Merge branch 'master' into elantra-2024-port

.gitattributes

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

.github/CODEOWNERS

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

.github/release-drafter.yml

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

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

@@ -8,23 +8,18 @@ on:
         required: true
         type: string
       target_hardware:
-        description: 'Hardware target to compile for (qcom or chestnut)'
+        description: 'Hardware target to compile for (qcom or usbgpu)'
         required: true
         type: choice
         default: 'qcom'
         options:
           - qcom
-          - chestnut
+          - usbgpu
       hf_repo:
         description: 'Hugging Face dataset repository'
         required: false
         type: string
         default: 'sunnypilot/sunnypilot_models_v1'
-      docs_repo:
-        description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
-        required: false
-        type: string
-        default: 'sunnypilot/sunnypilot-models'
 
 jobs:
   setup:
@@ -39,9 +34,9 @@ jobs:
       - name: Checkout sunnypilot repo
         uses: actions/checkout@v4
         with:
+          repository: sunnypilot/sunnypilot
           path: sunnypilot
           submodules: recursive
-          fetch-depth: 1
 
       - name: Get tinygrad_repo ref
         id: get-tinygrad-ref
@@ -52,20 +47,19 @@ jobs:
           echo "tinygrad_ref=$ref" >> $GITHUB_OUTPUT
           echo "tinygrad_ref is $ref"
 
-      - name: Checkout docs repo (gh-pages)
+      - name: Checkout docs repo (sunnypilot-models, gh-pages)
         uses: actions/checkout@v4
         with:
-          repository: ${{ inputs.docs_repo }}
+          repository: sunnypilot/sunnypilot-models
           ref: gh-pages
           path: docs
           ssh-key: ${{ secrets.CI_SUNNYPILOT_DOCS_PRIVATE_KEY }}
-          fetch-depth: 1
 
       - name: Get next JSON version to use (from GitHub docs repo)
         id: get-json
         run: |
           cd docs/docs
-          PREFIX="driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_' || '' }}v"
+          PREFIX="driving_models_${{ inputs.target_hardware == 'usbgpu' && 'usbgpu_' || '' }}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"
@@ -84,7 +78,6 @@ 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
@@ -124,7 +117,6 @@ jobs:
       json_version: ${{ needs.setup.outputs.json_version }}
       target_hardware: ${{ github.event.inputs.target_hardware }}
       hf_repo: ${{ github.event.inputs.hf_repo }}
-      docs_repo: ${{ inputs.docs_repo }}
       set_min_version: ${{ github.event.inputs.set_min_version }}
       tinygrad_ref: ${{ needs.setup.outputs.tinygrad_ref }}
     secrets: inherit
@@ -169,7 +161,6 @@ jobs:
       target_hardware: ${{ github.event.inputs.target_hardware }}
       artifact_suffix: -retry
       hf_repo: ${{ github.event.inputs.hf_repo }}
-      docs_repo: ${{ inputs.docs_repo }}
       set_min_version: ${{ github.event.inputs.set_min_version }}
       tinygrad_ref: ${{ needs.setup.outputs.tinygrad_ref }}
     secrets: inherit

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

@@ -0,0 +1,83 @@
+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

@@ -1,516 +0,0 @@
-name: Build default models
-
-on:
-  workflow_dispatch:
-    inputs:
-      target:
-        description: 'Model target to build'
-        required: true
-        type: choice
-        options:
-          - small
-          - big
-          - dm
-  workflow_call:
-    inputs:
-      target:
-        description: 'Model target to build (small, big, or dm)'
-        required: true
-        type: string
-
-concurrency:
-  group: build-default-models-${{ inputs.target }}
-  cancel-in-progress: false
-
-env:
-  HF_REPO: sunnypilot/sunnypilot_models_v1
-
-jobs:
-  resolve:
-    runs-on: ubuntu-24.04
-    outputs:
-      model_name: ${{ steps.resolve.outputs.model_name }}
-      safe_model_name: ${{ steps.resolve.outputs.safe_model_name }}
-      onnx_ref: ${{ steps.resolve.outputs.onnx_ref }}
-      onnx_path: ${{ steps.resolve.outputs.onnx_path }}
-      hf_defaults_path: ${{ steps.resolve.outputs.hf_defaults_path }}
-      tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-
-      - id: resolve
-        run: |
-          export PYTHONPATH=${{ github.workspace }}
-
-          if [ "${{ inputs.target }}" = "big" ]; then
-            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
-            HF_DEFAULTS_PATH="models/defaults/big"
-          elif [ "${{ inputs.target }}" = "dm" ]; then
-            ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
-            HF_DEFAULTS_PATH="models/defaults/dm"
-            NAME="dmonitoring_model ($(git log -1 --format=%cd --date=format:'%B %d, %Y' -- "$ONNX_PATH"))"
-          else
-            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL; print(DEFAULT_MODEL)")
-            ONNX_PATH="openpilot/selfdrive/modeld/models/driving_supercombo.onnx"
-            HF_DEFAULTS_PATH="models/defaults/small"
-          fi
-          ONNX_REF=""
-          [ -n "$ONNX_PATH" ] && ONNX_REF=$(git log -1 --format='%H' -- "$ONNX_PATH")
-
-          TINYGRAD_REF=$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)
-          if [ -z "$TINYGRAD_REF" ]; then
-            echo "::error::Failed to resolve tinygrad ref"
-            exit 1
-          fi
-
-          SAFE_NAME="${NAME// /-}"
-          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
-          echo "safe_model_name=${SAFE_NAME}" >> $GITHUB_OUTPUT
-          echo "onnx_ref=${ONNX_REF}" >> $GITHUB_OUTPUT
-          echo "onnx_path=${ONNX_PATH}" >> $GITHUB_OUTPUT
-          echo "hf_defaults_path=${HF_DEFAULTS_PATH}" >> $GITHUB_OUTPUT
-          echo "tinygrad_ref=${TINYGRAD_REF}" >> $GITHUB_OUTPUT
-
-  build_small_model:
-    needs: resolve
-    if: ${{ inputs.target == 'small' }}
-    runs-on: [self-hosted, tici]
-    env:
-      MODELS_DIR: openpilot/selfdrive/modeld/models
-      COMPILER: tinygrad_repo/examples/openpilot
-      SMALL_ONNX: openpilot/selfdrive/modeld/models/driving_supercombo.onnx
-      SMALL_PKL: openpilot/selfdrive/modeld/models/driving_tinygrad.pkl
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-
-      - name: Pull small ONNX via LFS
-        run: git lfs pull -I "${{ env.SMALL_ONNX }}"
-
-
-      - name: Set environment variables
-        run: |
-          source /etc/profile
-          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
-          export UV_PYTHON_PREFERENCE=managed
-          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
-          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
-          uv sync --frozen
-          printenv >> $GITHUB_ENV
-
-      - name: Disable powersave
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
-
-      - name: Compile small model from ONNX
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-          env ${TG_FLAGS} python3 ${{ github.workspace }}/${{ env.COMPILER }}/compile_onnx.py \
-            ${{ github.workspace }}/${{ env.SMALL_ONNX }} \
-            ${{ github.workspace }}/${{ env.SMALL_PKL }} \
-            --device-input "*" --out-of-band --benchmark-runs 1
-
-      - name: 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" "$OUTPUT_DIR/"
-
-          ONNX_SHA256=$(git cat-file blob "$(git ls-files -s "${{ github.workspace }}/${{ env.SMALL_ONNX }}" | awk '{print $2}')" | grep '^oid sha256:' | cut -d: -f2)
-
-          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
-            --model-dir "$MODELS_DIR" \
-            --output-dir "$OUTPUT_DIR" \
-            --custom-name "$MODEL_NAME" \
-            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}" \
-            --onnx-sha256 "$ONNX_SHA256"
-
-          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
-
-      - name: Upload small model artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
-          path: ${{ github.workspace }}/small_output/
-
-      - name: Upload artifact name file
-        uses: actions/upload-artifact@v4
-        with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
-          path: ${{ github.workspace }}/small_output/artifact_name.txt
-
-      - name: Re-enable powersave
-        if: always()
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
-
-  build_big_model:
-    needs: resolve
-    if: ${{ inputs.target == 'big' }}
-    runs-on: [self-hosted, chestnut]
-    env:
-      MODELS_DIR: openpilot/selfdrive/modeld/models
-      COMPILER: tinygrad_repo/examples/openpilot
-      BIG_PKL: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-          lfs: true
-
-      - name: Pull big PKL via LFS
-        run: git lfs pull -I "${{ env.BIG_PKL }}"
-
-      - name: Set environment variables
-        run: |
-          source /etc/profile
-          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
-          export UV_PYTHON_PREFERENCE=managed
-          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
-          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
-          uv sync --frozen
-          printenv >> $GITHUB_ENV
-
-      - name: Disable powersave
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
-
-      - name: Wait for chestnut PCIe link
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-          python3 -c "
-          import time
-          from openpilot.system.hardware.chestnut.flash import link_up
-          for i in range(10):
-              if link_up():
-                  print(f'PCIe link up after {i+1} attempt(s)')
-                  break
-              time.sleep(1)
-          else:
-              raise RuntimeError('Chestnut PCIe link not ready after 10 attempts')
-          "
-
-      - name: Chunk big pkl
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH=${{ github.workspace }}
-          python3 -c "
-          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
-          import os
-          pkl = '${{ github.workspace }}/${{ env.BIG_PKL }}'
-          size = os.path.getsize(pkl)
-          targets = get_chunk_targets(pkl, size)
-          chunk_file(pkl, targets)
-          print(f'Chunked into {len(targets)} files')
-          "
-
-      - name: Prepare output
-        env:
-          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH=${{ github.workspace }}
-          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
-          OUTPUT_DIR="${{ github.workspace }}/big_output"
-          PKL_BASE="big_driving_tinygrad.pkl"
-          mkdir -p "$OUTPUT_DIR"
-
-          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
-          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
-
-          PKL_LFS_SHA256=$(sha256sum "$MODELS_DIR/${PKL_BASE}" | cut -d' ' -f1)
-
-          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
-            --model-dir "$MODELS_DIR" \
-            --output-dir "$OUTPUT_DIR" \
-            --custom-name "$MODEL_NAME" \
-            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}" \
-            --onnx-sha256 "$PKL_LFS_SHA256"
-
-          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
-
-      - name: Upload big model artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
-          path: ${{ github.workspace }}/big_output/
-
-      - name: Upload artifact name file
-        uses: actions/upload-artifact@v4
-        with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
-          path: ${{ github.workspace }}/big_output/artifact_name.txt
-
-      - name: Re-enable powersave
-        if: always()
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
-
-  upload_defaults:
-    needs: [ resolve, build_small_model, build_big_model, build_dm_model ]
-    if: |
-      ${{
-        !cancelled() &&
-        (inputs.target == 'big' && needs.build_big_model.result == 'success' ||
-         inputs.target == 'small' && needs.build_small_model.result == 'success' ||
-         inputs.target == 'dm' && needs.build_dm_model.result == 'success')
-      }}
-    runs-on: ubuntu-24.04
-    permissions:
-      id-token: write
-      contents: write
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Pull LFS for resolved ONNX files
-        if: ${{ needs.resolve.outputs.onnx_path != '' }}
-        run: git lfs pull -I "${{ needs.resolve.outputs.onnx_path }}"
-
-      - name: Install huggingface_hub
-        run: pip install --upgrade "huggingface_hub>=0.22.0"
-
-      - name: Download artifact name
-        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
-        uses: actions/download-artifact@v4
-        with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
-          path: artifact_name
-
-      - name: Read artifact name
-        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
-        id: artifact
-        run: |
-          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
-          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
-
-      - name: Download model artifact
-        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
-        uses: actions/download-artifact@v4
-        with:
-          name: ${{ steps.artifact.outputs.artifact_name }}
-          path: output
-
-      - name: Upload model to HF
-        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
-          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
-        run: |
-          rm -f output/artifact_name.txt
-          export PYTHONPATH=$(pwd)
-          python3 release/ci/upload_default_model.py \
-            --hf-repo "${{ env.HF_REPO }}" \
-            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
-            --artifact-name "$ARTIFACT_NAME" \
-            --model-dir output \
-            --model-name "${{ needs.resolve.outputs.model_name }}" \
-            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
-            --run-number "${{ github.run_number }}"
-
-      - name: Download DM artifact
-        if: ${{ inputs.target == 'dm' }}
-        uses: actions/download-artifact@v4
-        with:
-          name: dm-model-${{ github.run_number }}
-          path: dm_output
-
-      - name: Generate DM metadata and upload to HF
-        if: ${{ inputs.target == 'dm' }}
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
-        run: |
-          export PYTHONPATH=$(pwd)
-          python3 -c "
-          import json, hashlib
-          from pathlib import Path
-          from datetime import datetime, UTC
-
-          dm_dir = Path('dm_output')
-          manifest = list(dm_dir.glob('*.chunkmanifest'))
-          assert manifest, 'No chunkmanifest found'
-          pkl_name = manifest[0].name.removesuffix('.chunkmanifest')
-          num_chunks = int(manifest[0].read_text().strip())
-
-          chunks = []
-          for i in range(num_chunks):
-              chunk = dm_dir / f'{pkl_name}.chunk{i+1:02d}of{num_chunks:02d}'
-              chunks.append({
-                  'file_name': chunk.name,
-                  'sha256': hashlib.sha256(chunk.read_bytes()).hexdigest()
-              })
-
-          digest = hashlib.sha256()
-          for c in chunks:
-              with open(dm_dir / c['file_name'], 'rb') as f:
-                  while block := f.read(1024*1024):
-                      digest.update(block)
-
-          metadata = {
-              'bundles': [{
-                  'short_name': 'DMMODEL',
-                  'display_name': '${{ needs.resolve.outputs.model_name }}',
-                  'ref': '${{ needs.resolve.outputs.onnx_ref }}',
-                  'runner': 'tinygrad',
-                  'build_time': datetime.now(UTC).strftime('%Y-%m-%dT%H:%M:%SZ'),
-                  'models': [{
-                      'type': 'chunked',
-                      'artifact': {
-                          'file_name': pkl_name,
-                          'download_uri': {'url': '', 'sha256': digest.hexdigest()},
-                          'chunks': chunks
-                      }
-                  }]
-              }]
-          }
-          with open(dm_dir / 'metadata.json', 'w') as f:
-              json.dump(metadata, f, indent=2)
-          print('Generated DM metadata.json')
-          "
-
-          python3 release/ci/upload_default_model.py \
-            --hf-repo "${{ env.HF_REPO }}" \
-            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
-            --artifact-name "dm-model-${{ github.run_number }}" \
-            --model-dir dm_output \
-            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
-            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
-            --model-name "${{ needs.resolve.outputs.model_name }}" \
-            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
-            --run-number "${{ github.run_number }}"
-
-  build_dm_model:
-    needs: resolve
-    if: ${{ inputs.target == 'dm' }}
-    runs-on: [self-hosted, tici]
-    env:
-      DM_ONNX: openpilot/selfdrive/modeld/models/dmonitoring_model.onnx
-      DM_PKL: openpilot/selfdrive/modeld/models/dmonitoring_model_tinygrad.pkl
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-
-      - name: Pull DM ONNX via LFS
-        run: git lfs pull -I "${{ env.DM_ONNX }}"
-
-      - name: Set environment variables
-        run: |
-          source /etc/profile
-          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
-          export UV_PYTHON_PREFERENCE=managed
-          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
-          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
-          uv sync --frozen
-          printenv >> $GITHUB_ENV
-
-      - name: Disable powersave
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
-
-      - name: Compile DM model
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-
-          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-
-          taskset -c 7 env ${TG_FLAGS} python3 \
-            ${{ github.workspace }}/tinygrad_repo/examples/openpilot/compile3.py \
-            ${{ github.workspace }}/${{ env.DM_ONNX }} \
-            ${{ github.workspace }}/${{ env.DM_PKL }}
-
-      - name: Chunk DM pkl
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH=${{ github.workspace }}
-          python3 -c "
-          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
-          import os
-          pkl = '${{ github.workspace }}/${{ env.DM_PKL }}'
-          size = os.path.getsize(pkl)
-          targets = get_chunk_targets(pkl, size)
-          chunk_file(pkl, targets)
-          print(f'Chunked {pkl} into {len(targets)} chunks')
-          "
-
-      - name: Compile DM warp
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-
-          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-          COMPILER="${{ github.workspace }}/tinygrad_repo/examples/openpilot"
-          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
-          DM_SIZE=$(python3 -c "from openpilot.common.transformations.model import DM_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
-
-          for res in $(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')"); do
-            CAM_W=$(echo $res | cut -d x -f1)
-            CAM_H=$(echo $res | cut -d x -f2)
-            STRIDE_INFO=$(python3 -c "
-          import sys
-          from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
-          s,y,u,sz = get_nv12_info(int(sys.argv[1]), int(sys.argv[2]))
-          print(f'{s},{y},{u},{sz}')
-          " $CAM_W $CAM_H)
-            WARP_PKL="${MODELS_DIR}/dm_warp_${res}_tinygrad.pkl"
-            taskset -c 7 env ${TG_FLAGS} python3 "${COMPILER}/compile_warp.py" \
-              --frame ${CAM_W},${CAM_H},${STRIDE_INFO} \
-              --warp-to ${DM_SIZE} \
-              --layout luma \
-              --border-fill 16 \
-              --transform-device NPY \
-              --output "${WARP_PKL}"
-          done
-
-      - name: Prepare DM output
-        run: |
-          mkdir -p dm_output
-          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunk* dm_output/
-          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunkmanifest dm_output/
-          cp ${{ github.workspace }}/openpilot/selfdrive/modeld/models/dm_warp_* dm_output/
-
-      - name: Upload DM artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: dm-model-${{ github.run_number }}
-          path: dm_output/
-
-      - name: Re-enable powersave
-        if: always()
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
-

