131,6 +146,7 @@ class UIState(UIStateSP):
     self.sm.update(0)
     self._update_state()
     self._update_status()
+    self._update_chestnut_state()
     device.update()
     UIStateSP.update(self)
 
@@ -194,12 +210,35 @@ class UIState(UIStateSP):
         self.status = UIStatus.DISENGAGED
         self.started_frame = self.sm.frame
         self.started_time = time.monotonic()
+        self.chestnut_present = self.sm["deviceState"].chestnutPresent
 
       for callback in self._offroad_transition_callbacks:
         callback()
 
       self._started_prev = self.started
 
+  def _update_chestnut_state(self) -> None:
+    detected = self.sm["deviceState"].chestnutPresent
+    if not self.started:
+      self.chestnut_present = detected
+      self.chestnut_state = (ChestnutState.READY if detected and self.chestnut_compiled else
+                             ChestnutState.UNCOMPILED if detected else ChestnutState.DISCONNECTED)
+      return
+
+    model_seen = self.sm.recv_frame["modelV2"] > self.started_frame
+    if not self.chestnut_present:
+      self.chestnut_state = ChestnutState.DISCONNECTED
+    elif not self.chestnut_compiled:
+      self.chestnut_state = ChestnutState.UNCOMPILED
+    elif self.chestnut_state == ChestnutState.FAILED or not detected or (model_seen and (not self.sm.alive["modelV2"] or not self.sm["modelV2"].big)):
+      self.chestnut_state = ChestnutState.FAILED
+    elif self.chestnut_loading or not model_seen:
+      self.chestnut_state = ChestnutState.LOADING
+    elif self.chestnut_active is False:
+      self.chestnut_state = ChestnutState.FAILED
+    else:
+      self.chestnut_state = ChestnutState.ACTIVE
+
   def update_params(self) -> None:
     # For slower operations
     # Update longitudinal control state
@@ -216,12 +255,27 @@ class UIState(UIStateSP):
     self.always_on_dm = self.params.get_bool("AlwaysOnDM")
     self.experimental_mode = self.params.get_bool("ExperimentalMode")
     self.experimental_mode_confirmed = self.params.get_bool("ExperimentalModeConfirmed")
-    # keep usbgpu UI active until offroad transition when gpu disappears
-    self.usbgpu = self.sm["deviceState"].chestnutPresent or (self.usbgpu and self.started)
-    if not self.usbgpu_compiled:
-      self.usbgpu_compiled = usbgpu_compiled()
-    self.usbgpu_active = self.params.get("UsbGpuActive")
-    self.usbgpu_loading = self.params.get_bool("UsbGpuLoading")
+    if not self.chestnut_compiled:
+      self.chestnut_compiled = chestnut_compiled()
+    self.chestnut_active = self.params.get("ChestnutActive")
+    self.chestnut_loading = self.params.get_bool("ChestnutLoading")
+    now = time.monotonic()
+    if read_int(TYPEC_CC_ORIENTATION_PATH) != 0:
+      self.usb_disconnected_ts = None
+      if not self.usb_connected:
+        self.usb_connected = True
+        self.usb_connected_ts = now
+        self.usb_unknown = False
+      elif self.usb_connected_ts is not None and now - self.usb_connected_ts > 10.:
+        self.usb_unknown = not any(is_chestnut_usb_id(d["vendorId"], d["productId"], True) for d in get_usb_state())
+        self.usb_connected_ts = None
+    elif self.usb_connected:
+      if self.usb_disconnected_ts is None:
+        self.usb_disconnected_ts = now
+      elif now - self.usb_disconnected_ts > PARAM_UPDATE_TIME:
+        self.usb_connected = False
+        self.usb_connected_ts = None
+        self.usb_unknown = False
 
     UIStateSP.update_params(self)
 

openpilot/sunnypilot/mapd/mapd_manager.py

@@ -55,6 +55,19 @@ def cleanup_old_osm_data(files_to_remove: list[str]) -> None:
       shutil.rmtree(file, ignore_errors=False)
 
 
+def clear_downloaded_maps() -> None:
+  """Deletes downloaded OSM map data and resets params."""
+  path = f"{Paths.mapd_root()}/offline"
+  if os.path.exists(path):
+    shutil.rmtree(path, ignore_errors=True)
+
+  for param in ("OsmDownloadedDate", "OsmLocal", "OsmLocationName", "OsmLocationTitle",
+                "OsmStateName", "OsmStateTitle"):
+    params.remove(param)
+
+  cloudlog.info("mapd: downloaded maps cleared")
+
+
 def request_refresh_osm_location_data(nations: list[str], states: list[str] | None = None) -> None:
   params.put("OsmDownloadedDate", str(datetime.now().timestamp()), block=True)
   params.put_bool("OsmDbUpdatesCheck", False, block=True)
@@ -131,6 +144,10 @@ def main_thread():
     show_alert = bool(get_files_for_cleanup() and params.get_bool("OsmLocal"))
     set_offroad_alert("Offroad_OSMUpdateRequired", show_alert, "This alert will be cleared when new maps are downloaded.")
 
+    if params.get("Mapd_ClearCache"):
+      clear_downloaded_maps()
+      params.remove("Mapd_ClearCache")
+
     update_osm_db()
     live_map_sp.tick()
     rk.keep_time()

openpilot/sunnypilot/modeld_v2/__init__.py

@@ -1,5 +0,0 @@
-from pathlib import Path
-
-MODEL_PATH = Path(__file__).parent / 'models/supercombo.onnx'
-MODEL_PKL_PATH = Path(__file__).parent / 'models/supercombo_tinygrad.pkl'
-METADATA_PATH = Path(__file__).parent / 'models/supercombo_metadata.pkl'

openpilot/sunnypilot/modeld_v2/compile_modeld.py

@@ -7,6 +7,7 @@ See the LICENSE.md file in the root directory for more details.
 """
 
 import argparse
+import math
 import os
 import tempfile
 import time
@@ -31,7 +32,7 @@ def _patch_tinygrad_fetch_fw():
   helpers.fetch_fw = fetch_fw
 _patch_tinygrad_fetch_fw()
 
-from openpilot.selfdrive.modeld.compile_modeld import NV12Frame, make_frame_prepare, sample_desire, sample_skip, shift_and_sample
+import openpilot.selfdrive.modeld.compile_modeld as stock
 from tinygrad import dtypes
 from tinygrad.device import Device
 from tinygrad.engine.jit import TinyJit
@@ -40,8 +41,7 @@ from tinygrad.tensor import Tensor
 MODEL_TYPES = ('vision_policy', 'supercombo', 'vision_multi_policy')
 WARP_INPUTS = ['tfm', 'big_tfm']
 POLICY_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']
-WARP_DEV = os.getenv('WARP_DEV')
-
+nv12_copy_size = stock.nv12_copy_size
 
 def _detect_desire_key(shapes: dict) -> str | None:
   return next((key for key in shapes if key.startswith('desire')), None)
@@ -66,14 +66,15 @@ def get_policy_npy_shapes(input_shapes: dict, is_supercombo: bool = False) -> tu
   if desire_key:
     shapes['desire'] = (input_shapes[desire_key][2],)
 
-  if is_supercombo and 'features_buffer' in input_shapes:
-    fb = input_shapes['features_buffer']
-    shapes['prev_feat'] = (fb[0], fb[2])
-
   for key, shape in input_shapes.items():
     if key not in (desire_key, 'features_buffer') and 'img' not in key:
       shapes[key] = tuple(shape)
 
+  if is_supercombo and 'features_buffer' in input_shapes:
+    fb = input_shapes['features_buffer']
+    feat_dim = math.prod(fb[2:])
+    shapes['prev_feat'] = (fb[0], feat_dim)
+
   sizes = [int(np.prod(size)) for size in shapes.values()]
   return shapes, sizes
 
@@ -117,8 +118,9 @@ def generate_queues_and_npy(input_shapes: dict, frame_skip: int, device: str = D
   }
 
   if features_buffer:
+    feat_dim = math.prod(features_buffer[2:])
     feat_q_len = frame_skip * features_buffer[1] if is_supercombo else frame_skip * (features_buffer[1] - 1) + 1
-    queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], features_buffer[2]),
+    queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], feat_dim),
                        dtype=np.float32), device=device).contiguous().realize()
 
   queues.update({key: Tensor(value, device='NPY').realize() for key, value in npy_arrays.items() if key in ('tfm', 'big_tfm')})
@@ -136,7 +138,7 @@ def make_supercombo_input_queues(input_shapes: dict, frame_skip: int,
   return generate_queues_and_npy(input_shapes, frame_skip, device, is_supercombo=True)
 