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

@@ -30,7 +30,7 @@ on:
         type: boolean
         default: true
       target_hardware:
-        description: 'Hardware target to compile for (qcom or chestnut)'
+        description: 'Hardware target to compile for (qcom or usbgpu)'
         required: false
         type: string
         default: 'qcom'
@@ -39,11 +39,6 @@ on:
         required: false
         type: string
         default: 'sunnypilot/sunnypilot_models_v1'
-      docs_repo:
-        description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
-        required: false
-        type: string
-        default: 'sunnypilot/sunnypilot-models'
       set_min_version:
         description: 'Minimum selector version'
         required: false
@@ -106,20 +101,15 @@ on:
         default: 'qcom'
         options:
           - qcom
-          - chestnut
+          - usbgpu
       hf_repo:
         description: 'Hugging Face dataset repository'
         required: false
         type: string
         default: 'sunnypilot/sunnypilot_models_v1'
-      docs_repo:
-        description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
-        required: false
-        type: string
-        default: 'sunnypilot/sunnypilot-models'
 env:
   RECOMPILED_DIR: recompiled${{ inputs.recompiled_dir }}
-  JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_v' || 'v' }}${{ inputs.json_version }}.json
+  JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'usbgpu' && 'usbgpu_v' || 'v' }}${{ inputs.json_version }}.json
 
 jobs:
   build_model:
@@ -146,7 +136,7 @@ jobs:
       - name: Checkout docs repo
         uses: actions/checkout@v4
         with:
-          repository: ${{ inputs.docs_repo }}
+          repository: sunnypilot/sunnypilot-models
           ref: gh-pages
           path: docs
           ssh-key: ${{ secrets.CI_SUNNYPILOT_DOCS_PRIVATE_KEY }}
@@ -156,7 +146,7 @@ jobs:
 
       - name: Validate hf_repo and JSON version
         env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
         run: |
           if [ ! -f "$JSON_FILE" ]; then
             echo "JSON file $JSON_FILE does not exist!"
@@ -165,8 +155,13 @@ jobs:
           python3 -c "
           import sys
           from huggingface_hub import HfApi
-          HfApi().repo_info(repo_id=sys.argv[1], repo_type='dataset')
-          print(f'Success: Repo {sys.argv[1]} exists.')
+          try:
+              api = HfApi()
+              api.repo_info(repo_id=sys.argv[1], repo_type='dataset')
+              print(f'Success: Repo {sys.argv[1]} exists.')
+          except Exception as e:
+              print('HF validation failed:', e)
+              sys.exit(1)
           " "${{ inputs.hf_repo }}"
 
       - name: Download artifact name file
@@ -197,7 +192,7 @@ jobs:
 
       - name: Upload to Hugging Face
         env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
           ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
         run: |
           hf upload ${{ inputs.hf_repo }} \

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

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

.github/workflows/docs.yaml

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

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

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

.github/workflows/release-drafter.yml

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

.github/workflows/release.yaml

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

.github/workflows/repo-maintenance.yaml

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

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

@@ -31,7 +31,7 @@ on:
         type: string
         default: ''
       target_hardware:
-        description: 'Hardware target to compile for (qcom or chestnut)'
+        description: 'Hardware target to compile for (qcom or usbgpu)'
         required: false
         type: string
         default: 'qcom'
@@ -57,7 +57,7 @@ on:
         type: choice
         options:
           - qcom
-          - chestnut
+          - usbgpu
         default: 'qcom'
 
 
@@ -102,28 +102,26 @@ jobs:
           cat $GITHUB_OUTPUT
       - run: |
           cd ${{ github.workspace }}/openpilot/openpilot
-          if [ "${{ inputs.target_hardware }}" != "chestnut" ]; then
-            git lfs pull -X "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/dmonitoring_*.onnx,**/selfdrive/modeld/models/big_*.pkl,**/selfdrive/modeld/models/dmonitoring_*.pkl"
-            rm -f selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/dmonitoring_*.onnx selfdrive/modeld/models/big_*.pkl selfdrive/modeld/models/dmonitoring_*.pkl
+          if [ "${{ inputs.target_hardware }}" != "usbgpu" ]; 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
-            git lfs pull -I "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/big_*.pkl" -X ""
-            find selfdrive/modeld/models -type f \( -name "*.onnx" -o -name "*.pkl" \) ! -name "big_*.onnx" ! -name "big_*.pkl" -delete
+            git lfs pull -I "**/selfdrive/modeld/models/big_*.onnx" -X ""
+            find selfdrive/modeld/models -name "*.onnx" ! -name "big_*.onnx" -delete
           fi
-          if grep -lIF "version https://git-lfs.github.com/spec/v1" selfdrive/modeld/models/*.onnx selfdrive/modeld/models/*.pkl 2>/dev/null; then
-            echo "::error::the ONNX or PKL files above are still LFS pointers, not real models"
+          if grep -lIF "version https://git-lfs.github.com/spec/v1" selfdrive/modeld/models/*.onnx; then
+            echo "::error::the ONNX files above are still LFS pointers, not real models"
             exit 1
           fi
       - name: 'Upload Artifact'
         uses: actions/upload-artifact@v4
         with:
           name: models-${{ env.REF }}${{ inputs.artifact_suffix  }}
-          path: |
-            ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
-            ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.pkl
+          path: ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
           if-no-files-found: error
 
   build_model:
-    runs-on: [self-hosted, "${{ inputs.target_hardware == 'chestnut' && 'chestnut' || 'tici' }}"]
+    runs-on: [self-hosted, usbgpu]
     needs: get_model
     env:
       MODEL_NAME: ${{ inputs.custom_name || inputs.upstream_branch }} (${{ needs.get_model.outputs.model_date }})
@@ -187,10 +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 [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
-            echo "CHESTNUT build"
-            export CHESTNUT=1
-            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1"
+          if [ "${{ 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"
             OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
           else
             echo "QCOM build"
@@ -198,75 +196,64 @@ jobs:
             OUTPUT_PKL="${{ env.MODELS_DIR }}/driving_tinygrad.pkl"
           fi
 
-          NATIVE_PKL=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "*.pkl" -print -quit)
+          # Generate metadata for all ONNX files
+          find "${{ env.MODELS_DIR }}" -maxdepth 1 -name '*.onnx' | while IFS= read -r onnx_file; do
+            echo "Generating metadata: $onnx_file"
+            env ${TG_FLAGS_QCOM} python3 "${{ env.MODELS_DIR }}/../get_model_metadata.py" "$onnx_file" || true
+          done
 
-          if [ -n "$NATIVE_PKL" ]; then
-            echo "Found native precompiled pkl: $NATIVE_PKL"
-            if [ "$NATIVE_PKL" != "$OUTPUT_PKL" ]; then
-              mv "$NATIVE_PKL" "$OUTPUT_PKL"
+          # Detect model type and build compile args
+          VISION_ONNX=""
+          for f in "${{ env.MODELS_DIR }}/driving_vision.onnx" "${{ env.MODELS_DIR }}/big_driving_vision.onnx"; do
+            [ -f "$f" ] && VISION_ONNX="$f" && break
+          done
+
+          POLICY_ONNX=""
+          for f in "${{ env.MODELS_DIR }}/driving_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_policy.onnx"; do
+            [ -f "$f" ] && POLICY_ONNX="$f" && break
+          done
+
+          OFF_POLICY_ONNX=""
+          for f in "${{ env.MODELS_DIR }}/driving_off_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_off_policy.onnx"; do
+            [ -f "$f" ] && OFF_POLICY_ONNX="$f" && break
+          done
+
+          ON_POLICY_ONNX=""
+          for f in "${{ env.MODELS_DIR }}/driving_on_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_on_policy.onnx"; do
+            [ -f "$f" ] && ON_POLICY_ONNX="$f" && break
+          done
+
+          SUPERCOMBO_ONNX=""
+          for f in "${{ env.MODELS_DIR }}/supercombo.onnx" "${{ env.MODELS_DIR }}/driving_supercombo.onnx" "${{ env.MODELS_DIR }}/big_supercombo.onnx" "${{ env.MODELS_DIR }}/big_driving_supercombo.onnx"; do
+            [ -f "$f" ] && SUPERCOMBO_ONNX="$f" && break
+          done
+
+          MODEL_TYPE="" ONNX_ARGS="" OUTPUT_NAME=""
+          if [ -f "$VISION_ONNX" ]; then
+            ONNX_ARGS="--vision-onnx $VISION_ONNX"
+            if [ -f "$ON_POLICY_ONNX" ] && [ -f "$OFF_POLICY_ONNX" ]; then
+              MODEL_TYPE=vision_multi_policy
+              ONNX_ARGS="$ONNX_ARGS --off-policy-onnx $OFF_POLICY_ONNX --on-policy-onnx $ON_POLICY_ONNX"
+            elif [ -f "$OFF_POLICY_ONNX" ] && [ -f "$POLICY_ONNX" ]; then
+              MODEL_TYPE=vision_multi_policy
+              ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX --off-policy-onnx $OFF_POLICY_ONNX"
+            elif [ -f "$POLICY_ONNX" ]; then
+              MODEL_TYPE=vision_policy
+              ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX"
             fi
-            echo "Chunking pkl"
-            python3 -c "from openpilot.common.file_chunker import chunk_file, get_chunk_targets; import os; p='$OUTPUT_PKL'; chunk_file(p, get_chunk_targets(p, os.path.getsize(p)))"
-          else
-            # Generate metadata for all ONNX files
-            find "${{ env.MODELS_DIR }}" -maxdepth 1 -name '*.onnx' | while IFS= read -r onnx_file; do
-              echo "Generating metadata: $onnx_file"
-              env ${TG_FLAGS_QCOM} python3 "${{ env.MODELS_DIR }}/../get_model_metadata.py" "$onnx_file" || true
-            done
+          elif [ -f "$SUPERCOMBO_ONNX" ]; then
+            MODEL_TYPE=supercombo
+            ONNX_ARGS="--supercombo-onnx $SUPERCOMBO_ONNX"
+          fi
 
-            # Detect model type and build compile args
-            VISION_ONNX=""
-            for f in "${{ env.MODELS_DIR }}/driving_vision.onnx" "${{ env.MODELS_DIR }}/big_driving_vision.onnx"; do
-              [ -f "$f" ] && VISION_ONNX="$f" && break
-            done
-
-            POLICY_ONNX=""
-            for f in "${{ env.MODELS_DIR }}/driving_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_policy.onnx"; do
-              [ -f "$f" ] && POLICY_ONNX="$f" && break
-            done
-
-            OFF_POLICY_ONNX=""
-            for f in "${{ env.MODELS_DIR }}/driving_off_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_off_policy.onnx"; do
-              [ -f "$f" ] && OFF_POLICY_ONNX="$f" && break
-            done
-
-            ON_POLICY_ONNX=""
-            for f in "${{ env.MODELS_DIR }}/driving_on_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_on_policy.onnx"; do
-              [ -f "$f" ] && ON_POLICY_ONNX="$f" && break
-            done
-
-            SUPERCOMBO_ONNX=""
-            for f in "${{ env.MODELS_DIR }}/supercombo.onnx" "${{ env.MODELS_DIR }}/driving_supercombo.onnx" "${{ env.MODELS_DIR }}/big_supercombo.onnx" "${{ env.MODELS_DIR }}/big_driving_supercombo.onnx"; do
-              [ -f "$f" ] && SUPERCOMBO_ONNX="$f" && break
-            done
-
-            MODEL_TYPE="" ONNX_ARGS="" OUTPUT_NAME=""
-            if [ -f "$VISION_ONNX" ]; then
-              ONNX_ARGS="--vision-onnx $VISION_ONNX"
-              if [ -f "$ON_POLICY_ONNX" ] && [ -f "$OFF_POLICY_ONNX" ]; then
-                MODEL_TYPE=vision_multi_policy
-                ONNX_ARGS="$ONNX_ARGS --off-policy-onnx $OFF_POLICY_ONNX --on-policy-onnx $ON_POLICY_ONNX"
-              elif [ -f "$OFF_POLICY_ONNX" ] && [ -f "$POLICY_ONNX" ]; then
-                MODEL_TYPE=vision_multi_policy
-                ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX --off-policy-onnx $OFF_POLICY_ONNX"
-              elif [ -f "$POLICY_ONNX" ]; then
-                MODEL_TYPE=vision_policy
-                ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX"
-              fi
-            elif [ -f "$SUPERCOMBO_ONNX" ]; then
-              MODEL_TYPE=supercombo
-              ONNX_ARGS="--supercombo-onnx $SUPERCOMBO_ONNX"
-            fi
-
-            if [ -n "$MODEL_TYPE" ]; then
-              echo "Detected: $MODEL_TYPE -> $OUTPUT_PKL"
-              env ${TG_FLAGS} python3 "$COMPILE_MODELD" \
-                --model-type $MODEL_TYPE \
-                --model-size $MODEL_SIZE \
-                --camera-resolutions $CAMERA_RES \
-                $ONNX_ARGS \
-                --output "$OUTPUT_PKL"
-            fi
+          if [ -n "$MODEL_TYPE" ]; then
+            echo "Detected: $MODEL_TYPE -> $OUTPUT_PKL"
+            env ${TG_FLAGS} python3 "$COMPILE_MODELD" \
+              --model-type $MODEL_TYPE \
+              --model-size $MODEL_SIZE \
+              --camera-resolutions $CAMERA_RES \
+              $ONNX_ARGS \
+              --output "$OUTPUT_PKL"
           fi
 
       - name: Prepare Output

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

@@ -39,8 +39,6 @@ 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: |
@@ -98,8 +96,6 @@ 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:
@@ -123,7 +119,6 @@ jobs:
     steps:
       - uses: actions/checkout@v4
         with:
-          fetch-depth: 1
           submodules: recursive
           ref: ${{ env.SOURCE_BRANCH }}
           repository: ${{ github.event.pull_request.head.repo.fork && github.event.pull_request.head.repo.full_name || github.repository }}
@@ -170,10 +165,7 @@ jobs:
           scons -j1 cache_dir="$SCONS_CACHE" --minimal \
             openpilot/selfdrive/locationd openpilot/sunnypilot/selfdrive/locationd
           echo "Building rest of sunnypilot"
-          sudo rm -rf /tmp/* || true
-          mkdir -p "$BUILD_DIR/tmp"
-          export TMPDIR="$BUILD_DIR/tmp"
-          SKIP_TINYGRAD_COMPILE=1 /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
+          /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}
@@ -219,245 +211,91 @@ 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:
-      - name: Resolve tinygrad ref via API
+      - uses: actions/checkout@v4
+        with:
+          ref: ${{ github.head_ref || github.ref_name }}
+
+      - run: git lfs pull -I "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
+
+      - name: Check HF defaults and build if needed
         id: resolve
         run: |
-          REF="${{ github.head_ref || github.ref_name }}"
-
-          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl?ref=${REF}" --jq '.sha')
-          [ -n "$BLOB_SHA" ] || { echo "::error::Failed to resolve big_driving_tinygrad.pkl blob SHA"; exit 1; }
-          ONNX_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          echo "big PKL hash: $ONNX_HASH"
-          [ -n "$ONNX_HASH" ] || { echo "::error::Failed to extract big PKL hash"; exit 1; }
-
-          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
-          echo "tinygrad ref: $TINYGRAD_REF"
+          ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
+          echo "Repo ONNX hash: $ACTUAL_ONNX_HASH"
 
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
-          check_defaults() {
-            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
-            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
-            [ "$TINYGRAD_MATCH" = "true" ] || return 1
-            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+          check_hash() {
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
+            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ACTUAL_ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
             [ -n "$BUNDLE" ] && [ "$BUNDLE" != "null" ]
           }
 
-          if check_defaults; then
-            echo "HF defaults match repo tinygrad ref"
-            exit 0
-          fi
+          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 "No matching model on HF — dispatching build"
-          gh workflow run build-default-models.yaml --ref "$REF" -f target=big
-          sleep 10
+            echo "Waiting for build to start..."
+            sleep 120
 
-          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
+            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
-          done
 
-          echo "::error::Build run did not complete within 45 minutes"
-          exit 1
+            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
+          fi
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Cancel run on failure
-        if: failure()
-        run: gh run cancel ${{ github.run_id }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-
-  prepare_small_model:
-    needs: [ prepare_strategy ]
-    runs-on: ubuntu-24.04
-    concurrency:
-      group: prepare-small-model
-      cancel-in-progress: false
-    outputs:
-      driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
-    env:
-      GH_REPO: ${{ github.repository }}
-      HF_REPO: sunnypilot/sunnypilot_models_v1
-      HF_DEFAULTS_PATH: models/defaults/small
-    steps:
-      - name: Resolve tinygrad ref via API
-        id: resolve
+      - name: Download big model chunks
         run: |
-          REF="${{ github.head_ref || github.ref_name }}"
-
-          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.sha')
-          DRIVING_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          echo "Driving ONNX hash: $DRIVING_HASH"
-          [ -n "$DRIVING_HASH" ] || { echo "::error::Failed to extract driving ONNX hash"; exit 1; }
-          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: $TINYGRAD_REF"
-
+          ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
           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)')
 
-          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" ] && [ "$DRIVING" != "null" ] || return 1
-          }
+          mkdir -p big_model_chunks
+          ARTIFACT=$(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')
 
-          if check_defaults; then
-            echo "HF defaults match repo tinygrad ref"
-            exit 0
-          fi
-
-          echo "No matching model on HF — dispatching build"
-          gh workflow run build-default-models.yaml --ref "$REF" -f target=small
-          sleep 10
-
-          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
-          echo "Dispatched build run: $BUILD_RUN_ID"
-
-          echo "Waiting for build run to complete..."
-          for i in $(seq 1 60); do
-            sleep 30
-            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
-            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
-            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
-            if [ "$STATUS" = "completed" ]; then
-              if [ "$CONCLUSION" = "success" ]; then
-                echo "Build run succeeded, verifying HF..."
-                sleep 10
-                if check_defaults; then
-                  echo "Small model verified on HF"
-                  exit 0
-                fi
-                echo "::error::Build succeeded but model not found on HF"
-                exit 1
-              else
-                echo "::error::Build run failed with conclusion=$CONCLUSION"
-                exit 1
-              fi
-            fi
+          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"
           done
 
-          echo "::error::Small model build did not complete within 30 minutes"
-          exit 1
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          echo "$NUM_CHUNKS" > "big_model_chunks/${CANONICAL}.chunkmanifest"
 
-      - name: Cancel run on failure
-        if: failure()
-        run: gh run cancel ${{ github.run_id }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-
-  prepare_dm_model:
-    needs: [ prepare_strategy ]
-    runs-on: ubuntu-24.04
-    concurrency:
-      group: prepare-dm-model
-      cancel-in-progress: false
-    outputs:
-      dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
-    env:
-      GH_REPO: ${{ github.repository }}
-      HF_REPO: sunnypilot/sunnypilot_models_v1
-      HF_DEFAULTS_PATH: models/defaults/dm
-    steps:
-      - name: Resolve tinygrad ref via API
-        id: resolve
-        run: |
-          REF="${{ github.head_ref || github.ref_name }}"
-
-          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.sha')
-          DM_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          echo "DM ONNX hash: $DM_HASH"
-          [ -n "$DM_HASH" ] || { echo "::error::Failed to extract DM ONNX hash"; exit 1; }
-          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" ] && [ "$DM" != "null" ] || return 1
-          }
-
-          if check_defaults; then
-            echo "HF defaults match DM tinygrad ref"
-            exit 0
-          fi
-
-          echo "No matching DM model on HF — dispatching build"
-          gh workflow run build-default-models.yaml --ref "$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: 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()
@@ -467,24 +305,23 @@ 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, prepare_small_model, prepare_dm_model ]
+    needs: [ build, prepare_strategy, prepare_chestnut ]
     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
@@ -496,16 +333,23 @@ jobs:
           mkdir -p ${{ env.OUTPUT_DIR }}
           tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
 
-      - name: Download model chunks from HF
-        uses: ./.github/workflows/download-hf-model-chunks
+      - 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
         with:
-          hf_repo: sunnypilot/sunnypilot_models_v1
-          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
-          models: |
-            [
-              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
-              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"}
-            ]
+          name: 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/"
 
       - name: Configure Git
         run: |
@@ -527,6 +371,22 @@ 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: |
@@ -534,77 +394,12 @@ 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'
@@ -612,8 +407,6 @@ 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

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

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

.github/workflows/test_models.yml

@@ -1,85 +0,0 @@
-name: Test Models Compatibility With Tinygrad Changes
-on:
-  pull_request:
-    paths:
-      - 'tinygrad_repo'
-  workflow_dispatch:
-
-jobs:
-  generate-matrix:
-    runs-on: ubuntu-latest
-    outputs:
-      models: ${{ steps.set-matrix.outputs.models }}
-    steps:
-      - uses: actions/checkout@v4
-      - name: Fetch and Parse json
-        id: set-matrix
-        run: |
-          python3 -c '
-          import json, urllib.request, os, re
-
-          with open("openpilot/sunnypilot/models/fetcher.py", "r") as f:
-            urls = re.findall(r"MODEL_URL(?:_CHESTNUT)?\s*=\s*[\"'"'"']([^\"'"'"']+)[\"'"'"']", f.read())
-
-          artifacts = []
-          for url in urls:
-            data = json.loads(urllib.request.urlopen(url).read())
-            for bundle in data.get("bundles", []):
-              for model in bundle.get("models", []):
-                if "artifact" in model:
-                  artifacts.append(model["artifact"])
-
-          with open(os.environ["GITHUB_OUTPUT"], "a") as f:
-            f.write(f"models={json.dumps(artifacts)}\n")
-          '
-
-  test-model:
-    name: Test ${{ matrix.artifact.file_name }}
-    needs: generate-matrix
-    runs-on: ubuntu-latest
-    container: ghcr.io/commaai/openpilot-base:latest
-    strategy:
-      fail-fast: false
-      matrix:
-        artifact: ${{ fromJson(needs.generate-matrix.outputs.models) }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: true
-
-      - name: Download Model Chunks in Parallel
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
-        run: |
-          mkdir -p /tmp/model_chunks
-          echo '${{ toJson(matrix.artifact.chunks) }}' > chunks.json
-
-          BASE_URL="${{ matrix.artifact.download_uri.url }}"
-          export BASE_DIR=$(dirname "$BASE_URL")
-
-          python3 -c '
-          import json, os
-          with open("chunks.json") as f:
-            chunks = json.load(f)
-          manifest_path = f"/tmp/model_chunks/${{ matrix.artifact.file_name }}.chunkmanifest"
-          with open(manifest_path, "w") as f:
-            f.write(str(len(chunks)))
-          base_dir = os.environ["BASE_DIR"]
-          hf_token = os.environ.get("HF_TOKEN", "")
-          with open("/tmp/curl_config.txt", "w") as f:
-            for c in chunks:
-              fn = c["file_name"]
-              f.write(f"url = \"{base_dir}/{fn}\"\noutput = \"/tmp/model_chunks/{fn}\"\n")
-              if hf_token:
-                f.write(f"header = \"Authorization: Bearer {hf_token}\"\n")
-          '
-          curl -Z --parallel-immediate --parallel-max 12 --retry 3 --retry-all-errors -s -S -f -L -K /tmp/curl_config.txt
-
-      - name: Run Model Compatibility Test
-        env:
-          MODEL_BASE_NAME: ${{ matrix.artifact.file_name }}
-          MODEL_CHUNK_DIR: "/tmp/model_chunks"
-        run: |
-          export PYTHONPATH="$GITHUB_WORKSPACE:$GITHUB_WORKSPACE/tinygrad_repo"
-          pip uninstall -y tinygrad || true
-          python3 -m pytest openpilot/sunnypilot/modeld_v2/tests/test_models.py

.github/workflows/tests.yaml

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

.gitignore

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

.gitmodules

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

.lfsconfig

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

Jenkinsfile

@@ -12,17 +12,16 @@ def retryWithDelay(int maxRetries, int delay, Closure body) {
 def device(String ip, String step_label, String cmd) {
   withCredentials([file(credentialsId: 'id_rsa', variable: 'key_file')]) {
     def ssh_cmd = """
-ssh -o ControlMaster=no -o ControlPath=none -o ConnectTimeout=5 -o ServerAliveInterval=5 -o ServerAliveCountMax=12 -o BatchMode=yes -o StrictHostKeyChecking=no -i ${key_file} 'comma@${ip}' exec setpriv --pdeathsig HUP /usr/bin/bash <<'END'
+ssh -o ControlMaster=auto -o ControlPath=/tmp/ssh_control_%C -o ControlPersist=yes -o ConnectTimeout=5 -o ServerAliveInterval=5 -o ServerAliveCountMax=2 -o BatchMode=yes -o StrictHostKeyChecking=no -i ${key_file} 'comma@${ip}' exec /usr/bin/bash <<'END'
 
 set -e
 
 export TERM=xterm-256color
 
-trap 'kill 0' HUP # stop this process group on SSH disconnect
+shopt -s huponexit # kill all child processes when the shell exits
 
 export CI=1
 export PYTHONWARNINGS=error
-export PYTHONFAULTHANDLER=1
 export COMMA_CACHE=/data/tmp/comma_download_cache
 #export LOGPRINT=debug # this has gotten too spammy...
 export TEST_DIR=${env.TEST_DIR}
@@ -70,8 +69,7 @@ export LD_LIBRARY_PATH="\$(python -c 'import ffmpeg; print(ffmpeg.LIB_DIR)'):/us
 ln -snf ${env.TEST_DIR} /data/pythonpath
 
 cd ${env.TEST_DIR} || true
-time ( ${cmd} ) &
-wait \$!
+time ${cmd}
 END"""
 
     sh script: ssh_cmd, label: step_label
@@ -171,7 +169,7 @@ node {
   env.GIT_BRANCH = checkout(scm).GIT_BRANCH
   env.GIT_COMMIT = checkout(scm).GIT_COMMIT
 
-  def excludeBranches = ['__nightly', '__nightly-chestnut', 'devel', 'devel-staging',
+  def excludeBranches = ['__nightly', 'devel', 'devel-staging',
                          'release-tizi', 'release-tizi-staging', 'release-mici', 'release-mici-staging', 'testing-closet*', 'hotfix-*']
   def excludeRegex = excludeBranches.join('|').replaceAll('\\*', '.*')
 