 
-def make_random_images(keys, shape, device):
+def make_random_images(keys, shape, device, rng=None):
   return {k: Tensor.randint(shape, low=0, high=256, dtype=dtypes.uint8, device=device).realize() for k in keys}
 
 
@@ -149,24 +151,9 @@ def make_warp_queues(device=Device.DEFAULT):
   return queues, npy
 
 
-def make_warp(nv12: NV12Frame, model_w: int, model_h: int):
-  frame_prepare = make_frame_prepare(nv12, model_w, model_h)
-  WARP_DEV = os.getenv('WARP_DEV', Device.DEFAULT)
-
-  def warp(tfm, big_tfm, frame, big_frame):
-    tfm = tfm.to(WARP_DEV)
-    big_tfm = big_tfm.to(WARP_DEV)
-    Tensor.realize(tfm, big_tfm)
-
-    warped_frame = frame_prepare(frame, tfm).unsqueeze(0)
-    warped_big_frame = frame_prepare(big_frame, big_tfm).unsqueeze(0)
-    return Tensor.cat(warped_frame, warped_big_frame)
-  return warp
-
-
 def make_run_policy(vision_runner, policy_runners: list, features_slice: slice, frame_skip: int, input_shapes: dict):
-  sample_skip_fn = partial(sample_skip, frame_skip=frame_skip)
-  sample_desire_fn = partial(sample_desire, frame_skip=frame_skip)
+  sample_skip_fn = partial(stock.sample_skip, frame_skip=frame_skip)
+  sample_desire_fn = partial(stock.sample_desire, frame_skip=frame_skip)
 
   desire_key = _detect_desire_key(input_shapes)
   road_key, wide_key = _detect_vision_keys(input_shapes)
@@ -183,14 +170,14 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
     warped_dev = warped.to(Device.DEFAULT)
     Tensor.realize(packed_npy_inputs_dev, warped_dev)
 
-    img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn).realize()
-    big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn).realize()
+    img = stock.shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn)
+    big_img = stock.shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn)
 
     unpacked_tensors = [tensor.reshape(shape) for tensor, shape in zip(packed_npy_inputs_dev.split(npy_sizes), npy_shapes.values(), strict=True)]
     unpacked_dict = dict(zip(npy_shapes.keys(), unpacked_tensors, strict=True))
 
     desire_dev = unpacked_dict['desire']
-    desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn).realize()
+    desire_buf = stock.shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn)
 
     inputs = {desire_key: desire_buf}
     for key, tensor_val in unpacked_dict.items():
@@ -199,44 +186,45 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
 
     if 'prev_feat' in unpacked_dict:
       prev_feat_dev = unpacked_dict['prev_feat']
-      inputs['features_buffer'] = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).realize()
+      inputs['features_buffer'] = stock.shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).reshape(input_shapes['features_buffer'])
 
     if vision_runner:
       vision_out_cast = next(iter(vision_runner({road_key: img, wide_key: big_img}).values())).cast('float32').realize()
       if 'features_buffer' not in inputs:
         new_feat = vision_out_cast[:, features_slice].reshape(1, -1).unsqueeze(0)
-        inputs['features_buffer'] = shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
+        inputs['features_buffer'] = stock.shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
       policy_outs = [next(iter(pol_runner(inputs).values())).cast('float32').realize() for pol_runner in policy_runners]
       return (vision_out_cast, *policy_outs) if len(policy_outs) > 1 else (vision_out_cast, policy_outs[0])
 
     inputs.update({road_key: img, wide_key: big_img})
     if 'features_buffer' not in inputs:
-      inputs['features_buffer'] = sample_skip_fn(feat_q)
+      inputs['features_buffer'] = sample_skip_fn(feat_q).reshape(input_shapes['features_buffer'])
 
     policy_out = next(iter(policy_runners[0](inputs).values())).cast('float32').realize()
     if 'features_buffer' not in inputs and features_slice is not None:
       new_feat = policy_out[:, features_slice].reshape(1, -1).unsqueeze(0)
-      shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
+      stock.shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
     return policy_out
 
   return run_policy
 
 
-def compile_jit(jit, make_random_inputs, input_keys, make_queues):
+def compile_jit(jit, input_keys, make_queues, make_random_inputs=None, benchmark_runs: int = 1):
   SEED = 42
-  def random_inputs_run(fn, seed, test_val=None, test_buffers=None, expect_match=True):
-    input_queues, npy = make_queues(Device.DEFAULT)
+  def random_inputs_run(fn, seed, n_runs, test_val=None, test_buffers=None, expect_match=True):
+    queues_res = make_queues(Device.DEFAULT)
+    input_queues, npy = queues_res[0], queues_res[1]
+    frame_views = queues_res[2] if len(queues_res) > 2 else {}
     rng = np.random.default_rng(seed)
     Tensor.manual_seed(seed)
 
-    testing = test_val is not None or test_buffers is not None
-    n_runs = 1 if testing else 3
-
     for i in range(n_runs):
       for v in npy.values():
         v[:] = rng.standard_normal(v.shape).astype(v.dtype)
+      for v in frame_views.values():
+        v[:] = rng.integers(0, 256, size=v.shape, dtype=np.uint8)
       Device.default.synchronize()
-      random_inputs = make_random_inputs()
+      random_inputs = make_random_inputs(rng=rng) if make_random_inputs is not None else {}
       st = time.perf_counter()
       outs = fn(**{k: input_queues[k] for k in input_keys if k in input_queues}, **random_inputs)
       mt = time.perf_counter()
@@ -257,14 +245,15 @@ def compile_jit(jit, make_random_inputs, input_keys, make_queues):
     return val, buffers
 
   print('capture + replay')
-  test_val, test_buffers = random_inputs_run(jit, SEED)
-  print('pickle round trip')
+  test_val, test_buffers = random_inputs_run(jit, SEED, 3)
+  print(f'pickle round trip ({benchmark_runs} runs per seed)')
   with tempfile.TemporaryFile(dir=".") as f:
     dump_oob(jit, f)
     f.seek(0)
-    deserialized_jit = load_oob(f)
-  random_inputs_run(deserialized_jit, SEED, test_val=test_val, test_buffers=test_buffers)
-  return deserialized_jit
+    loaded_jit = load_oob(f)
+  random_inputs_run(loaded_jit, SEED, benchmark_runs, test_val, test_buffers, expect_match=True)
+  random_inputs_run(loaded_jit, SEED+1, benchmark_runs, test_val, test_buffers, expect_match=False)
+  return jit
 
 
 def _parse_size(size_str: str) -> tuple[int, int]:
@@ -295,7 +284,7 @@ def _load_policy_runners(args: argparse.Namespace) -> tuple[list, list]:
 
 
 if __name__ == "__main__":
-  if 'USB' in os.getenv('DEV', '') or os.getenv('USBGPU'):
+  if 'USB' in os.getenv('DEV', '') or os.getenv('CHESTNUT'):
     from openpilot.system.hardware.chestnut.flash import link_up
     for _ in range(10):
       if link_up():
@@ -314,6 +303,7 @@ if __name__ == "__main__":
   parser.add_argument('--model-size', type=_parse_size, required=True, help='model input WxH')
   parser.add_argument('--camera-resolutions', type=_parse_size, nargs='+', required=True)
   parser.add_argument('--frame-skip', type=int, default=None, help='frame skip value (auto-derived if not provided)')
+  parser.add_argument('--benchmark-runs', type=int, default=1, help='benchmark runs')
   parser.add_argument('--output', required=True)
 
   parser.add_argument('--vision-onnx', help='vision ONNX (for split models)')
@@ -332,48 +322,64 @@ if __name__ == "__main__":
   args.on_policy_onnx = read_file_chunked_to_disk(args.on_policy_onnx)
   args.supercombo_onnx = read_file_chunked_to_disk(args.supercombo_onnx)
 