@@ -203,12 +201,6 @@ node {
       )
     }
 
-    if (env.BRANCH_NAME == '__nightly-chestnut') {
-      deviceStage("build nightly-chestnut", "mici-chestnut-ci", [], [
-        step("build nightly-chestnut", "SCONSFLAGS=-j4 INCLUDE_BIG_MODEL=1 PANDA_DEBUG_BUILD=1 RELEASE_BRANCH=nightly-chestnut $SOURCE_DIR/tools/release/build_release.sh TestChestnutOnroad"),
-      ])
-    }
-
     if (!env.BRANCH_NAME.matches(excludeRegex)) {
     parallel (
       'onroad tests': {
@@ -260,14 +252,6 @@ node {
           step("test amp", "./openpilot/common/hardware/comma/tests/test_amplifier.py"),
         ])
       },
-      'chestnut': {
-        deviceStage("chestnut", "mici-chestnut-ci", ["UNSAFE=1", "CHESTNUT=1"], [
-          step("build", "./openpilot/selfdrive/test/chestnut.sh"),
-          step("model replay", "openpilot/selfdrive/test/process_replay/model_replay.py --chestnut"),
-          step("onroad tests", "./openpilot/selfdrive/test/test_onroad.py TestChestnutOnroad", [timeout: 120]),
-          step("test power draw", "./openpilot/selfdrive/test/test_power_draw.py"),
-        ])
-      },
 
     )
     }

SConstruct

@@ -87,6 +87,7 @@ acados_include_dirs = [
 # vendored in commaai/dependencies.
 allowed_system_libs = {
   "EGL", "GLESv2", "GL",
+  "Qt5Charts", "Qt5Core", "Qt5Gui", "Qt5Widgets",
   "dl", "drm", "gbm", "m", "pthread",
 }
 
@@ -120,7 +121,6 @@ def _libflags(target, source, env, for_signature):
 env = Environment(
   ENV={
     "PATH": os.environ['PATH'],
-    "TMPDIR": os.environ.get('TMPDIR', '/tmp'),
     "PYTHONPATH": os.pathsep.join(submodule_python_paths),
     "ACADOS_SOURCE_DIR": acados.DIR,
     "ACADOS_PYTHON_INTERFACE_PATH": acados.TEMPLATE_DIR,
@@ -346,8 +346,6 @@ AddPostAction(BUILD_TARGETS or [Dir('.')], prune_cache_dir)
 def check_build_product_size(target, source, env):
   limit = 50 * 1024 * 1024  # GitHub max size
   for t in target:
-    if str(t).endswith('.pkl'):  # chunked during release packaging
-      continue
     if hasattr(t, 'isfile') and t.isfile() and (size := os.path.getsize(t.abspath)) > limit:
       raise SCons.Errors.UserError(f"{t} is {size / (1024 * 1024):.1f} MiB, exceeding the {limit / (1024 * 1024):.1f} MiB limit")
 if not GetOption('extras'):

docs/CARS.md

@@ -34,7 +34,7 @@ A supported vehicle is one that just works when you install a comma device. All
 |Chrysler|Pacifica Hybrid 2019-25|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Chrysler Pacifica Hybrid 2019-25">Buy Here</a></sub></details>|||
 |comma|body|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|None|<a href="https://youtu.be/VT-i3yRsX2s?t=2736" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
 |CUPRA[<sup>12</sup>](#footnotes)|Ateca 2018-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=CUPRA Ateca 2018-23">Buy Here</a></sub></details>|||
-|CUPRA|Born 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=CUPRA Born 2021-23">Buy Here</a></sub></details>|||
+|CUPRA[<sup>12</sup>](#footnotes)|Born 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=CUPRA Born 2021-23">Buy Here</a></sub></details>|||
 |Dodge|Durango 2020-21|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Dodge Durango 2020-21">Buy Here</a></sub></details>|||
 |Ford|Bronco Sport 2021-24|Co-Pilot360 Assist+|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Ford Q3 connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Ford Bronco Sport 2021-24">Buy Here</a></sub></details>|||
 |Ford|Escape 2020-22|Co-Pilot360 Assist+|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Ford Q3 connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Ford Escape 2020-22">Buy Here</a></sub></details>|||
@@ -99,7 +99,7 @@ A supported vehicle is one that just works when you install a comma device. All
 |Honda|Fit 2018-20|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Fit 2018-20">Buy Here</a></sub></details>|||
 |Honda|Freed 2020|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Freed 2020">Buy Here</a></sub></details>|||
 |Honda|HR-V 2019-22|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2019-22">Buy Here</a></sub></details>|||
-|Honda|HR-V 2023-27|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2023-27">Buy Here</a></sub></details>|||
+|Honda|HR-V 2023-25|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2023-25">Buy Here</a></sub></details>|||
 |Honda|Insight 2019-22|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|3 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Insight 2019-22">Buy Here</a></sub></details>|||
 |Honda|Inspire 2018|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|3 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Inspire 2018">Buy Here</a></sub></details>|||
 |Honda|N-Box 2018|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|11 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda N-Box 2018">Buy Here</a></sub></details>|||
@@ -268,8 +268,8 @@ A supported vehicle is one that just works when you install a comma device. All
 |Škoda[<sup>12</sup>](#footnotes)|Superb 2015-22[<sup>15</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Škoda Superb 2015-22">Buy Here</a></sub></details>|||
 |Tesla[<sup>10</sup>](#footnotes)|Model 3 (with HW3) 2019-23[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model 3 (with HW3) 2019-23">Buy Here</a></sub></details>|||
 |Tesla[<sup>10</sup>](#footnotes)|Model 3 (with HW4) 2024-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model 3 (with HW4) 2024-25">Buy Here</a></sub></details>|||
-|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW3) 2020-24[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW3) 2020-24">Buy Here</a></sub></details>|||
-|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW4) 2023-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW4) 2023-25">Buy Here</a></sub></details>|||
+|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW3) 2020-23[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW3) 2020-23">Buy Here</a></sub></details>|||
+|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW4) 2024-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW4) 2024-25">Buy Here</a></sub></details>|||
 |Toyota|Alphard 2019-20|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Alphard 2019-20">Buy Here</a></sub></details>|||
 |Toyota|Alphard Hybrid 2021|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Alphard Hybrid 2021">Buy Here</a></sub></details>|||
 |Toyota|Avalon 2016|Toyota Safety Sense P|Stock|19 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Avalon 2016">Buy Here</a></sub></details>|||
@@ -335,8 +335,8 @@ A supported vehicle is one that just works when you install a comma device. All
 |Volkswagen[<sup>12</sup>](#footnotes)|Golf R 2015-19|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Golf R 2015-19">Buy Here</a></sub></details>|||
 |Volkswagen[<sup>12</sup>](#footnotes)|Golf SportsVan 2015-20|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Golf SportsVan 2015-20">Buy Here</a></sub></details>|||
 |Volkswagen[<sup>12</sup>](#footnotes)|Grand California 2019-24|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|31 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Grand California 2019-24">Buy Here</a></sub></details>|<a href="https://youtu.be/4100gLeabmo" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
-|Volkswagen|ID.4 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2021-23">Buy Here</a></sub></details>|||
-|Volkswagen|ID.4 2024-25|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2024-25">Buy Here</a></sub></details>|||
+|Volkswagen[<sup>12</sup>](#footnotes)|ID.4 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2021-23">Buy Here</a></sub></details>|||
+|Volkswagen[<sup>12</sup>](#footnotes)|ID.4 2024-25|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2024-25">Buy Here</a></sub></details>|||
 |Volkswagen[<sup>12</sup>](#footnotes)|Jetta 2019-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Jetta 2019-23">Buy Here</a></sub></details>|||
 |Volkswagen[<sup>12</sup>](#footnotes)|Jetta GLI 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Jetta GLI 2021-23">Buy Here</a></sub></details>|||
 |Volkswagen|Passat 2015-22[<sup>14</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Passat 2015-22">Buy Here</a></sub></details>|||
@@ -363,7 +363,7 @@ A supported vehicle is one that just works when you install a comma device. All
 <sup>6</sup>See more setup details for <a href="https://github.com/commaai/openpilot/wiki/nissan" target="_blank">Nissan</a>. <br />
 <sup>7</sup>In the non-US market, openpilot requires the car to come equipped with EyeSight with Lane Keep Assistance. <br />
 <sup>8</sup>Enabling longitudinal control (alpha) will disable all EyeSight functionality, including AEB, LDW, and RAB. <br />
-<sup>9</sup>Model years 2023 and 2024 can have either hardware type, depending on build date and factory. To check which hardware type your vehicle has, look for <b>Autopilot computer</b> under <b>Software -> Additional Vehicle Information</b> on your vehicle's touchscreen. See <a href="https://www.notateslaapp.com/news/2173/how-to-check-if-your-tesla-has-hardware-4-ai4-or-hardware-3">this page</a> for more information. <br />
+<sup>9</sup>Some 2023 model years have HW4. To check which hardware type your vehicle has, look for <b>Autopilot computer</b> under <b>Software -> Additional Vehicle Information</b> on your vehicle's touchscreen. See <a href="https://www.notateslaapp.com/news/2173/how-to-check-if-your-tesla-has-hardware-4-ai4-or-hardware-3">this page</a> for more information. <br />
 <sup>10</sup>See more setup details for <a href="https://github.com/commaai/openpilot/wiki/tesla" target="_blank">Tesla</a>. <br />
 <sup>11</sup>openpilot operates above 28mph for Camry 4CYL L, 4CYL LE and 4CYL SE which don't have Full-Speed Range Dynamic Radar Cruise Control. <br />
 <sup>12</sup>The J533 harness plugs in at the CAN gateway under the dashboard, just above the steering column. More information can be found at <a href="https://docs.howtocomma.com/docs/j533-harness-install" target="_blank">this guide</a>. <br />

docs/README.md

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

launch_chffrplus.sh

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

launch_env.sh

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

openpilot/cereal/custom.capnp

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

openpilot/cereal/log.capnp

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

openpilot/cereal/services.py

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

openpilot/common/esim/base.py

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

openpilot/common/esim/lpa.py

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

openpilot/common/file_chunker.py

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

openpilot/common/hardware/base.py

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

openpilot/common/hardware/comma/agnos.json

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

openpilot/common/hardware/comma/modem.py

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

openpilot/common/hardware/comma/power_monitor.py

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

openpilot/common/hardware/comma/updater

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

openpilot/common/hardware/usb.py

@@ -4,17 +4,11 @@ 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))
@@ -87,7 +81,7 @@ def set_usb_state(device_state, devices: list[dict]) -> None:
     entry.linkErrorCount = device["linkErrorCount"]
     entry.usb3Lane = device.get("usb3Lane", "unknown")
 
-    if is_chestnut_usb_id(entry.vendorId, entry.productId):
+    if (entry.vendorId, entry.productId) in CHESTNUT_USB_IDS:
       chestnut_present = True
 
   device_state.chestnutPresent = chestnut_present

openpilot/common/params_keys.h

@@ -28,7 +28,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"ControlsReady", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"CurrentBootlog", {PERSISTENT, STRING}},
     {"CurrentRoute", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
-    {"DisableDriverCameraIR", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"DisableLogging", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
     {"DisablePowerDown", {PERSISTENT | BACKUP, BOOL}},
     {"DisableUpdates", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -60,7 +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 | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"IsLiveStreaming", {CLEAR_ON_MANAGER_START, BOOL}},
     {"IsMetric", {PERSISTENT | BACKUP, BOOL}},
     {"IsOffroad", {CLEAR_ON_MANAGER_START, BOOL}},
     {"IsRhdDetected", {PERSISTENT, BOOL}},
@@ -93,12 +92,6 @@ 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}},
@@ -137,8 +130,8 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"UpdaterLastFetchTime", {PERSISTENT, TIME}},
     {"UptimeOffroad", {PERSISTENT, FLOAT, "0.0"}},
     {"UptimeOnroad", {PERSISTENT, FLOAT, "0.0"}},
-    {"ChestnutActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
-    {"ChestnutLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"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}},
     {"Version", {PERSISTENT, STRING}},
 
     // --- sunnypilot params --- //
@@ -202,16 +195,14 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
 
     // Model Manager params
     {"ModelManager_ActiveBundle", {PERSISTENT, JSON}},
-    {"ModelManager_ActiveBundleUSBGPU", {PERSISTENT, JSON}}, //TODO-SP: kept for migration, remove on next sync?
-    {"ModelManager_ActiveBundleChestnut", {PERSISTENT, JSON}},
-    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, JSON}},
+    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, STRING}},
     {"ModelManager_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
-    {"ModelManager_DownloadRef", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
+    {"ModelManager_DownloadIndex", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, INT}},
     {"ModelManager_Favs", {PERSISTENT | BACKUP, STRING}},
     {"ModelManager_LastSyncTime", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
-    {"ModelManager_LastSyncTime_Chestnut", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
+    {"ModelManager_LastSyncTime_USBGPU", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
     {"ModelManager_ModelsCache", {PERSISTENT | BACKUP, JSON}},
-    {"ModelManager_ModelsCache_Chestnut", {PERSISTENT | BACKUP, JSON}},
+    {"ModelManager_ModelsCache_USBGPU", {PERSISTENT | BACKUP, JSON}},
 
     // Neural Network Lateral Control
     {"NeuralNetworkLateralControl", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -254,7 +245,6 @@ 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 -rf %s", real_path.c_str()));
+      util::check_system(util::string_format("rm %s -rf", real_path.c_str()));
       unlink(param_path.c_str());
     }
     if (getenv("COMMA_CACHE") == nullptr) {
-      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::download_cache_root().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()));
+    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()));
     unsetenv("OPENPILOT_PREFIX");
   }
 

openpilot/common/qrcode.py

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

openpilot/common/tests/test_qrcode.py

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

openpilot/selfdrive/assets/icons_mici/chestnut_orange.png

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

openpilot/selfdrive/assets/icons_mici/egpu_crossed.png

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

openpilot/selfdrive/assets/icons_mici/egpu_gray.png

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

openpilot/selfdrive/assets/icons_mici/egpu_orange.png

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

openpilot/selfdrive/assets/icons_mici/usb.png

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

openpilot/selfdrive/assets/prep-svg.sh

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

openpilot/selfdrive/car/card.py

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

openpilot/selfdrive/locationd/locationd.py

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

openpilot/selfdrive/modeld/SConscript

@@ -1,45 +1,94 @@
 import glob
+import json
 import os
 import time
 from SCons.Script import Action, Value
+from openpilot.common.file_chunker import chunk_file, get_chunk_targets, get_existing_chunks
 from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
 from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE, DM_INPUT_SIZE
-from openpilot.selfdrive.modeld.helpers import chestnut_present
-from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
+from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.selfdrive.modeld.helpers import TG_INPUT_DEVICES_PATH, usbgpu_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()
-lenv.PrependENVPath('PYTHONPATH', Dir('#tinygrad_repo').abspath)
 
 tinygrad_root = env.Dir("#").abspath
 tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=tinygrad_root)
                   if 'pycache' not in x and os.path.isfile(os.path.join(tinygrad_root, x))]
 