-  vision_runner = OnnxRunner(args.vision_onnx) if args.vision_onnx else None
-
-  if args.model_type == 'vision_policy':
-    assert vision_runner and args.policy_onnx
-    policy_runners = [OnnxRunner(args.policy_onnx)]
-    output_data['metadata'] = {'vision': make_metadata_dict(args.vision_onnx), 'policy': make_metadata_dict(args.policy_onnx)}
-  elif args.model_type == 'supercombo':
+  if args.model_type == 'supercombo':
     assert args.supercombo_onnx
-    policy_runners = [OnnxRunner(args.supercombo_onnx)]
-    output_data['metadata'] = {'model': make_metadata_dict(args.supercombo_onnx)}
-  elif args.model_type == 'vision_multi_policy':
-    assert vision_runner
-    policy_runners, policy_names = _load_policy_runners(args)
-    output_data['metadata'] = {'vision': make_metadata_dict(args.vision_onnx)}
-    for name in policy_names:
-      runner_arg = getattr(args, f"{name}_onnx")
-      output_data['metadata'][name] = make_metadata_dict(runner_arg)
+    model_metadata = make_metadata_dict(args.supercombo_onnx)
+    output_data['metadata'] = {'model': model_metadata, **model_metadata}
+    output_data['input_devices'] = {'model': Device.DEFAULT}
+    output_data['run_model'] = {}
+    derived_frame_skip = args.frame_skip or derive_frame_skip({}, model_metadata['input_shapes'])
+    model_runner = OnnxRunner(args.supercombo_onnx)
+    run_policy = stock.make_run_policy(model_runner, model_metadata, derived_frame_skip)
+    for cam_w, cam_h in args.camera_resolutions:
+      print(f"Compiling unified run_model JIT for {cam_w}x{cam_h}...")
+      nv12 = stock.NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
+      frame_copy_size = stock.nv12_copy_size(nv12.stride, nv12.y_height, nv12.uv_height)
+      make_model_queues = partial(stock.make_input_queues, model_metadata['input_shapes'], derived_frame_skip,
+                                  frame_copy_size=frame_copy_size)
+      warp = stock.make_warp(nv12, model_w, model_h)
+      run_model_jit = TinyJit(stock.make_run_model(warp, run_policy, model_metadata, frame_copy_size), prune=True)
+      output_data['run_model'][(cam_w, cam_h)] = compile_jit(run_model_jit, stock.MODELD_INPUTS, make_model_queues, benchmark_runs=args.benchmark_runs)
+  else:
+    vision_runner = OnnxRunner(args.vision_onnx) if args.vision_onnx else None
+    if args.model_type == 'vision_policy':
+      assert vision_runner and args.policy_onnx
+      policy_runners = [OnnxRunner(args.policy_onnx)]
+      output_data['metadata'] = {'vision': make_metadata_dict(args.vision_onnx), 'policy': make_metadata_dict(args.policy_onnx)}
+    elif args.model_type == 'vision_multi_policy':
+      assert vision_runner
+      policy_runners, policy_names = _load_policy_runners(args)
+      output_data['metadata'] = {'vision': make_metadata_dict(args.vision_onnx)}
+      for name in policy_names:
+        runner_arg = getattr(args, f"{name}_onnx")
+        output_data['metadata'][name] = make_metadata_dict(runner_arg)
 
-  policy_keys = [key for key in output_data['metadata'].keys() if key != 'vision']
-  first_policy_meta = output_data['metadata'][policy_keys[0]] if policy_keys else {}
-  vision_meta = output_data['metadata'].get('vision', {})
+    policy_keys = [key for key in output_data['metadata'].keys() if key != 'vision']
+    first_policy_meta = output_data['metadata'][policy_keys[0]] if policy_keys else {}
+    vision_meta = output_data['metadata'].get('vision', {})
 
-  derived_frame_skip = args.frame_skip or derive_frame_skip(vision_meta.get('input_shapes', {}), first_policy_meta.get('input_shapes', {}))
-  all_shapes = {key: value for meta in output_data['metadata'].values() for key, value in meta['input_shapes'].items()}
-  feat_meta = output_data['metadata'].get('vision') or output_data['metadata'].get('model') or output_data['metadata'].get('policy')
-  assert feat_meta is not None
-  features_slice = feat_meta['output_slices']['hidden_state']
-  is_supercombo = vision_runner is None
+    derived_frame_skip = args.frame_skip or derive_frame_skip(vision_meta.get('input_shapes', {}), first_policy_meta.get('input_shapes', {}))
+    all_shapes = {key: value for meta in output_data['metadata'].values() for key, value in meta['input_shapes'].items()}
+    feat_meta = output_data['metadata'].get('vision') or output_data['metadata'].get('policy')
+    assert feat_meta is not None
+    features_slice = feat_meta['output_slices']['hidden_state']
 
-  print(f"Compiling run_policy JIT (model_size={model_w}x{model_h}, frame_skip={derived_frame_skip})...")
-  run_policy_func = make_run_policy(vision_runner, policy_runners, features_slice, derived_frame_skip, all_shapes)
-  run_policy_jit = TinyJit(run_policy_func, prune=True)
-  make_policy_queues = partial(generate_queues_and_npy, all_shapes, derived_frame_skip, is_supercombo=is_supercombo)
-  make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, model_h // 2, model_w // 2), device=WARP_DEV)
-  output_data['run_policy'] = compile_jit(run_policy_jit, make_random_model_inputs, POLICY_INPUTS, make_policy_queues)
+    print(f"Compiling run_policy JIT (model_size={model_w}x{model_h}, frame_skip={derived_frame_skip})...")
+    run_policy_func = make_run_policy(vision_runner, policy_runners, features_slice, derived_frame_skip, all_shapes)
+    run_policy_jit = TinyJit(run_policy_func, prune=True)
+    make_policy_queues = partial(generate_queues_and_npy, all_shapes, derived_frame_skip, is_supercombo=False)
+    make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, model_h // 2, model_w // 2), device=Device.DEFAULT)
+    output_data['run_policy'] = compile_jit(run_policy_jit, POLICY_INPUTS, make_policy_queues, make_random_inputs=make_random_model_inputs)
 
-  for cam_w, cam_h in args.camera_resolutions:
-    print(f"Compiling warp JIT for {cam_w}x{cam_h}...")
-    nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-    make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=nv12.size, device=WARP_DEV)
-    warp = TinyJit(make_warp(nv12, model_w, model_h), prune=True)
-    output_data[(cam_w, cam_h)] = compile_jit(warp, make_random_warp_inputs, WARP_INPUTS, make_warp_queues)
+    for cam_w, cam_h in args.camera_resolutions:
+      print(f"Compiling warp JIT for {cam_w}x{cam_h}...")
+      nv12 = stock.NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
+      frame_copy_size = stock.nv12_copy_size(nv12.stride, nv12.y_height, nv12.uv_height)
+      make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=frame_copy_size, device=Device.DEFAULT)
+      warp = TinyJit(stock.make_warp(nv12, model_w, model_h), prune=True)
+      output_data[(cam_w, cam_h)] = compile_jit(warp, WARP_INPUTS, make_warp_queues, make_random_inputs=make_random_warp_inputs)
+
+    output_data['metadata']['warp_dev'] = Device.DEFAULT
 
   with open(args.output, "wb") as file:
     dump_oob(output_data, file)

openpilot/sunnypilot/modeld_v2/constants.py

@@ -14,6 +14,8 @@ class ModelConstants:
 
   # model inputs constants
   MODEL_FREQ = 20
+  MODEL_RUN_FREQ = 20
+  MODEL_CONTEXT_FREQ = 5
   FEATURE_LEN = 512
   FULL_HISTORY_BUFFER_LEN = 99
   DESIRE_LEN = 8
@@ -35,6 +37,7 @@ class ModelConstants:
   LANE_LINES_WIDTH = 2
   ROAD_EDGES_WIDTH = 2
   PLAN_WIDTH = 15
+  ACTION_WIDTH = 2
   DESIRE_PRED_WIDTH = 8
   LAT_PLANNER_SOLUTION_WIDTH = 4
   DESIRED_CURV_WIDTH = 1

openpilot/sunnypilot/modeld_v2/meta_helper.py

@@ -1,26 +1,9 @@
 from openpilot.sunnypilot.modeld_v2.constants import Meta
-from openpilot.cereal import custom
 from openpilot.sunnypilot.modeld_v2.meta_20hz import Meta20hz
 from openpilot.sunnypilot.models.helpers import get_active_bundle
 