-camera_configs = [(c.width, c.height) for c in (_ar_ox_fisheye, _os_fisheye)]
+def estimate_pickle_max_size(onnx_size):
+  return 1.2 * onnx_size  + 10 * 1024 * 1024  # 20% + 10MB is plenty
 
 if arch == 'comma_arm64':
-  tg_flags = 'DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1'
+  tg_backend = 'QCOM'
+  tg_flags = f'DEV={tg_backend} IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1'
 else:
-  # JIT=2 disables graph batching, which produces incorrect outputs after buffers change.
-  tg_flags = 'DEV=METAL JIT=2' if arch == 'Darwin' else 'DEV=CPU:LLVM'
+  tg_backend = 'CPU'
+  tg_flags = f'DEV=CPU' if arch == 'Darwin' else 'DEV=CPU:LLVM'
 
-CHESTNUT = chestnut_present()
-if CHESTNUT:
-  chestnut_tg_flags = 'DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32'
+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'
   # the USB+AMD GPU takes an exclusive flock; serialize all targets that touch it
-  chestnut_lock = File("models/.chestnut.lock").abspath
+  usbgpu_lock = File("models/.usb_gpu.lock").abspath
+
+def write_tg_devices(target, source, env):
+  with open(str(target[0]), "w") as f:
+    json.dump(tg_devices, f)
+    f.write("\n")
+
+tg_devices_node = lenv.Command(
+  str(TG_INPUT_DEVICES_PATH),
+  [Value(tg_devices)],
+  write_tg_devices,
+)
 
 # tinygrad calls brew which needs a $HOME in the env
 mac_brew_string = f'HOME={os.path.expanduser("~")}' if arch == 'Darwin' else ''
 
-warp_deps = [File("#openpilot/system/camerad/cameras/nv12_info.py")]
-compiler = Dir('#tinygrad_repo/examples/openpilot').abspath
-# CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
-taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
+modeld_dir = Dir("#openpilot/selfdrive/modeld").abspath
+compile_modeld_script = [
+  File(f"{modeld_dir}/compile_modeld.py"),
+  File(f"{modeld_dir}/get_model_metadata.py"),
+  File("#openpilot/system/camerad/cameras/nv12_info.py"),
+  File("#openpilot/common/hardware/hw.py"),
+]
+model_w, model_h = MEDMODEL_INPUT_SIZE
+frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
 
-def chestnut_action(command):
-  def do_compile(target, source, env):
+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):
@@ -47,44 +96,50 @@ def chestnut_action(command):
         break
       time.sleep(1)
     else:
-      print("Chestnut not ready, skipping warp build")
+      print("Chestnut not ready, skipping big model build")
       return
-    return env.Execute(command)
-  return Action(do_compile, "  [CHESTNUT] $TARGET")
-
-def compile_model(onnx_path, pkl_path):
-  onnx_path, target_pkl_path = File(onnx_path).abspath, File(pkl_path).abspath
-  cmd = (f'{tg_flags} {mac_brew_string} {taskset}python3 "{compiler}/compile_onnx.py" '
-         f'"{onnx_path}" "{target_pkl_path}" --device-input "*" --out-of-band --benchmark-runs 1')
-  lenv.Command(
-    target_pkl_path,
-    tinygrad_files + [onnx_path, Value(cmd)],
-    Action(cmd, "  [ONNX] $TARGET"),
+    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)
 
-compile_model('models/dmonitoring_model.onnx', 'models/dmonitoring_model_tinygrad.pkl')
-compile_model('models/driving_supercombo.onnx', 'models/driving_tinygrad.pkl')
-
-model_w, model_h = MEDMODEL_INPUT_SIZE
-for chestnut in [False, True] if CHESTNUT else [False]:
-  file_prefix, cmd_flags = ('big_', chestnut_tg_flags) if chestnut else ('', tg_flags)
-  for cam_w, cam_h in camera_configs:
-    warp_pkl_path = File(f"models/{file_prefix}driving_warp_{cam_w}x{cam_h}_tinygrad.pkl").abspath
-    stride, y_height, uv_height, _ = get_nv12_info(cam_w, cam_h)
-    cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 "{compiler}/compile_warp.py" '
-           f'--frame {cam_w},{cam_h},{stride},{y_height},{uv_height},{stride * (y_height + uv_height)} '
-           f'--warp-to {model_w}x{model_h} --layout yuv420 --frames 2 '
-           f'--output {warp_pkl_path}')
-    action = chestnut_action(cmd) if chestnut else cmd
-    node = lenv.Command(warp_pkl_path, tinygrad_files + warp_deps + [Value(cmd)], action)
-    if chestnut:
-      lenv.SideEffect(chestnut_lock, node)
+# get model metadata
+fn = File(f"models/dmonitoring_model").abspath
+script_files = [File(Dir("#openpilot/selfdrive/modeld").File("get_model_metadata.py").abspath)]
+cmd = f'{tg_flags} {mac_brew_string} python3 {Dir("#openpilot/selfdrive/modeld").abspath}/get_model_metadata.py {fn}.onnx'
+lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files + script_files + [tg_devices_node], cmd)
 
 dm_w, dm_h = DM_INPUT_SIZE
-for cam_w, cam_h in camera_configs:
+compile_dm_warp_script = [File(f"{modeld_dir}/compile_dm_warp.py")]
+for cam_w, cam_h in CAMERA_CONFIGS:
   dm_pkl_path = File(f"models/dm_warp_{cam_w}x{cam_h}_tinygrad.pkl").abspath
-  stride, y_height, uv_height, frame_size = get_nv12_info(cam_w, cam_h)
-  cmd = (f'{tg_flags} {mac_brew_string} python3 "{compiler}/compile_warp.py" '
-         f'--frame {cam_w},{cam_h},{stride},{y_height},{uv_height},{frame_size} --warp-to {dm_w}x{dm_h} '
-         f'--layout luma --border-fill 16 --transform-device NPY --output {dm_pkl_path}')
-  lenv.Command(dm_pkl_path, tinygrad_files + warp_deps + [Value(cmd)], cmd)
+  cmd = (f'{tg_flags} {mac_brew_string} python3 {modeld_dir}/compile_dm_warp.py '
+         f'--camera-resolution {cam_w}x{cam_h} --warp-to {dm_w}x{dm_h} '
+         f'--output {dm_pkl_path}')
+  lenv.Command(dm_pkl_path, tinygrad_files + compile_dm_warp_script + compile_modeld_script + [tg_devices_node], cmd)
+
+def tg_compile(flags, model_name):
+  pythonpath_string = 'PYTHONPATH="${PYTHONPATH}:' + env.Dir("#tinygrad_repo").abspath + '"'
+  fn = File(f"models/{model_name}").abspath
+  pkl = fn + "_tinygrad.pkl"
+  onnx_path = fn + ".onnx"
+  chunk_targets = get_chunk_targets(pkl, estimate_pickle_max_size(os.path.getsize(onnx_path)))
+  def do_chunk(target, source, env):
+    chunk_file(pkl, chunk_targets)
+  return lenv.Command(
+    chunk_targets,
+    [onnx_path] + tinygrad_files + [Value(chunk_targets), chunker_file, tg_devices_node],
+    [f'{pythonpath_string} {flags} python3 {Dir("#tinygrad_repo").abspath}/examples/openpilot/compile3.py {fn}.onnx {pkl}',
+     Action(do_chunk, "  [CHUNK] $TARGET")],
+  )
+
+tg_compile(tg_flags, 'dmonitoring_model')

openpilot/selfdrive/modeld/compile_dm_warp.py

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

openpilot/selfdrive/modeld/compile_modeld.py

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

openpilot/selfdrive/modeld/dmonitoringmodeld.py

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

openpilot/selfdrive/modeld/fill_model_msg.py

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

openpilot/selfdrive/modeld/get_model_metadata.py

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

openpilot/selfdrive/modeld/helpers.py

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

openpilot/selfdrive/modeld/modeld.py

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

openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a501760a9d1d5fef0eab2b8c5d122d06124fc26dc8e0782e0aa94b82a208f0ff
+size 1757355221

openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl

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

openpilot/selfdrive/modeld/models/driving_supercombo.onnx

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

openpilot/selfdrive/pandad/__init__.py

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

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.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.setIgnitionLine(health.ignition_line_pkt);
+  ps.setIgnitionCan(health.ignition_can_pkt);
+  ps.setControlsAllowed(health.controls_allowed_pkt);
   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((health.flags_pkt & HEALTH_FLAG_POWER_SAVE_ENABLED) != 0U);
-  ps.setHeartbeatLost((health.flags_pkt & HEALTH_FLAG_HEARTBEAT_LOST) != 0U);
+  ps.setPowerSaveEnabled((bool)(health.power_save_enabled_pkt));
+  ps.setHeartbeatLost((bool)(health.heartbeat_lost_pkt));
   ps.setAlternativeExperience(health.alternative_experience_pkt);
   ps.setHarnessStatus(cereal::PandaState::HarnessStatus(health.car_harness_status_pkt));
-  ps.setInterruptLoad(health.interrupt_load_pkt / 255.0f);
+  ps.setInterruptLoad(health.interrupt_load_pkt);
   ps.setFanPower(health.fan_power);
-  ps.setSafetyRxChecksInvalid((health.flags_pkt & HEALTH_FLAG_SAFETY_RX_CHECKS_INVALID) != 0U);
+  ps.setSafetyRxChecksInvalid((bool)(health.safety_rx_checks_invalid_pkt));
   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.flags_pkt |= HEALTH_FLAG_IGNITION_LINE;
+    health.ignition_line_pkt = 1;
   }
 
-  bool ignition_local = ((health.flags_pkt & (HEALTH_FLAG_IGNITION_LINE | HEALTH_FLAG_IGNITION_CAN)) != 0U) && !always_offroad;
+  bool ignition_local = ((health.ignition_line_pkt != 0) || (health.ignition_can_pkt != 0)) && !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.flags_pkt & HEALTH_FLAG_POWER_SAVE_ENABLED) != 0U) != power_save_desired) {
+  if (health.power_save_enabled_pkt != power_save_desired) {
     panda->set_power_saving(power_save_desired);
   }
 
@@ -342,8 +342,8 @@ void process_peripheral_state(Panda *panda, PubMaster *pm, bool no_fan_control,
       }
     }
 
-    // Disable IR on input timeout or when requested offroad.
-    if (nanos_since_boot() - last_cabin_camera_t > 1e9 || (!is_onroad && params.getBool("DisableDriverCameraIR"))) {
+    // Disable IR on input timeout
+    if (nanos_since_boot() - last_cabin_camera_t > 1e9) {
       ir_pwr = 0;
     }
 

openpilot/selfdrive/selfdrived/alerts_offroad.json

@@ -19,30 +19,6 @@
   },
   "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

@@ -195,18 +195,17 @@ class SelfdriveD(CruiseHelper):
       self.events.add(EventName.joystickDebug)
       self.startup_event = None
 
-    loading = self.params.get_bool("ChestnutLoading")
+    loading = self.params.get_bool("UsbGpuLoading")
     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("ChestnutActive")
-    chestnut_present = self.sm['deviceState'].chestnutPresent
+    big_active = self.params.get("UsbGpuActive")
+    usbgpu_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 chestnut_present)
+    big_failed = big_active is False or model_unavailable or (self.big_model_active and not usbgpu_present)
     if big_failed and not self.big_model_failed:
       self.events.add(EventName.bigModelFailed)
     self.big_model_failed = big_failed
@@ -453,12 +452,11 @@ class SelfdriveD(CruiseHelper):
       self.logged_comm_issue = None
 
     if not self.CP.notCar and not big_model_settling:  # localization has nothing to work with during the load
-      # the defaults of a message that was never received are not a localizer failure
-      if self.sm.seen['deviceMotion'] and not self.sm['deviceMotion'].posenetOK:
+      if not self.sm['deviceMotion'].posenetOK:
         self.events.add(EventName.posenetInvalid)
-      if self.sm.seen['deviceMotion'] and not self.sm['deviceMotion'].inputsOK:
+      if not self.sm['deviceMotion'].inputsOK:
         self.events.add(EventName.locationdTemporaryError)
-      if (self.sm.seen['vehicleParameters'] and not self.sm['vehicleParameters'].valid and cal_status == log.ExtrinsicsCalibration.Status.calibrated and
+      if (not self.sm['vehicleParameters'].valid and cal_status == log.ExtrinsicsCalibration.Status.calibrated and
           not TESTING_CLOSET and (not SIMULATION or REPLAY)):
         self.events.add(EventName.paramsdTemporaryError)
 

openpilot/selfdrive/test/chestnut.sh

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

openpilot/selfdrive/test/process_replay/migration.py

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

openpilot/selfdrive/test/process_replay/model_replay.py

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

openpilot/selfdrive/test/process_replay/process_replay.py

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

openpilot/selfdrive/test/scons_build_test.sh

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

openpilot/selfdrive/test/setup_device_ci.sh

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

openpilot/selfdrive/test/test_onroad.py

@@ -20,12 +20,8 @@ from openpilot.common.basedir import BASEDIR
 from openpilot.common.timeout import Timeout
 from openpilot.common.params import Params
 from openpilot.selfdrive.selfdrived.events import EVENTS, ET
-from openpilot.selfdrive.test.helpers import set_params_enabled, release_only, processes_context, log_collector
-from openpilot.common.hardware import HARDWARE
+from openpilot.selfdrive.test.helpers import set_params_enabled, release_only
 from openpilot.common.hardware.hw import Paths
-from openpilot.common.mock import mock_messages
-from opendbc.car.car_helpers import get_demo_car_params
-from openpilot.selfdrive.modeld.helpers import chestnut_present, chestnut_compiled
 from openpilot.tools.lib.logreader import LogReader
 from openpilot.tools.lib.log_time_series import msgs_to_time_series
 
@@ -461,43 +457,5 @@ class TestOnroad(OpenpilotTestCase):
            f"Not engageable for whole segment:\n- selfdriveState.engageable: {Counter(eng)}\n- No entry events: {no_entries}"
 