-ModelBundle = custom.ModelManagerSP.ModelBundle
-
 
 def load_meta_constants():
-  """
-  Determines and loads the appropriate meta model class based on the metadata provided. The function checks
-  specific keys and conditions within the provided metadata dictionary to identify the corresponding meta
-  model class to return.
-
-  :param model_metadata: Dictionary containing metadata about the model. It includes
-      details such as input shapes, output slices, and other configurations for identifying
-      metadata-dependent meta model classes.
-  :type model_metadata: dict
-  :return: The appropriate meta model class (Meta, MetaSimPose, or MetaTombRaider)
-      based on the conditions and metadata provided.
-  :rtype: type
-  """
   if (bundle := get_active_bundle()) and bundle.is20hz:
     return Meta20hz
-
-  return Meta  # Default
+  return Meta

openpilot/sunnypilot/modeld_v2/modeld.py

@@ -6,24 +6,25 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
 
+from collections.abc import Callable
 import os
 os.environ['GMMU'] = '0'
-from openpilot.common.hardware import COMMA_HARDWARE
-from openpilot.selfdrive.modeld.helpers import usbgpu_present, load_oob
-import time
 import numpy as np
+import threading
+import time
+from setproctitle import setproctitle
+from tinygrad.tensor import Tensor
+
 import openpilot.cereal.messaging as messaging
+from openpilot.common.hardware import COMMA_HARDWARE
+from openpilot.selfdrive.modeld.helpers import chestnut_present, load_oob
 from openpilot.cereal import log
 from opendbc.car.structs import car
 from openpilot.cereal.services import SERVICE_LIST
-from setproctitle import setproctitle
 from openpilot.cereal.messaging import PubMaster, SubMaster
 from openpilot.cereal.visionipc import VisionStreamType
 from msgq.visionipc import VisionIpcClient, VisionBuf
 from opendbc.car.car_helpers import get_demo_car_params
-
-from tinygrad.tensor import Tensor
-
 from openpilot.common.file_chunker import open_file_chunked
 from openpilot.common.swaglog import cloudlog
 from openpilot.common.params import Params
@@ -37,18 +38,25 @@ from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
 from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan, smooth_value
 from openpilot.selfdrive.modeld.modeld import ChestnutState
 
+from openpilot.selfdrive.modeld.compile_modeld import (
+  MODELD_INPUTS,
+  make_input_queues as make_stock_input_queues,
+)
 from openpilot.sunnypilot.modeld_v2.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState, get_curvature_from_output
-from openpilot.sunnypilot.modeld_v2.constants import Plan
+from openpilot.sunnypilot.modeld_v2.parse_model_outputs import Parser
+from openpilot.sunnypilot.modeld_v2.constants import ModelConstants, Plan
 from openpilot.sunnypilot.modeld_v2.meta_helper import load_meta_constants
 from openpilot.sunnypilot.modeld_v2.camera_offset_helper import CameraOffsetHelper
-from openpilot.sunnypilot.modeld_v2.compile_modeld import derive_frame_skip, make_split_input_queues, make_supercombo_input_queues, WARP_INPUTS, POLICY_INPUTS
-
+from openpilot.sunnypilot.modeld_v2.compile_modeld import (derive_frame_skip, make_split_input_queues,
+                                                           make_supercombo_input_queues, nv12_copy_size,
+                                                           WARP_INPUTS, POLICY_INPUTS)
 from openpilot.sunnypilot.livedelay.helpers import get_lat_delay
 from openpilot.sunnypilot.modeld_v2.modeld_base import ModelStateBase
 from openpilot.sunnypilot.models.helpers import get_active_bundle
 from openpilot.sunnypilot.selfdrive.controls.lib.relc import RoadEdgeLaneChangeController
 
 PROCESS_NAME = "openpilot.selfdrive.modeld.modeld_tinygrad"
+BIG_MODEL_TIMEOUT = 60
 
 
 def _pkl_exists(path):
@@ -68,6 +76,7 @@ def _find_driving_pkl(bundle):
   pkl_path = os.path.join(model_root, pkl_name)
   if _pkl_exists(pkl_path):
     return pkl_path
+  return None
 
 
 class FrameMeta:
@@ -84,14 +93,14 @@ class ModelState(ModelStateBase):
   inputs: dict[str, np.ndarray]
   prev_desire: np.ndarray
 
-  def __init__(self, cam_w: int, cam_h: int, usbgpu: bool = False):
+  def __init__(self, cam_w: int, cam_h: int, chestnut: bool = False):
     ModelStateBase.__init__(self)
 
     env_pkl = os.environ.get('COMBINED_MODEL_PKL')
     if env_pkl and os.path.exists(env_pkl):
       model_bundle = None
     else:
-      model_bundle = get_active_bundle()
+      model_bundle = get_active_bundle(chestnut=chestnut)
     self.generation = model_bundle.generation if model_bundle is not None else None
     overrides = {override.key: override.value for override in model_bundle.overrides} if model_bundle else {}
 
@@ -99,46 +108,50 @@ class ModelState(ModelStateBase):
     self.LONG_SMOOTH_SECONDS = float(overrides.get('long', ".0"))
     self.MIN_LAT_CONTROL_SPEED = 0.3
     self.PLANPLUS_CONTROL: float = 1.0
-    self.usbgpu = usbgpu
+    self.chestnut = chestnut
 
     pkl_path = _find_driving_pkl(model_bundle)
-    assert pkl_path is not None, "No driving pkl found — all models must be compiled with compile_modeld.py"
+    assert pkl_path is not None, f"No driving pkl found for {'chestnut' if chestnut else 'small model'} — all models must be compiled with compile_modeld.py"
     self._init_combined(pkl_path, cam_w, cam_h, model_bundle)
 
   def _init_combined(self, pkl_path, cam_w, cam_h, bundle):
     cloudlog.warning(f"loading combined pkl: {pkl_path}")
     jits = load_oob(open_file_chunked(pkl_path))
 
-    self.WARP_DEV = 'QCOM' if COMMA_HARDWARE else 'CPU'
-    self.DEV = 'AMD' if self.usbgpu else self.WARP_DEV
-    self.QUEUE_DEV = self.DEV
     metadata = jits['metadata']
+    self.WARP_DEV = metadata.get('warp_dev', 'QCOM') if COMMA_HARDWARE else 'CPU'
+    self.DEV = ('AMD' if self.chestnut else 'QCOM') if COMMA_HARDWARE else 'CPU'
+    self.QUEUE_DEV = self.DEV
+    self.is_run_model = 'run_model' in jits
 
-    self.is_legacy_model = 'run_policy' not in jits  # remove after next recompile
-    if self.is_legacy_model:
-      self.warp = jits[(cam_w, cam_h)]['warp_enqueue']
-      self.run_policy = jits[(cam_w, cam_h)]['run_policy']
-    else:
-      self.run_policy = jits['run_policy']
-      self.warp = jits[(cam_w, cam_h)]
+    nv12_info = get_nv12_info(cam_w, cam_h)
+    self.frame_copy_size = nv12_copy_size(*nv12_info[:3])
+    self.full_frames: dict = {}
+    self._blob_cache: dict = {}
+    self.frame_buffers: dict = {}
 
-    if 'model' in metadata:
-      model_metadata = metadata['model']
+    if self.is_run_model or 'model' in metadata:
+      model_metadata = metadata.get('model', metadata)
+      self.input_shapes = model_metadata['input_shapes']
       self.vision_output_slices = model_metadata['output_slices']
       self.policy_output_slices = {}
       self._policy_slices_list = []
       self._combined_model_type = 'supercombo'
-      self._vision_input_names = [key for key in model_metadata['input_shapes'] if 'img' in key]
-      frame_skip = derive_frame_skip({}, model_metadata['input_shapes'])
-      self.input_queues, self.numpy_inputs = make_supercombo_input_queues(model_metadata['input_shapes'],
-                                                                          frame_skip, device=self.QUEUE_DEV)
-    else:
-      vision_metadata = metadata['vision']
-      policy_keys = [k for k in metadata if k != 'vision']
-      if policy_keys == ['policy']:
-        self._combined_model_type = 'split'
+      self._vision_input_names = [key for key in self.input_shapes if 'img' in key]
+      self.frame_skip = derive_frame_skip({}, self.input_shapes)
+      if self.is_run_model:
+        self.input_queues, self.numpy_inputs, self.frame_buffers = make_stock_input_queues(
+          self.input_shapes, self.frame_skip, device=self.DEV, frame_copy_size=self.frame_copy_size)
+        self.frame_views, self.npy = self.frame_buffers, self.numpy_inputs
+        self.run_model, self.run_policy, self.warp = jits['run_model'][(cam_w, cam_h)], None, None
       else:
-        self._combined_model_type = 'multi_policy'
+        self.input_queues, self.numpy_inputs = make_supercombo_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
+        self.run_model, self.run_policy, self.warp = None, jits['run_policy'], jits[(cam_w, cam_h)]
+    else:
+      self.run_model, self.run_policy, self.warp = None, jits['run_policy'], jits[(cam_w, cam_h)]
+      vision_metadata = metadata['vision']
+      policy_keys = [k for k in metadata if k not in ('vision', 'warp_dev')]
+      self._combined_model_type = 'split' if policy_keys == ['policy'] else 'multi_policy'
       self.vision_output_slices = vision_metadata['output_slices']
       self._policy_keys = policy_keys
       self._policy_slices_list = [metadata[k]['output_slices'] for k in policy_keys]
@@ -154,57 +167,39 @@ class ModelState(ModelStateBase):
     self._desire_key = next(key for key in self.numpy_inputs if key.startswith('desire'))
     self._road_key = next(key for key in self._vision_input_names if 'big' not in key)
     self._wide_key = next(key for key in self._vision_input_names if 'big' in key)
+    self.frame_buf_params = dict.fromkeys(self._vision_input_names, nv12_info)
 
     is_20hz = bundle.is20hz if bundle else self._combined_model_type in ('split', 'multi_policy')
     if is_20hz:
       from openpilot.sunnypilot.models.split_model_constants import SplitModelConstants
       self.constants = SplitModelConstants()
     else:
-      from openpilot.sunnypilot.modeld_v2.constants import ModelConstants
       self.constants = ModelConstants()
 
-    if self._combined_model_type != 'supercombo':
-      from openpilot.sunnypilot.modeld_v2.parse_model_outputs_split import Parser as SplitParser
-      self.parser = SplitParser()
-    else:
-      from openpilot.sunnypilot.modeld_v2.parse_model_outputs import Parser as CombinedParser
-      self.parser = CombinedParser()
-
+    self.parser = Parser()
     self.prev_desire = np.zeros(self.constants.DESIRE_LEN, dtype=np.float32)
-    self.full_frames: dict = {}
-    self._blob_cache: dict = {}
-    nv12_info = get_nv12_info(cam_w, cam_h)
-    self.frame_buf_params = dict.fromkeys(self._vision_input_names, nv12_info)
 
-    yuv_size = self.frame_buf_params[self._road_key][3]
-    frame_tensor = Tensor(np.zeros(yuv_size, dtype=np.uint8), device=self.WARP_DEV).contiguous().realize()
-    big_frame_tensor = Tensor(np.zeros(yuv_size, dtype=np.uint8), device=self.WARP_DEV).contiguous().realize()
-
-    if self.is_legacy_model: # Remove this conditional hack after recompile
-      self.warp(**self.input_queues, frame=frame_tensor, big_frame=big_frame_tensor)
-    else:
-      self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=frame_tensor, big_frame=big_frame_tensor)
-
-    if self.usbgpu:
-      self.warmup()
+    if self.warp is not None:
+      self.full_frames = {k: Tensor(np.zeros(nv12_info[3], dtype=np.uint8), device=self.WARP_DEV).contiguous().realize() for k in self._vision_input_names}
+      self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames[self._road_key], big_frame=self.full_frames[self._wide_key])
 
   def warmup(self) -> None:
-    dummy_frames = {k: np.zeros(self.frame_buf_params[k][3], dtype=np.uint8) for k in self._vision_input_names}
+    dummy_size = self.frame_copy_size if self.is_run_model else self.frame_buf_params[self._road_key][3]
+    dummy_frames = {k: np.zeros(dummy_size, dtype=np.uint8) for k in self._vision_input_names}
     transforms = {k: np.eye(3, dtype=np.float32) for k in [self._road_key, self._wide_key] if k}
-
-    dummy_inputs = {}
-    for k, v in self.numpy_inputs.items():
-      if k not in ['tfm', 'big_tfm', 'prev_feat']:
-        dummy_inputs[k] = np.zeros(v.shape, dtype=v.dtype)
-
-    self.run(dummy_frames, transforms, dummy_inputs, prepare_only=False)
-
-    for v in self.numpy_inputs.values():
-      v[:] = 0
+    dummy_inputs = {k: np.zeros(v.shape, dtype=v.dtype) for k, v in self.numpy_inputs.items() if k not in ['tfm', 'big_tfm', 'prev_feat']}
+    self.run(dummy_frames, transforms, dummy_inputs)
+    if self.is_run_model:
+      self.input_queues, self.numpy_inputs, self.frame_buffers = make_stock_input_queues(
+        self.input_shapes, self.frame_skip, device=self.DEV, frame_copy_size=self.frame_copy_size)
+      self.frame_views = self.frame_buffers
+      self.npy = self.numpy_inputs
+    else:
+      for v in self.numpy_inputs.values():
+        v[:] = 0
+      self.full_frames.clear()
+      self._blob_cache.clear()
     self.prev_desire[:] = 0
-    self.full_frames.clear()
-    self._blob_cache.clear()
-
 
   @property
   def mlsim(self) -> bool:
@@ -219,45 +214,50 @@ class ModelState(ModelStateBase):
     return self._desire_key
 
   def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray],
-                inputs: dict[str, np.ndarray], prepare_only: bool) -> dict[str, np.ndarray] | None:
-    for key in bufs.keys():
-      ptr = np.frombuffer(bufs[key].data, dtype=np.uint8).ctypes.data
-      yuv_size = self.frame_buf_params[key][3]
-      cache_key = (key, ptr)
-      if cache_key not in self._blob_cache:
-        self._blob_cache[cache_key] = Tensor.from_blob(ptr, (yuv_size,), dtype='uint8', device=self.WARP_DEV)
-      self.full_frames[key] = self._blob_cache[cache_key]
+          inputs: dict[str, np.ndarray],
+          after_enqueue: Callable[[], None] | None = None) -> dict[str, np.ndarray] | None:
+    if self.is_run_model:
+      for key, buf in bufs.items():
+        data = buf.data if hasattr(buf, 'data') else buf
+        np.copyto(self.frame_buffers[key], np.frombuffer(data, dtype=np.uint8, count=self.frame_copy_size))
+    else:
+      for key, buf in bufs.items():
+        ptr = np.frombuffer(buf.data, dtype=np.uint8).ctypes.data
+        cache_key = (key, ptr)
+        if cache_key not in self._blob_cache:
+          self._blob_cache[cache_key] = Tensor.from_blob(ptr, (self.frame_buf_params[key][3],), dtype='uint8', device=self.WARP_DEV)
+        self.full_frames[key] = self._blob_cache[cache_key]
 
     desire_key = self.desire_key
     inputs[desire_key][0] = 0
     self.numpy_inputs[desire_key][:] = np.where(inputs[desire_key] - self.prev_desire > .99, inputs[desire_key], 0)
     self.prev_desire[:] = inputs[desire_key]
+
     for key in ('traffic_convention', 'lateral_control_params', 'action_t'):
       if key in self.numpy_inputs and key in inputs:
         self.numpy_inputs[key][:] = inputs[key]
 
-    road_key = self._road_key
-    wide_key = self._wide_key
-    self.numpy_inputs['tfm'][:, :] = transforms[road_key].reshape(3, 3)
-    self.numpy_inputs['big_tfm'][:, :] = transforms[wide_key].reshape(3, 3)
+    self.numpy_inputs['tfm'][:, :] = transforms[self._road_key].reshape(3, 3)
+    self.numpy_inputs['big_tfm'][:, :] = transforms[self._wide_key].reshape(3, 3)
 