 
-@unittest.skipUnless(HARDWARE.get_device_type() == "mici", "requires MICI")
-class TestChestnutOnroad(OpenpilotTestCase):
-  COMMA_HARDWARE_TEST = True
-
-  @mock_messages(['deviceMotion'])
-  def test_camera_models(self, subtests):
-    assert chestnut_present() and chestnut_compiled()
-    Params().put("CarParams", get_demo_car_params().to_bytes(), block=True)
-    services = ['narrowRoadCameraState', 'wideRoadCameraState', 'cabinCameraState', 'modelV2', 'driverStateV2']
-    sm = messaging.SubMaster(services)
-    pm = messaging.PubMaster(['deviceState'])
-    device_state = messaging.new_message('deviceState')
-    device_state.deviceState.deviceType = HARDWARE.get_device_type()
-    device_state_bytes = device_state.to_bytes()
-    with processes_context(['camerad', 'calibrationd', 'modeld', 'dmonitoringmodeld']):
-      with Timeout(60, "camera models didn't start"):
-        while not all(sm.seen.values()) or not sm.valid['modelV2']:
-          pm.send('deviceState', device_state_bytes)
-          sm.update(1000)
-      with log_collector(services) as (logs, _):
-        time.sleep(TEST_DURATION)
-
-    msgs = {s: [m for m in logs if m.which() == s] for s in services}
-    for service, messages in msgs.items():
-      with subtests.test(service=service):
-        expected = TEST_DURATION * SERVICE_LIST[service].frequency
-        assert np.isclose(len(messages), expected, rtol=0.05, atol=2), f"{service}: expected {expected}, got {len(messages)}"
-        assert all(m.valid for m in messages)
-        frame_ids = [getattr(m, service).frameId for m in messages]
-        assert np.all(np.diff(frame_ids) > 0), f"{service}: repeated or reordered frames"
-
-    camera_frames = {m.narrowRoadCameraState.frameId for m in msgs['narrowRoadCameraState']}
-    model_frames = {m.modelV2.frameId for m in msgs['modelV2']}
-    assert len(camera_frames & model_frames) >= TEST_DURATION * SERVICE_LIST['modelV2'].frequency * 0.9
-    assert all(m.modelV2.big for m in msgs['modelV2']), "Chestnut fell back to the small model"
-    assert all(np.isfinite(m.modelV2.position.x).all() for m in msgs['modelV2'])
-
-
 if __name__ == "__main__":
   unittest.main()

openpilot/selfdrive/test/test_power_draw.py

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

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

@@ -1,7 +1,7 @@
 import time
 import pyray as rl
 
-from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 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=TextAlignment.CENTER,
-                                       alignment_vertical=TextAlignmentVertical.MIDDLE)
+                                       alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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, TextAlignment
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
 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=TextAlignment.RIGHT)
+    gui_label(version_rect, self._version_text, 48, rl.WHITE, alignment=rl.GuiTextAlignment.TEXT_ALIGN_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, TextAlignment, gui_app
+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.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=TextAlignment.LEFT)
+    self._title = Label(tr("Welcome to sunnypilot"), font_size=90, font_weight=FontWeight.BOLD, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_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=TextAlignment.LEFT)
+                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_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=TextAlignment.LEFT)
+                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_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

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

openpilot/selfdrive/ui/layouts/sidebar.py

@@ -168,16 +168,9 @@ 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
-    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)
+    rl.draw_texture_ex(button_img, rl.Vector2(HOME_BTN.x, HOME_BTN.y), 0.0, 1.0, tint)
 
     # Microphone button
     if self._recording_audio:

openpilot/selfdrive/ui/lib/prime_state.py

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

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

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

@@ -77,7 +77,7 @@ class MiciMainLayout(Scroller):
       on_settings=lambda: gui_app.push_widget(self._settings_layout),
       on_alerts=lambda: self._scroll_to(self._alerts_layout),
       alert_count_callback=self._alerts_layout.active_alerts,
-      alert_icon_callback=self._alerts_layout.highest_severity_icon,
+      max_severity_callback=self._alerts_layout.max_severity,
     )
     for layout in (self._car_onroad_layout, self._body_onroad_layout):
       layout.set_click_callback(lambda: self._scroll_to(self._home_layout))

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

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 import pyray as rl
 import re
 import threading
@@ -13,7 +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, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.lib.multilang import tr
 
 REFRESH_INTERVAL = 5.0  # seconds
@@ -31,7 +29,6 @@ class AlertData:
   text: str
   severity: int
   visible: bool = False
-  icon: str | None = None
 
 
 class AlertItem(Widget):
@@ -59,28 +56,18 @@ class AlertItem(Widget):
     self._bg_big = gui_app.texture("icons_mici/offroad_alerts/big_alert.png", self.ALERT_WIDTH, self.ALERT_HEIGHT_BIG)
     self._bg_big_pressed = gui_app.texture("icons_mici/offroad_alerts/big_alert_pressed.png", self.ALERT_WIDTH, self.ALERT_HEIGHT_BIG)
 
-    # Load alert icons
+    # Load warning icons
     self._icon_orange = gui_app.texture("icons_mici/offroad_alerts/orange_warning.png", self.ICON_SIZE, self.ICON_SIZE)
     self._icon_red = gui_app.texture("icons_mici/offroad_alerts/red_warning.png", self.ICON_SIZE, self.ICON_SIZE)
     self._icon_green = gui_app.texture("icons_mici/offroad_alerts/green_wheel.png", self.ICON_SIZE, self.ICON_SIZE)
-    self._custom_icon = gui_app.texture(alert_data.icon, self.ICON_SIZE, self.ICON_SIZE) if alert_data.icon else None
-
-    if self._custom_icon is not None:
-      self._icon = self._custom_icon
-    elif alert_data.severity == -1:
-      self._icon = self._icon_green
-    elif alert_data.severity > 0:
-      self._icon = self._icon_red
-    else:
-      self._icon = self._icon_orange
 
     self._title_label = UnifiedLabel(text="", font_size=32, font_weight=FontWeight.SEMI_BOLD, text_color=self.TEXT_COLOR,
-                                     alignment=TextAlignment.LEFT,
-                                     alignment_vertical=TextAlignmentVertical.TOP, line_height=0.95)
+                                     alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
+                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP, line_height=0.95)
 
     self._body_label = UnifiedLabel(text="", font_size=28, font_weight=FontWeight.ROMAN, text_color=self.TEXT_COLOR,
-                                    alignment=TextAlignment.LEFT,
-                                    alignment_vertical=TextAlignmentVertical.BOTTOM, line_height=0.95)
+                                    alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
+                                    alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM, line_height=0.95)
 
     self._title_text = ""
     self._body_text = ""
@@ -88,10 +75,6 @@ class AlertItem(Widget):
 
     self._update_content()
 
-  @property
-  def icon(self) -> rl.Texture:
-    return self._icon
-
   def _split_text(self, text: str) -> tuple[str, str]:
     """Split text into title (first sentence) and body (remaining text)."""
     # Find the end of the first sentence (period, exclamation, or question mark followed by space or end)
@@ -193,9 +176,16 @@ class AlertItem(Widget):
       self._body_label.render(body_rect)
 
     # Draw warning icon on the right side
+    # Use green icon for update alerts (severity = -1), red for high severity, orange for low severity
+    if self.alert_data.severity == -1:
+      icon_texture = self._icon_green
+    elif self.alert_data.severity > 0:
+      icon_texture = self._icon_red
+    else:
+      icon_texture = self._icon_orange
     icon_x = self._rect.x + self.ALERT_WIDTH - self.ALERT_PADDING - self.ICON_SIZE
     icon_y = self._rect.y + self.ALERT_PADDING
-    rl.draw_texture_ex(self._icon, rl.Vector2(icon_x, icon_y), 0.0, 1.0, rl.WHITE)
+    rl.draw_texture_ex(icon_texture, rl.Vector2(icon_x, icon_y), 0.0, 1.0, rl.WHITE)
 
 
 class MiciOffroadAlerts(Scroller):
@@ -210,8 +200,8 @@ class MiciOffroadAlerts(Scroller):
 
     # Create empty state label
     self._empty_label = UnifiedLabel(tr("no alerts"), 65, FontWeight.DISPLAY, rl.WHITE,
-                                     alignment=TextAlignment.CENTER,
-                                     alignment_vertical=TextAlignmentVertical.MIDDLE)
+                                     alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
 
     # Build initial alert list
     self._build_alerts()
@@ -224,10 +214,8 @@ class MiciOffroadAlerts(Scroller):
   def active_alerts(self) -> int:
     return sum(alert.visible for alert in self.sorted_alerts)
 
-  def highest_severity_icon(self) -> rl.Texture | None:
-    item = max((item for item in self.alert_items if item.alert_data.visible),
-               key=lambda item: (item.alert_data.severity, bool(item.alert_data.icon)), default=None)
-    return item.icon if item is not None else None
+  def max_severity(self) -> int | None:
+    return max((alert.severity for alert in self.sorted_alerts if alert.visible), default=None)
 
   def scrolling(self):
     return self._scroller.scroll_panel.is_touch_valid()
@@ -247,7 +235,7 @@ class MiciOffroadAlerts(Scroller):
     # Add regular alerts sorted by severity
     for key, config in sorted(OFFROAD_ALERTS.items(), key=lambda x: x[1].get("severity", 0), reverse=True):
       severity = config.get("severity", 0)
-      alert_data = AlertData(key=key, text="", severity=severity, icon=config.get("icon"))
+      alert_data = AlertData(key=key, text="", severity=severity)
       self.sorted_alerts.append(alert_data)
 
       # Create alert item widget

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, TextAlignment
+from openpilot.system.ui.lib.application import FontWeight, gui_app
 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=TextAlignment.CENTER)
+                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
       rl.end_scissor_mode()
       return
 

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

@@ -23,6 +23,8 @@ class AlphaLongConfirmPage(NavScroller):
       GreyBigButton("", "WARNING: alpha longitudinal control may disable Automatic Emergency Braking (AEB)"),
       GreyBigButton("", "On this car, openpilot defaults to the stock system's built-in ACC."),
       GreyBigButton("", "Enabling this will switch to openpilot longitudinal control."),
+      GreyBigButton("", "Using Experimental mode is recommended with openpilot longitudinal control alpha."),
+      GreyBigButton("", "Changing this setting will restart openpilot if the car is powered on."),
       accept,
     ])
 
@@ -61,31 +63,28 @@ class DeveloperLayoutMici(NavScroller):
 
     txt_ssh = gui_app.texture("icons_mici/settings/developer/ssh.png", 56, 64)
     github_username = ui_state.params.get("GithubUsername") or ""
-    self._ssh_keys_btn = BigButton("SSH keys", "Not set" if not github_username else github_username, icon=txt_ssh,
-                                   description="Grant SSH access to all public keys in your GitHub settings. Only enter your own username.")
+    self._ssh_keys_btn = BigButton("SSH keys", "Not set" if not github_username else github_username, icon=txt_ssh)
     self._ssh_keys_btn.set_click_callback(ssh_keys_callback)
 
     # adb, ssh, ssh keys, debug mode, joystick debug mode, longitudinal maneuver mode, ip address
     # ******** Main Scroller ********
-    self._adb_toggle = BigCircleParamControl(gui_app.texture("icons_mici/adb_short.png", 82, 82), "AdbEnabled", icon_offset=(0, 12),
-                                             description="Use Android Debug Bridge (ADB) over USB or the network.", title="enable ADB")
-    self._ssh_toggle = BigCircleParamControl(gui_app.texture("icons_mici/ssh_short.png", 82, 82), "SshEnabled", icon_offset=(0, 12),
-                                             description="Access the device remotely using your SSH keys.", title="enable SSH")
-    self._joystick_toggle = BigToggle("joystick debug\nmode", initial_state=ui_state.params.get_bool("JoystickDebugMode"),
-                                      toggle_callback=self._on_joystick_debug_mode, description="Control the car with a joystick for debugging.")
-    self._long_maneuver_toggle = BigToggle("longitudinal maneuver mode", initial_state=ui_state.params.get_bool("LongitudinalManeuverMode"),
-                                           toggle_callback=self._on_long_maneuver_mode,
-                                           description="Run longitudinal maneuvers for testing gas and brake control.")
-    self._lat_maneuver_toggle = BigToggle("lateral maneuver mode", initial_state=ui_state.params.get_bool("LateralManeuverMode"),
-                                          toggle_callback=self._on_lat_maneuver_mode,
-                                          description="Run lateral maneuvers for testing steering control.")
-    self._alpha_long_toggle = BigToggle("alpha longitudinal", initial_state=ui_state.params.get_bool("AlphaLongitudinalEnabled"),
-                                        toggle_callback=self._on_alpha_long_enabled,
-                                        description="Use alpha openpilot longitudinal control instead of stock ACC. This may disable Automatic Emergency " +
-                                                    "Braking (AEB).")
+    self._adb_toggle = BigCircleParamControl(gui_app.texture("icons_mici/adb_short.png", 82, 82), "AdbEnabled", icon_offset=(0, 12))
+    self._ssh_toggle = BigCircleParamControl(gui_app.texture("icons_mici/ssh_short.png", 82, 82), "SshEnabled", icon_offset=(0, 12))
+    self._joystick_toggle = BigToggle("joystick debug mode",
+                                      initial_state=ui_state.params.get_bool("JoystickDebugMode"),
+                                      toggle_callback=self._on_joystick_debug_mode)
+    self._long_maneuver_toggle = BigToggle("longitudinal maneuver mode",
+                                           initial_state=ui_state.params.get_bool("LongitudinalManeuverMode"),
+                                           toggle_callback=self._on_long_maneuver_mode)
+    self._lat_maneuver_toggle = BigToggle("lateral maneuver mode",
+                                          initial_state=ui_state.params.get_bool("LateralManeuverMode"),
+                                          toggle_callback=self._on_lat_maneuver_mode)
+    self._alpha_long_toggle = BigToggle("alpha longitudinal",
+                                        initial_state=ui_state.params.get_bool("AlphaLongitudinalEnabled"),
+                                        toggle_callback=self._on_alpha_long_enabled)
     self._debug_mode_toggle = BigParamControl("ui debug mode", "ShowDebugInfo",
-                                              toggle_callback=lambda checked: (gui_app.set_show_touches(checked), gui_app.set_show_fps(checked)),
-                                              description="Show touch locations and the UI frame rate.")
+                                              toggle_callback=lambda checked: (gui_app.set_show_touches(checked),
+                                                                               gui_app.set_show_fps(checked)))
 
     self._scroller.add_widgets([
       self._adb_toggle,

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

@@ -1,7 +1,6 @@
 import os
 import pyray as rl
 from collections.abc import Callable
-from typing import Union
 
 from openpilot.common.basedir import BASEDIR
 from openpilot.common.params import Params
@@ -78,16 +77,15 @@ def _engaged_confirmation_click(callback: Callable, action_text: str, icon: rl.T
 
 class EngagedConfirmationCircleButton(BigCircleButton):
   def __init__(self, title: str, icon: rl.Texture, callback: Callable[[], None], exit_on_confirm: bool = True,
-               red: bool = False, icon_offset: tuple[int, int] = (0, 0), *, description: str = ""):
-    super().__init__(icon, red, icon_offset, description=description, title=title)
+               red: bool = False, icon_offset: tuple[int, int] = (0, 0)):
+    super().__init__(icon, red, icon_offset)
     self.set_click_callback(lambda: _engaged_confirmation_click(callback, title, icon, exit_on_confirm=exit_on_confirm, red=red))
 
 
 class EngagedConfirmationButton(BigButton):
   def __init__(self, text: str, action_text: str, icon: rl.Texture, callback: Callable[[], None],
-               exit_on_confirm: bool = True, red: bool = False, *, description: str = "",
-               description_icon: Union[rl.Texture, None] = None):
-    super().__init__(text, "", icon, description=description, description_icon=description_icon)
+               exit_on_confirm: bool = True, red: bool = False):
+    super().__init__(text, "", icon)
     self.set_click_callback(lambda: _engaged_confirmation_click(callback, action_text, icon, exit_on_confirm=exit_on_confirm, red=red))
 