-    if self.is_legacy_model:  # remove after next recompile
-      if prepare_only:
-        self.warp(**self.input_queues, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
-        return None
-      raw_outputs = self.run_policy(**self.input_queues, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
+    if self.run_model is not None:
+      outs, = self.run_model(**{k: self.input_queues[k] for k in MODELD_INPUTS})
+      raw_outputs = outs
     else:
-      if prepare_only:
-        self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
-        return None
-      warped = self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
+      assert self.warp is not None and self.run_policy is not None
+      warped = self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames[self._road_key], big_frame=self.full_frames[self._wide_key])
       raw_outputs = self.run_policy(**{k: self.input_queues[k] for k in POLICY_INPUTS if k in self.input_queues}, warped=warped)
 
+    if after_enqueue is not None:
+      after_enqueue()
+
     if self._combined_model_type == 'supercombo':
       model_output = raw_outputs.numpy().flatten()
+      if self.chestnut and not np.all(np.isfinite(model_output)):
+        raise RuntimeError("model output not finite")
       sliced = {k: model_output[np.newaxis, v] for k, v in self.vision_output_slices.items()}
       outputs = self.parser.parse_outputs(sliced)
-      if 'prev_feat' in self.numpy_inputs:
+      if 'prev_feat' in self.numpy_inputs and 'hidden_state' in self.vision_output_slices:
         self.numpy_inputs['prev_feat'][:] = model_output[self.vision_output_slices['hidden_state']]
     else:
       vision_output = raw_outputs[0].numpy().flatten()
@@ -287,10 +287,6 @@ class ModelState(ModelStateBase):
       buf[0, :-1] = buf[0, 1:]
       buf[0, -1, :] = outputs['desired_curvature'][0, :] if not self.mlsim else 0
 
-    if self.usbgpu and not np.all(np.isfinite(outputs.get('plan', np.array([0.])))):
-      cloudlog.error("model output not finite, dropping frame")
-      return None
-
     return outputs
 
   def get_action_from_model(self, model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action,
@@ -327,13 +323,13 @@ def main(demo=False):
   setproctitle(PROCESS_NAME)
   config_realtime_process(7, 54)
 
-  USBGPU = usbgpu_present()
-  if USBGPU:
+  CHESTNUT = chestnut_present()
+  if CHESTNUT:
     os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
 
   params = Params()
-  params.put_bool("UsbGpuLoading", USBGPU)
-  params.remove("UsbGpuActive")
+  params.put_bool("ChestnutLoading", CHESTNUT)
+  params.remove("ChestnutActive")
 
   # visionipc clients
   while True:
@@ -362,31 +358,40 @@ def main(demo=False):
   st = time.monotonic()
 
   model = None
-  if USBGPU:
-    import threading
-    def load():
-      nonlocal model
-      model = ModelState(cam_w=vipc_client_main.width, cam_h=vipc_client_main.height, usbgpu=True)
-    t = threading.Thread(target=load, daemon=True)
-    t.start()
-    t.join(60)
+  if CHESTNUT:
+    big_model = None
+    def load_big():
+      nonlocal big_model
+      try:
+        m = ModelState(cam_w=vipc_client_main.width, cam_h=vipc_client_main.height, chestnut=True)
+        m.warmup()
+        big_model = m
+      except Exception:
+        cloudlog.exception("chestnut load failed")
+    loader = threading.Thread(target=load_big, daemon=True)
+    loader.start()
+    loader.join(BIG_MODEL_TIMEOUT)
+    model = big_model
     if model is None:
-      params.put_bool("UsbGpuActive", False)
-      raise RuntimeError("eGPU model load failed or timed out (60s)")
-    params.put_bool("UsbGpuActive", True)
-  else:
-    model = ModelState(cam_w=vipc_client_main.width, cam_h=vipc_client_main.height, usbgpu=False)
+      params.put_bool("ChestnutModelError", True)
+    params.put_bool("ChestnutActive", model is not None)
+    if model is not None:
+      params.remove("ChestnutModelError")
 
-  params.put_bool("UsbGpuLoading", False)
+  small_model = ModelState(cam_w=vipc_client_main.width, cam_h=vipc_client_main.height, chestnut=False) if model is None or CHESTNUT else None
+  if model is None:
+    model = small_model
+  params.put_bool("ChestnutLoading", False)
+  assert model is not None
   cloudlog.warning(f"models loaded in {time.monotonic() - st:.1f}s, modeld starting")
 
   # messaging
-  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if USBGPU else [])
+  pub_socks = ["modelV2", "drivingModelData", "cameraOdometry", "modelDataV2SP"] + (["chestnutState"] if CHESTNUT else [])
   pm = PubMaster(pub_socks)
   sm = SubMaster(["deviceState", "carState", "narrowRoadCameraState", "extrinsicsCalibration", "driverMonitoringState", "carControl", "lateralDelay"])
 
   publish_state = PublishState()
-  chestnut_state = ChestnutState(pm, USBGPU) if USBGPU else None
+  chestnut_state = ChestnutState(pm, model.chestnut) if CHESTNUT else None
 
   # setup filter to track dropped frames
   frame_dropped_filter = FirstOrderFilter(0., 10., 1. / model.constants.MODEL_FREQ)
@@ -485,9 +490,6 @@ def main(demo=False):
     run_count = run_count + 1
 
     frame_drop_ratio = frames_dropped / (1 + frames_dropped)
-    prepare_only = vipc_dropped_frames > 0
-    if prepare_only:
-      cloudlog.error(f"skipping model eval. Dropped {vipc_dropped_frames} frames")
 
     bufs = {name: buf_extra if 'big' in name else buf_main for name in model.vision_input_names}
     transforms = {name: model_transform_extra if 'big' in name else model_transform_main for name in model.vision_input_names}
@@ -509,7 +511,22 @@ def main(demo=False):
       inputs['action_t'] = np.array([lat_action_t, long_action_t], dtype=np.float32)
 
     mt1 = time.perf_counter()
-    model_output = model.run(bufs, transforms, inputs, prepare_only)
+    try:
+      send_chestnut = (chestnut_state is not None and
+                       run_count % round(model.constants.MODEL_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0)
+      model_output = model.run(bufs, transforms, inputs, chestnut_state.send if send_chestnut else None)
+    except Exception:
+      if not params.get_bool("ChestnutActive"):
+        raise
+      cloudlog.exception("chestnut failed, falling back to small")
+      params.put_bool("ChestnutModelError", True)
+      params.put_bool("ChestnutActive", False)
+      assert small_model is not None
+      model = small_model
+      if chestnut_state is not None:
+        chestnut_state.big = False
+      run_count = 0
+      model_output = None
     mt2 = time.perf_counter()
     model_execution_time = mt2 - mt1
 
@@ -524,7 +541,7 @@ def main(demo=False):
       fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
                      publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
                      frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, live_calib_seen, meta_constants)
-      modelv2_send.modelV2.big = model.usbgpu
+      modelv2_send.modelV2.big = model.chestnut
 
       desire_state = modelv2_send.modelV2.meta.desireState
       l_lane_change_prob = desire_state[log.Desire.laneChangeLeft]
@@ -545,9 +562,6 @@ def main(demo=False):
       pm.send('modelDataV2SP', mdv2sp_send)
     last_vipc_frame_id = meta_main.frame_id
 
-    if chestnut_state is not None and run_count % round(model.constants.MODEL_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0:
-      chestnut_state.send()
-
 if __name__ == "__main__":
   try:
     import argparse

openpilot/sunnypilot/modeld_v2/parse_model_outputs.py

@@ -115,22 +115,41 @@ class Parser:
     outs[name + '_stds'] = pred_std_final.reshape(final_shape)
 
   def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
-    # supercombo (4955 / 102) and newer variants (e.g. 990 / 144).
-    self.parse_mdn('plan',   outs, out_shape=(ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH))
-    self.parse_mdn('lane_lines', outs, out_shape=(ModelConstants.NUM_LANE_LINES, ModelConstants.IDX_N, ModelConstants.LANE_LINES_WIDTH))
-    self.parse_mdn('road_edges', outs, out_shape=(ModelConstants.NUM_ROAD_EDGES, ModelConstants.IDX_N, ModelConstants.LANE_LINES_WIDTH))
-    self.parse_mdn('pose',         outs, out_shape=(ModelConstants.POSE_WIDTH,))
-    self.parse_mdn('road_transform', outs, out_shape=(ModelConstants.POSE_WIDTH,))
+    if 'plan' in outs:
+      self.parse_mdn('plan', outs, out_shape=(ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH))
+    if 'planplus' in outs:
+      self.parse_mdn('planplus', outs, out_shape=(ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH))
+    if 'lane_lines' in outs:
+      self.parse_mdn('lane_lines', outs, out_shape=(ModelConstants.NUM_LANE_LINES, ModelConstants.IDX_N, ModelConstants.LANE_LINES_WIDTH))
+    if 'road_edges' in outs:
+      self.parse_mdn('road_edges', outs, out_shape=(ModelConstants.NUM_ROAD_EDGES, ModelConstants.IDX_N, ModelConstants.LANE_LINES_WIDTH))
+    if 'pose' in outs:
+      self.parse_mdn('pose', outs, out_shape=(ModelConstants.POSE_WIDTH,))
+    if 'road_transform' in outs:
+      self.parse_mdn('road_transform', outs, out_shape=(ModelConstants.POSE_WIDTH,))
     if 'sim_pose' in outs:
       self.parse_mdn('sim_pose', outs, out_shape=(ModelConstants.POSE_WIDTH,))
-    self.parse_mdn('wide_from_device_euler', outs, out_shape=(ModelConstants.WIDE_FROM_DEVICE_WIDTH,))
-    self.parse_mdn('lead', outs, out_shape=(ModelConstants.LEAD_TRAJ_LEN, ModelConstants.LEAD_WIDTH))
+    if 'wide_from_device_euler' in outs:
+      self.parse_mdn('wide_from_device_euler', outs, out_shape=(ModelConstants.WIDE_FROM_DEVICE_WIDTH,))
+    if 'lead' in outs:
+      self.parse_mdn('lead', outs, out_shape=(ModelConstants.LEAD_TRAJ_LEN, ModelConstants.LEAD_WIDTH))
     if 'lat_planner_solution' in outs:
       self.parse_mdn('lat_planner_solution', outs, out_shape=(ModelConstants.IDX_N, ModelConstants.LAT_PLANNER_SOLUTION_WIDTH))
     if 'desired_curvature' in outs:
       self.parse_mdn('desired_curvature', outs, out_shape=(ModelConstants.DESIRED_CURV_WIDTH,))
+    if 'action' in outs:
+      self.parse_mdn('action', outs, out_shape=(ModelConstants.ACTION_WIDTH,))
     for k in ['lead_prob', 'lane_lines_prob', 'meta']:
-      self.parse_binary_crossentropy(k, outs)
-    self.parse_categorical_crossentropy('desire_state', outs, out_shape=(ModelConstants.DESIRE_PRED_WIDTH,))
-    self.parse_categorical_crossentropy('desire_pred',  outs, out_shape=(ModelConstants.DESIRE_PRED_LEN, ModelConstants.DESIRE_PRED_WIDTH))
+      if k in outs:
+        self.parse_binary_crossentropy(k, outs)
+    if 'desire_state' in outs:
+      self.parse_categorical_crossentropy('desire_state', outs, out_shape=(ModelConstants.DESIRE_PRED_WIDTH,))
+    if 'desire_pred' in outs:
+      self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(ModelConstants.DESIRE_PRED_LEN, ModelConstants.DESIRE_PRED_WIDTH))
     return outs
+
+  def parse_vision_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
+    return self.parse_outputs(outs)
+
+  def parse_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
+    return self.parse_outputs(outs)

openpilot/sunnypilot/modeld_v2/parse_model_outputs_split.py

@@ -1,159 +0,0 @@
-import numpy as np
-from openpilot.sunnypilot.models.split_model_constants import SplitModelConstants
-
-
-def safe_exp(x, out=None):
-  # -11 is around 10**14, more causes float16 overflow
-  return np.exp(np.clip(x, -np.inf, 11), out=out)
-
-
-def sigmoid(x):
-  return 1. / (1. + safe_exp(-x))
-
-
-def softmax(x, axis=-1):
-  x -= np.max(x, axis=axis, keepdims=True)
-  if x.dtype == np.float32 or x.dtype == np.float64:
-    safe_exp(x, out=x)
-  else:
-    x = safe_exp(x)
-  x /= np.sum(x, axis=axis, keepdims=True)
-  return x
-
-
-class Parser:
-  def __init__(self, ignore_missing=False):
-    self.ignore_missing = ignore_missing
-
-  def check_missing(self, outs, name):
-    if name not in outs and not self.ignore_missing:
-      raise ValueError(f"Missing output {name}")
-    return name not in outs
-
-  def parse_categorical_crossentropy(self, name, outs, out_shape=None):
-    if self.check_missing(outs, name):
-      return
-    raw = outs[name]
-    if out_shape is not None:
-      raw = raw.reshape((raw.shape[0],) + out_shape)
-    outs[name] = softmax(raw, axis=-1)
-
-  def parse_binary_crossentropy(self, name, outs):
-    if self.check_missing(outs, name):
-      return
-    raw = outs[name]
-    outs[name] = sigmoid(raw)
-
-  def parse_mdn(self, name, outs, in_N=0, out_N=1, out_shape=None):
-    if self.check_missing(outs, name):
-      return
-    raw = outs[name]
-    raw = raw.reshape((raw.shape[0], max(in_N, 1), -1))
-
-    n_values = (raw.shape[2] - out_N)//2
-    pred_mu = raw[:,:,:n_values]
-    pred_std = safe_exp(raw[:,:,n_values: 2*n_values])
-
-    if in_N > 1:
-      weights = np.zeros((raw.shape[0], in_N, out_N), dtype=raw.dtype)
-      for i in range(out_N):
-        weights[:,:,i - out_N] = softmax(raw[:,:,i - out_N], axis=-1)
-
-      if out_N == 1:
-        for fidx in range(weights.shape[0]):
-          idxs = np.argsort(weights[fidx][:,0])[::-1]
-          weights[fidx] = weights[fidx][idxs]
-          pred_mu[fidx] = pred_mu[fidx][idxs]
-          pred_std[fidx] = pred_std[fidx][idxs]
-      assert out_shape is not None
-      full_shape = tuple([raw.shape[0], in_N] + list(out_shape))
-      outs[name + '_weights'] = weights
-      outs[name + '_hypotheses'] = pred_mu.reshape(full_shape)
-      outs[name + '_stds_hypotheses'] = pred_std.reshape(full_shape)
-
-      pred_mu_final = np.zeros((raw.shape[0], out_N, n_values), dtype=raw.dtype)
-      pred_std_final = np.zeros((raw.shape[0], out_N, n_values), dtype=raw.dtype)
-      for fidx in range(weights.shape[0]):
-        for hidx in range(out_N):
-          idxs = np.argsort(weights[fidx,:,hidx])[::-1]
-          pred_mu_final[fidx, hidx] = pred_mu[fidx, idxs[0]]
-          pred_std_final[fidx, hidx] = pred_std[fidx, idxs[0]]
-    else:
-      pred_mu_final = pred_mu
-      pred_std_final = pred_std
-
-    if out_N > 1:
-      assert out_shape is not None
-      final_shape = tuple([raw.shape[0], out_N] + list(out_shape))
-    else:
-      assert out_shape is not None
-      final_shape = tuple([raw.shape[0],] + list(out_shape))
-    outs[name] = pred_mu_final.reshape(final_shape)
-    outs[name + '_stds'] = pred_std_final.reshape(final_shape)
-
-  def is_mhp(self, outs, name, shape):
-    if self.check_missing(outs, name):
-      return False
-    if outs[name].shape[1] == 2 * shape:
-      return False
-    return True
-
-  def parse_dynamic_outputs(self, outs: dict[str, np.ndarray]) -> None:
-    if 'lead' in outs:
-      lead_mhp = self.is_mhp(outs, 'lead',
-                             SplitModelConstants.LEAD_MHP_SELECTION * SplitModelConstants.LEAD_TRAJ_LEN * SplitModelConstants.LEAD_WIDTH)
-      lead_in_N, lead_out_N = (SplitModelConstants.LEAD_MHP_N, SplitModelConstants.LEAD_MHP_SELECTION) if lead_mhp else (0, 0)
-      lead_out_shape = (SplitModelConstants.LEAD_TRAJ_LEN, SplitModelConstants.LEAD_WIDTH) if lead_mhp else \
-        (SplitModelConstants.LEAD_MHP_SELECTION, SplitModelConstants.LEAD_TRAJ_LEN, SplitModelConstants.LEAD_WIDTH)
-      self.parse_mdn('lead', outs, in_N=lead_in_N, out_N=lead_out_N, out_shape=lead_out_shape)
-    if 'plan' in outs:
-      plan_mhp = self.is_mhp(outs, 'plan', SplitModelConstants.IDX_N * SplitModelConstants.PLAN_WIDTH)
-      plan_in_N, plan_out_N = (SplitModelConstants.PLAN_MHP_N, SplitModelConstants.PLAN_MHP_SELECTION) if plan_mhp else (0, 0)
-      self.parse_mdn('plan', outs, in_N=plan_in_N, out_N=plan_out_N,
-                     out_shape=(SplitModelConstants.IDX_N, SplitModelConstants.PLAN_WIDTH))
-    if 'planplus' in outs:
-      self.parse_mdn('planplus', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.IDX_N, SplitModelConstants.PLAN_WIDTH))
-
-  def split_outputs(self, outs: dict[str, np.ndarray]) -> None:
-    if 'desired_curvature' in outs:
-      self.parse_mdn('desired_curvature', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.DESIRED_CURV_WIDTH,))
-    if 'desire_pred' in outs:
-      self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(SplitModelConstants.DESIRE_PRED_LEN,SplitModelConstants.DESIRE_PRED_WIDTH))
-    if 'desire_state' in outs:
-      self.parse_categorical_crossentropy('desire_state', outs, out_shape=(SplitModelConstants.DESIRE_PRED_WIDTH,))
-    if 'lane_lines' in outs:
-      self.parse_mdn('lane_lines', outs, in_N=0, out_N=0,
-                     out_shape=(SplitModelConstants.NUM_LANE_LINES,SplitModelConstants.IDX_N,SplitModelConstants.LANE_LINES_WIDTH))
-    if 'lane_lines_prob' in outs:
-      self.parse_binary_crossentropy('lane_lines_prob', outs)
-    if 'lead_prob' in outs:
-      self.parse_binary_crossentropy('lead_prob', outs)
-    if 'lat_planner_solution' in outs:
-      self.parse_mdn('lat_planner_solution', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.IDX_N,SplitModelConstants.LAT_PLANNER_SOLUTION_WIDTH))
-    if 'meta' in outs:
-      self.parse_binary_crossentropy('meta', outs)
-    if 'road_edges' in outs:
-      self.parse_mdn('road_edges', outs, in_N=0, out_N=0,
-                     out_shape=(SplitModelConstants.NUM_ROAD_EDGES,SplitModelConstants.IDX_N,SplitModelConstants.LANE_LINES_WIDTH))
-    if 'sim_pose' in outs:
-      self.parse_mdn('sim_pose', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.POSE_WIDTH,))
-    if 'action' in outs:
-      self.parse_mdn('action', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.ACTION_WIDTH,))
-
-  def parse_vision_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
-    self.parse_mdn('pose', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.POSE_WIDTH,))
-    self.parse_mdn('wide_from_device_euler', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.WIDE_FROM_DEVICE_WIDTH,))
-    self.parse_mdn('road_transform', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.POSE_WIDTH,))
-    self.parse_dynamic_outputs(outs)
-    self.split_outputs(outs)
-    return outs
-
-  def parse_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
-    self.parse_dynamic_outputs(outs)
-    self.split_outputs(outs)
-    return outs
-
-  def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
-    outs = self.parse_vision_outputs(outs)
-    outs = self.parse_policy_outputs(outs)
-    return outs