 
@@ -179,9 +177,7 @@ class DeviceLayoutMici(NavScroller):
       params.put_bool("OnroadCycleRequested", True, block=True)
 
     reset_calibration_btn = EngagedConfirmationButton("reset calibration", "reset", gui_app.texture("icons_mici/settings/device/lkas.png", 122, 64),
-                                                      reset_calibration_callback,
-                                                      description="Mount the device within 4° left or right and 5° up or 9° down. openpilot calibrates " +
-                                                                  "continuously; resetting is rarely needed. Resetting clears learned calibration.")
+                                                      reset_calibration_callback)
 
     reboot_btn = EngagedConfirmationCircleButton("reboot", gui_app.texture("icons_mici/settings/device/reboot.png", 64, 70),
                                                  reboot_callback, exit_on_confirm=False)
@@ -193,8 +189,7 @@ class DeviceLayoutMici(NavScroller):
     regulatory_btn = BigButton("regulatory info", "", gui_app.texture("icons_mici/settings/device/info.png", 64, 64))
     regulatory_btn.set_click_callback(self._on_regulatory)
 
-    cabin_cam_btn = BigButton("driver\ncamera preview", "", gui_app.texture("icons_mici/settings/device/cameras.png", 64, 64),
-                              description="Preview the cabin camera to check driver monitoring visibility. The vehicle must be off.")
+    cabin_cam_btn = BigButton("driver\ncamera preview", "", gui_app.texture("icons_mici/settings/device/cameras.png", 64, 64))
     cabin_cam_btn.set_click_callback(lambda: gui_app.push_widget(CabinCameraDialog()))
     cabin_cam_btn.set_enabled(lambda: ui_state.is_offroad())
 

openpilot/selfdrive/ui/mici/layouts/settings/network/__init__.py

@@ -1,60 +1,13 @@
 import pyray as rl
 
-from openpilot.cereal import log
 from openpilot.selfdrive.ui.mici.layouts.settings.network.wifi_ui import WifiIcon
 from openpilot.selfdrive.ui.mici.widgets.button import BigButton
-from openpilot.common.hardware import HARDWARE
 from openpilot.system.ui.lib.application import gui_app
-from openpilot.system.ui.lib.cellular_manager import CellularManager
 from openpilot.system.ui.lib.wifi_manager import WifiManager, ConnectStatus, SecurityType, normalize_ssid
 
-NetworkStrength = log.DeviceState.NetworkStrength
-NetworkType = log.DeviceState.NetworkType
-
-
-class EsimNetworkButton(BigButton):
-  def __init__(self, cellular_manager: CellularManager, *, description: str = ""):
-    self._cellular_manager = cellular_manager
-    self._cell_icons = {
-      NetworkStrength.unknown: gui_app.texture("icons_mici/settings/network/cell_strength_none.png", 64, 47),
-      NetworkStrength.poor: gui_app.texture("icons_mici/settings/network/cell_strength_low.png", 64, 47),
-      NetworkStrength.moderate: gui_app.texture("icons_mici/settings/network/cell_strength_medium.png", 64, 47),
-      NetworkStrength.good: gui_app.texture("icons_mici/settings/network/cell_strength_high.png", 64, 47),
-      NetworkStrength.great: gui_app.texture("icons_mici/settings/network/cell_strength_full.png", 64, 47),
-    }
-    super().__init__("esim", "loading...", self._cell_icons[NetworkStrength.unknown], scroll=True, description=description)
-
-  def _update_state(self):
-    super()._update_state()
-    self.set_enabled(self._cellular_manager.is_euicc is not False)
-    text, value, icon = self._compute_state()
-    self.set_text(text)
-    self.set_value(value)
-    self.set_icon(icon)
-
-  def _compute_state(self):
-    cm = self._cellular_manager
-    none_icon = self._cell_icons[NetworkStrength.unknown]
-    ip = cm.modem_state.get("ip_address") or "connecting..."
-    if cm.is_euicc is False:
-      iccid = cm.modem_state.get("iccid") or ""
-      if not iccid:
-        return "sim", "no sim", none_icon
-      return f"sim (...{iccid[-4:]})", ip, self._cell_icon()
-
-    active = cm.active_profile
-    if active is None:
-      return "esim", "loading...", none_icon
-    return active.display_name, ip, self._cell_icon()
-
-  def _cell_icon(self):
-    # read directly from HARDWARE so it reflects modem state even when wifi is the active connection
-    strength = HARDWARE.get_network_strength(NetworkType.cell4G)
-    return self._cell_icons.get(strength, self._cell_icons[NetworkStrength.unknown])
-
 
 class WifiNetworkButton(BigButton):
-  def __init__(self, wifi_manager: WifiManager, *, description: str = ""):
+  def __init__(self, wifi_manager: WifiManager):
     self._wifi_manager = wifi_manager
     self._lock_txt = gui_app.texture("icons_mici/settings/network/new/lock.png", 28, 36)
     self._draw_lock = False
@@ -64,7 +17,7 @@ class WifiNetworkButton(BigButton):
     self._wifi_medium_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_medium.png", 64, 47)
     self._wifi_full_txt = gui_app.texture("icons_mici/settings/network/wifi_strength_full.png", 64, 47)
 
-    super().__init__("wi-fi", "not connected", self._wifi_slash_txt, scroll=True, description=description)
+    super().__init__("wi-fi", "not connected", self._wifi_slash_txt, scroll=True)
 
   def _update_state(self):
     super()._update_state()