openpilot/sunnypilot/modeld_v2/tests/helpers.py

@@ -117,7 +117,7 @@ ARCHETYPES = {
     is_20hz=True,
     expected_model_type='split',
     expected_constants_class=SplitModelConstants,
-    expected_parser_module='parse_model_outputs_split',
+    expected_parser_module='parse_model_outputs',
     expected_desire_key='desire',
   ),
   'vision_multi_policy': Archetype(
@@ -130,7 +130,7 @@ ARCHETYPES = {
     is_20hz=True,
     expected_model_type='multi_policy',
     expected_constants_class=SplitModelConstants,
-    expected_parser_module='parse_model_outputs_split',
+    expected_parser_module='parse_model_outputs',
     expected_desire_key='desire',
   ),
   'tri_policy': Archetype(
@@ -144,7 +144,7 @@ ARCHETYPES = {
     is_20hz=True,
     expected_model_type='multi_policy',
     expected_constants_class=SplitModelConstants,
-    expected_parser_module='parse_model_outputs_split',
+    expected_parser_module='parse_model_outputs',
     expected_desire_key='desire',
   ),
   'supercombo_non20hz': Archetype(
@@ -190,8 +190,8 @@ def tmp_path():
 
 def patch_modeld(monkeypatch):
   def _patch(bundle):
-    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None: bundle)
-    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None: bundle)
+    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
+    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
 
   return _patch
 

openpilot/sunnypilot/modeld_v2/tests/test_combined_pkl_loader.py

@@ -59,8 +59,8 @@ class TestFindDrivingPkl(OpenpilotTestCase):
 class TestModelStateCombinedInit(OpenpilotTestCase):
   def test_asserts_when_no_pkl(self, monkeypatch):
     bundle = DummyBundle(models=[], is_20hz=True)
-    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None: bundle)
-    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None: bundle)
+    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
+    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
     with self.assertRaisesRegex(AssertionError, "No driving pkl found"):
       ModelState(cam_w=CAM_W, cam_h=CAM_H)
 
@@ -75,11 +75,11 @@ class TestStockEquivalence(OpenpilotTestCase):
 
     frame_skip = derive_frame_skip(SPLIT_VISION_INPUT_SHAPES, SPLIT_POLICY_INPUT_SHAPES)
     stock_shapes = {**SPLIT_VISION_INPUT_SHAPES, **SPLIT_POLICY_INPUT_SHAPES, 'action_t': (1, 2)}
-    stock_queues, stock_npy = make_input_queues(stock_shapes, frame_skip, device='NPY')
+    stock_queues, stock_npy, _frame_views = make_input_queues(stock_shapes, frame_skip, device='NPY', frame_copy_size=49152)
 
-    assert set(state.input_queues.keys()) == set(stock_queues.keys())
+    # sunnypilot split pipeline has tfm/big_tfm as queues (stock has them in npy only)
+    assert set(stock_queues.keys()) <= set(state.input_queues.keys())
     assert {'desire', 'traffic_convention'} <= set(state.numpy_inputs.keys())
-    assert set(state.numpy_inputs.keys()) == set(stock_npy.keys()) - {'action_t', 'prev_feat'}
 
   def test_split_queue_keys_work_with_desire_key(self, model_state_factory):
     from openpilot.sunnypilot.modeld_v2.compile_modeld import derive_frame_skip, make_split_input_queues
@@ -103,6 +103,23 @@ class TestStockEquivalence(OpenpilotTestCase):
     assert state.vision_output_slices == arch.metadata_structure['vision']['output_slices']
     assert state.policy_output_slices == arch.metadata_structure['policy']['output_slices']
 
+  def test_unified_run_model(self, tmp_path, monkeypatch, patch_modeld):
+    from openpilot.common.hardware import hw
+    from openpilot.selfdrive.modeld.helpers import dump_oob
+    shapes = {'img': (1, 12, 128, 256), 'big_img': (1, 12, 128, 256), 'features_buffer': (1, 24, 32, 512),
+              'desire_pulse': (1, 25, 8), 'traffic_convention': (1, 2), 'action_t': (1, 2)}
+    pkl_data = {'metadata': {'model': {'input_shapes': shapes, 'output_slices': {}}},
+                'run_model': {(CAM_W, CAM_H): tests_helpers._noop_jit}}
+    with open(tmp_path / 'driving_test_tinygrad.pkl', 'wb') as f:
+      dump_oob(pkl_data, f)
+    bundle = DummyBundle(models=[DummyModel('supercombo', 'driving_test_tinygrad.pkl')])
+    patch_modeld(bundle)
+    monkeypatch.setattr(hw.Paths, 'model_root', staticmethod(lambda: str(tmp_path)))
+    state = ModelState(cam_w=CAM_W, cam_h=CAM_H)
+    assert state.is_run_model and state.run_model is not None
+    assert state.run_policy is None and state.warp is None
+    assert 'img' in state.frame_views and 'big_img' in state.frame_views
+
 
 ARCHETYPE_NAMES = list(ARCHETYPES.keys())