openpilot/selfdrive/ui/mici/layouts/settings/network/esim_ui.py

@@ -1,412 +0,0 @@
-import threading
-
-import numpy as np
-import pyray as rl
-from collections.abc import Callable
-from openpilot.cereal import log
-from openpilot.cereal.visionipc import VisionStreamType
-
-from openpilot.common import qrcode
-from openpilot.common.swaglog import cloudlog
-from openpilot.selfdrive.ui.mici.onroad.cabin_camera_dialog import CabinCameraView
-from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.lib.multilang import tr
-from openpilot.system.ui.widgets.nav_widget import NavWidget
-
-from openpilot.selfdrive.ui.mici.widgets.button import BigButton, LABEL_COLOR
-from openpilot.selfdrive.ui.mici.widgets.dialog import BigDialog, BigInputDialog, BigConfirmationDialog
-from openpilot.common.esim.base import Profile
-from openpilot.common.esim.lpa import parse_lpa_activation_code
-from openpilot.system.ui.lib.application import DEFAULT_TEXT_COLOR, FontWeight, MousePos, TextAlignment, gui_app
-from openpilot.system.ui.lib.cellular_manager import CellularManager
-from openpilot.system.ui.widgets import Widget
-from openpilot.system.ui.widgets.label import UnifiedLabel, gui_label
-from openpilot.system.ui.widgets.scroller import NavRawScrollPanel, NavScroller
-
-
-class ProfileActionButton(Widget):
-  SIZE = 68
-  MARGIN = 10
-  HORIZONTAL_MARGIN = 4
-
-  def __init__(self, callback: Callable, delete: bool = False):
-    super().__init__()
-    self.set_click_callback(callback)
-    self._delete = delete
-    self._trash_txt = gui_app.texture("icons_mici/settings/network/new/trash.png", 25, 30) if delete else None
-
-    self._bg_txt = gui_app.texture("icons_mici/buttons/button_circle.png", self.SIZE, self.SIZE)
-    self._bg_pressed_txt = gui_app.texture("icons_mici/buttons/button_circle_pressed.png", self.SIZE, self.SIZE)
-    self.set_rect(rl.Rectangle(0, 0, self.SIZE + self.HORIZONTAL_MARGIN * 2, self.SIZE + self.MARGIN * 2))
-
-  def _render(self, _):
-    bg_txt = self._bg_pressed_txt if self.is_pressed else self._bg_txt
-    rl.draw_texture_ex(bg_txt, (self._rect.x + (self._rect.width - self._bg_txt.width) / 2,
-                                self._rect.y + (self._rect.height - self._bg_txt.height) / 2), 0, 1.0, rl.WHITE)
-    color = rl.Color(255, 105, 115, 255) if self._delete else DEFAULT_TEXT_COLOR
-    if not self.enabled:
-      color = rl.Color(color.r, color.g, color.b, 90)
-    if self._trash_txt:
-      rl.draw_texture_ex(self._trash_txt, (self._rect.x + (self._rect.width - self._trash_txt.width) / 2,
-                                          self._rect.y + (self._rect.height - self._trash_txt.height) / 2), 0, 1.0, color)
-    else:
-      gui_label(self._rect, "Aa", 30, color=color, alignment=TextAlignment.CENTER)
-
-
-class QRScannerDialog(NavWidget):
-  SCAN_INTERVAL_S = 0.25
-  INVALID_CODE_DURATION_S = 1.0
-
-  def __init__(self, on_qr_detected: Callable[[str], None]):
-    super().__init__()
-    self._on_qr_detected = on_qr_detected
-    self._camera_view = CabinCameraView("camerad", VisionStreamType.VISION_STREAM_CABIN)
-    self._detected = False
-    self._last_scan_time = 0.0
-    self._invalid_code_until = 0.0
-    self._scan_thread: threading.Thread | None = None
-    self._scan_result: str | None = None
-    self.set_rect(rl.Rectangle(0, 0, gui_app.width, gui_app.height))
-
-  def show_event(self):
-    super().show_event()
-    ui_state.params.put_bool("DisableDriverCameraIR", True)
-    ui_state.params.put_bool("IsDriverViewEnabled", True)
-
-  def hide_event(self):
-    super().hide_event()
-    ui_state.params.put_bool("IsDriverViewEnabled", False)
-    ui_state.params.put_bool("DisableDriverCameraIR", False)
-
-  def __del__(self):
-    self._camera_view.close()
-
-  def _update_state(self):
-    super()._update_state()
-
-    now = rl.get_time()
-    if self._detected or not self._camera_view.frame or now < self._invalid_code_until:
-      return
-
-    if self._scan_thread is not None:
-      if self._scan_thread.is_alive():
-        return
-      self._scan_thread = None
-      data = self._scan_result
-      if data is not None:
-        try:
-          parse_lpa_activation_code(data)
-        except ValueError:
-          self._invalid_code_until = now + self.INVALID_CODE_DURATION_S
-          self._last_scan_time = self._invalid_code_until
-        else:
-          self._detected = True
-          self.dismiss(lambda: self._on_qr_detected(data))
-        return
-
-    if now - self._last_scan_time < self.SCAN_INTERVAL_S:
-      return
-    self._last_scan_time = now
-
-    frame = self._camera_view.frame
-    y = np.frombuffer(frame.data, dtype=np.uint8, count=frame.height * frame.stride).reshape(frame.height, frame.stride)
-    gray = y[:, :frame.width].copy()  # the vision buffer is recycled under the scan thread
-    self._scan_thread = threading.Thread(target=self._scan, args=(gray,), daemon=True)
-    self._scan_thread.start()
-
-  def _scan(self, gray: np.ndarray):
-    self._scan_result = qrcode.decode(gray)
-
-  def _render(self, rect):
-    rl.begin_scissor_mode(int(rect.x), int(rect.y), int(rect.width), int(rect.height))
-    self._camera_view._render(rect)
-
-    if not self._camera_view.frame:
-      gui_label(rect, tr("camera starting"), font_size=54, font_weight=FontWeight.BOLD,
-                alignment=TextAlignment.CENTER)
-    else:
-      label_y = rect.y + rect.height * 3 / 4
-      label_rect = rl.Rectangle(rect.x, label_y + (rect.height - label_y) / 2 - 20, rect.width, 40)
-      text = "not an LPA code" if rl.get_time() < self._invalid_code_until else "hold QR code to camera"
-      gui_label(label_rect, text, font_size=32, font_weight=FontWeight.MEDIUM,
-                alignment=TextAlignment.CENTER,
-                color=rl.Color(255, 255, 255, int(255 * 0.9)))
-
-    rl.end_scissor_mode()
-
-
-class InstallingProfileDialog(BigDialog):
-  DOT_STEP = 0.6
-
-  def __init__(self):
-    super().__init__("installing profile", "please wait...")
-    self._show_time = 0.0
-
-  def show_event(self):
-    super().show_event()
-    self._nav_bar._alpha = 0.0
-    self._show_time = rl.get_time()
-
-  def _back_enabled(self) -> bool:
-    return False
-
-  def _render(self, _):
-    t = (rl.get_time() - self._show_time) % (self.DOT_STEP * 2)
-    dots = "." * min(int(t / (self.DOT_STEP / 4)), 3)
-    self._card.set_value(f"please wait{dots}")
-    super()._render(_)
-
-
-class EsimProfileButton(BigButton):
-  SUB_LABEL_DISABLED = rl.Color(255, 255, 255, int(255 * 0.585))
-  CHECK_ICON_COLOR = rl.Color(255, 255, 255, int(255 * 0.9 * 0.65))
-  LABEL_PADDING = 98
-  LABEL_WIDTH = 402 - 98 - 28
-  SUB_LABEL_WIDTH = 402 - BigButton.LABEL_HORIZONTAL_PADDING * 2
-
-  def __init__(self, profile: Profile, cellular_manager: CellularManager, profiles_enabled: Callable[[], bool]):
-    self._cellular_manager = cellular_manager
-    self._profiles_enabled = profiles_enabled
-    super().__init__(profile.display_name, scroll=True)
-
-    self._profile = profile
-
-    self._cell_full_txt = gui_app.texture("icons_mici/settings/network/cell_strength_full.png", 48, 36)
-    self._cell_none_txt = gui_app.texture("icons_mici/settings/network/cell_strength_none.png", 48, 36)
-    self._check_txt = gui_app.texture("icons_mici/setup/driver_monitoring/dm_check.png", 32, 32)
-    self._comma_txt = gui_app.texture("icons_mici/settings/comma_icon.png", 36, 36) if profile.is_comma else None
-
-    self._delete_btn = ProfileActionButton(self._on_delete, delete=True)
-    self._rename_btn = ProfileActionButton(self._on_rename) if not profile.is_comma else None
-    self._delete_btn.set_enabled(lambda: not self._locked and not self._cellular_manager.busy and self._show_delete_btn)
-    if self._rename_btn:
-      self._rename_btn.set_enabled(lambda: not self._locked and not self._cellular_manager.busy)
-    self.set_enabled(lambda: not self._profile.enabled and self._profiles_enabled() and not self._cellular_manager.busy)
-    self.update_profile(profile)
-
-  @property
-  def profile(self) -> Profile:
-    return self._profile
-
-  def update_profile(self, profile: Profile):
-    self._profile = profile
-    active = profile.enabled
-    self.set_text(profile.display_name)
-    self.set_value("active" if active else "switch")
-
-  def _update_state(self):
-    super()._update_state()
-    self._sub_label.set_color(DEFAULT_TEXT_COLOR if self.enabled else self.SUB_LABEL_DISABLED)
-    self._sub_label.set_font_weight(FontWeight.SEMI_BOLD if self.enabled else FontWeight.ROMAN)
-
-  @property
-  def _locked(self) -> bool:
-    return not self._profile.is_comma and not self._profiles_enabled()
-
-  @property
-  def _show_delete_btn(self) -> bool:
-    return not self._profile.enabled and not self._profile.is_comma
-
-  def _on_rename(self):
-    current = self._profile.nickname or ""
-    dlg = BigInputDialog("nickname", default_text=current, confirm_callback=self._on_nickname_entered,
-                         text_validator=lambda text: bool(text.strip()))
-    gui_app.push_widget(dlg)
-
-  def _on_delete(self):
-    icon = gui_app.texture("icons_mici/settings/network/new/trash.png", 54, 64)
-    gui_app.push_widget(BigConfirmationDialog("slide to delete", icon, self._delete_profile, red=True))
-
-  def _delete_profile(self):
-    if not self._locked and not self._cellular_manager.busy and self._show_delete_btn:
-      if ui_state.sm["deviceState"].networkType == log.DeviceState.NetworkType.none:
-        gui_app.push_widget(BigDialog("", tr("Ensure you're connected to the internet and try again.")))
-        return
-      self._cellular_manager.delete_profile(self._profile.iccid)
-
-  def _on_nickname_entered(self, nickname: str):
-    if not self._locked and not self._cellular_manager.busy:
-      self._cellular_manager.nickname_profile(self._profile.iccid, nickname.strip())
-
-  def _handle_mouse_release(self, mouse_pos: MousePos):
-    if self._show_delete_btn and rl.check_collision_point_rec(mouse_pos, self._delete_btn.rect):
-      return
-    if self._rename_btn is not None and rl.check_collision_point_rec(mouse_pos, self._rename_btn.rect):
-      return
-    super()._handle_mouse_release(mouse_pos)
-
-  def _get_label_font_size(self):
-    return 48
-
-  def _draw_content(self, btn_y: float):
-    self._label.set_color(self.SUB_LABEL_DISABLED if self._locked else LABEL_COLOR)
-    label_rect = rl.Rectangle(self._rect.x + self.LABEL_PADDING, btn_y + self.LABEL_VERTICAL_PADDING,
-                              self.LABEL_WIDTH, self._rect.height - self.LABEL_VERTICAL_PADDING * 2)
-    self._label.render(label_rect)
-
-    active = self._profile.enabled
-
-    if self.value:
-      sub_label_x = self._rect.x + self.LABEL_HORIZONTAL_PADDING
-      label_y = btn_y + self._rect.height - self.LABEL_VERTICAL_PADDING
-      action_w = self._rename_btn.rect.width if self._rename_btn is not None else 0
-      action_w += self._delete_btn.rect.width if self._show_delete_btn else 0
-      sub_label_w = self.SUB_LABEL_WIDTH - action_w
-      sub_label_height = self._sub_label.get_content_height(sub_label_w)
-
-      if active:
-        check_y = int(label_y - sub_label_height + (sub_label_height - self._check_txt.height) / 2)
-        rl.draw_texture_ex(self._check_txt, rl.Vector2(sub_label_x, check_y), 0.0, 1.0, self.CHECK_ICON_COLOR)
-        sub_label_x += self._check_txt.width + 14
-
-      sub_label_rect = rl.Rectangle(sub_label_x, label_y - sub_label_height, sub_label_w, sub_label_height)
-      self._sub_label.render(sub_label_rect)
-
-    if self._comma_txt:
-      rl.draw_texture_ex(self._comma_txt, (self._rect.x + 36, btn_y + 38), 0.0, 1.0, rl.WHITE)
-    else:
-      cell_icon = self._cell_full_txt if active else self._cell_none_txt
-      rl.draw_texture_ex(cell_icon, (self._rect.x + 30, btn_y + 38), 0.0, 1.0, rl.WHITE)
-
-    btn_x = self._rect.x + self._rect.width - (ProfileActionButton.MARGIN - ProfileActionButton.HORIZONTAL_MARGIN)
-    btn_bottom = btn_y + self._rect.height
-    if self._show_delete_btn:
-      btn_x -= self._delete_btn.rect.width
-      self._delete_btn.render(rl.Rectangle(
-        btn_x, btn_bottom - self._delete_btn.rect.height,
-        self._delete_btn.rect.width, self._delete_btn.rect.height,
-      ))
-    if self._rename_btn is not None:
-      btn_x -= self._rename_btn.rect.width
-      self._rename_btn.render(rl.Rectangle(
-        btn_x, btn_bottom - self._rename_btn.rect.height,
-        self._rename_btn.rect.width, self._rename_btn.rect.height,
-      ))
-
-  def set_touch_valid_callback(self, touch_callback: Callable[[], bool]) -> None:
-    def action_pressed() -> bool:
-      return self._delete_btn.is_pressed or (self._rename_btn is not None and self._rename_btn.is_pressed)
-    super().set_touch_valid_callback(lambda: touch_callback() and not action_pressed())
-    self._delete_btn.set_touch_valid_callback(touch_callback)
-    if self._rename_btn:
-      self._rename_btn.set_touch_valid_callback(touch_callback)
-
-
-class EsimErrorDialog(NavRawScrollPanel):
-  def __init__(self, error: str):
-    super().__init__()
-    self._title = UnifiedLabel("esim error", font_size=64, font_weight=FontWeight.BOLD)
-    self._error = UnifiedLabel(error, font_size=36, elide=False)
-
-  def _render(self, rect: rl.Rectangle):
-    width = int(rect.width - 80)
-    title_height = self._title.get_content_height(width)
-    error_height = self._error.get_content_height(width)
-    offset = self._scroll_panel.update(rect, title_height + error_height + 100)
-    y = rect.y + 40 + offset
-
-    rl.begin_scissor_mode(int(rect.x), int(rect.y), int(rect.width), int(rect.height))
-    self._title.render(rl.Rectangle(rect.x + 40, y, width, title_height))
-    self._error.render(rl.Rectangle(rect.x + 40, y + title_height + 20, width, error_height))
-    rl.end_scissor_mode()
-
-
-class EsimUI(NavScroller):
-  def __init__(self, cellular_manager: CellularManager, profiles_enabled: Callable[[], bool]):
-    super().__init__()
-
-    self._cellular_manager = cellular_manager
-    self._profiles_enabled = profiles_enabled
-
-    self._add_profile_btn = BigButton("add profile", "scan QR code")
-    self._add_profile_btn.set_click_callback(self._on_add_profile)
-    self._scroller.add_widget(self._add_profile_btn)
-    self._installing_dialog: InstallingProfileDialog | None = None
-
-    self._cellular_manager.on_profiles_updated = self._on_profiles_updated
-    self._cellular_manager.on_operation_error = self._on_error
-
-  def show_event(self):
-    super().show_event()
-    self._update_buttons(re_sort=True)
-    self._cellular_manager.refresh_profiles()
-
-  def _on_profiles_updated(self):
-    if self._installing_dialog:
-      existing = {btn.profile.iccid for btn in self._scroller.items if isinstance(btn, EsimProfileButton)}
-      added = [profile for profile in self._cellular_manager.profiles if profile.iccid not in existing]
-      # Start the normal tap-to-activate flow once the profile list is visible again.
-      self._installing_dialog.dismiss(lambda: self._on_profile_clicked(added[0]) if len(added) == 1 else None)
-      self._installing_dialog = None
-
-    self._update_buttons()
-
-  def _update_buttons(self, re_sort: bool = False):
-    existing = {btn.profile.iccid: btn for btn in self._scroller.items if isinstance(btn, EsimProfileButton)}
-    buttons = []
-    for profile in self._cellular_manager.profiles:
-      btn = existing.get(profile.iccid)
-      if btn is None:
-        btn = EsimProfileButton(profile, self._cellular_manager, self._profiles_enabled)
-        btn.set_click_callback(lambda btn=btn: self._on_profile_clicked(btn.profile))
-        self._scroller.add_widget(btn)
-      else:
-        btn.update_profile(profile)
-      buttons.append(btn)
-
-    if re_sort:
-      self._scroller.items[:] = sorted(buttons, key=lambda b: not b.profile.enabled)
-    else:
-      self._scroller.items[:] = [btn for btn in self._scroller.items if btn in buttons]
-
-    self._scroller.items.append(self._add_profile_btn)
-
-  def _move_profile_to_front(self, iccid: str | None, scroll: bool = False):
-    front_btn_idx = next((i for i, btn in enumerate(self._scroller.items)
-                          if isinstance(btn, EsimProfileButton) and btn.profile.iccid == iccid), None) if iccid else None
-
-    if front_btn_idx is not None and front_btn_idx > 0:
-      self._scroller.move_item(front_btn_idx, 0)
-
-      if scroll:
-        self._scroller.scroll_to(self._scroller.scroll_panel.get_offset(), smooth=True)
-
-  def _update_state(self):
-    super()._update_state()
-
-    self._add_profile_btn.set_enabled(not self._cellular_manager.busy and self._profiles_enabled())
-    active = self._cellular_manager.active_profile
-    self._move_profile_to_front(active.iccid if active else None)
-
-  def _on_add_profile(self):
-    if self._cellular_manager.busy or not self._profiles_enabled():
-      return
-    if ui_state.sm["deviceState"].networkType == log.DeviceState.NetworkType.none:
-      gui_app.push_widget(BigDialog("", tr("Ensure you're connected to the internet and try again.")))
-      return
-    gui_app.push_widget(QRScannerDialog(on_qr_detected=self._on_qr_scanned))
-
-  def _on_qr_scanned(self, lpa_code: str):
-    dlg = BigInputDialog("enter a nickname...", text_validator=lambda text: bool(text.strip()),
-                         confirm_callback=lambda nickname: self._download_profile(lpa_code, nickname))
-    gui_app.push_widget(dlg)
-
-  def _download_profile(self, lpa_code: str, nickname: str):
-    self._installing_dialog = InstallingProfileDialog()
-    gui_app.push_widget(self._installing_dialog)
-    self._cellular_manager.download_profile(lpa_code, nickname.strip())
-
-  def _on_error(self, error: str):
-    cloudlog.error("eSIM error: %s", error)
-    dlg = EsimErrorDialog(error)
-    if self._installing_dialog:
-      self._installing_dialog.dismiss(lambda: gui_app.push_widget(dlg))
-      self._installing_dialog = None
-    else:
-      gui_app.push_widget(dlg)
-
-  def _on_profile_clicked(self, profile: Profile):
-    if self._cellular_manager.busy or not self._profiles_enabled():
-      return
-    self._cellular_manager.switch_profile(profile.iccid)
-    self._move_profile_to_front(profile.iccid, scroll=True)

openpilot/selfdrive/ui/mici/layouts/settings/network/network_layout.py

@@ -1,13 +1,12 @@
-from openpilot.selfdrive.ui.mici.layouts.settings.network import EsimNetworkButton, WifiNetworkButton
-from openpilot.selfdrive.ui.mici.layouts.settings.network.esim_ui import EsimUI
+from openpilot.system.ui.widgets.scroller import NavScroller
+from openpilot.selfdrive.ui.mici.layouts.settings.network import WifiNetworkButton
 from openpilot.selfdrive.ui.mici.layouts.settings.network.wifi_ui import WifiUIMici
 from openpilot.selfdrive.ui.mici.widgets.button import BigButton, BigMultiToggle, BigParamControl, BigToggle
 from openpilot.selfdrive.ui.mici.widgets.dialog import BigInputDialog
 from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.selfdrive.ui.lib.prime_state import PrimeType
 from openpilot.system.ui.lib.application import gui_app
-from openpilot.system.ui.lib.cellular_manager import CellularManager
 from openpilot.system.ui.lib.wifi_manager import WifiManager, Network, MeteredType
-from openpilot.system.ui.widgets.scroller import NavScroller
 
 
 class NetworkLayoutMici(NavScroller):
@@ -29,8 +28,7 @@ class NetworkLayoutMici(NavScroller):
       self._network_metered_btn.set_enabled(False)
       self._wifi_manager.set_tethering_active(checked)
 
-    self._tethering_toggle_btn = BigToggle("enable tethering", "", toggle_callback=tethering_toggle_callback,
-                                           description="Share the device’s internet connection through a Wi-Fi hotspot.")
+    self._tethering_toggle_btn = BigToggle("enable tethering", "", toggle_callback=tethering_toggle_callback)
 
     def tethering_password_callback(password: str):
       if password:
@@ -60,39 +58,26 @@ class NetworkLayoutMici(NavScroller):
 
     # TODO: signal for current network metered type when changing networks, this is wrong until you press it once
     # TODO: disable when not connected
-    self._network_metered_btn = BigMultiToggle("network usage", ["default", "metered", "unmetered"], select_callback=network_metered_callback,
-                                               description="Metered prevents large uploads on this Wi-Fi connection. Default uses the network’s detected " +
-                                                           "setting.")
+    self._network_metered_btn = BigMultiToggle("network usage", ["default", "metered", "unmetered"], select_callback=network_metered_callback)
     self._network_metered_btn.set_enabled(False)
 
     self._wifi_button = WifiNetworkButton(self._wifi_manager)
     self._wifi_button.set_click_callback(lambda: gui_app.push_widget(self._wifi_ui))
 
-    # ******** eSIM ********
-    self._cellular_manager = CellularManager()
-    self._esim_ui = EsimUI(
-      self._cellular_manager,
-      lambda: not ui_state.prime_state.is_full_prime(),
-    )
-    self._esim_button = EsimNetworkButton(self._cellular_manager)
-    self._esim_button.set_click_callback(lambda: gui_app.push_widget(self._esim_ui))
-
     # ******** Advanced settings ********
     # ******** Roaming toggle ********
-    self._roaming_btn = BigParamControl("enable roaming", "GsmRoaming", description="Allow cellular data roaming.")
+    self._roaming_btn = BigParamControl("enable roaming", "GsmRoaming")
 
     # ******** APN settings ********
-    self._apn_btn = BigButton("apn settings", "edit",
-                              description="Set the access point name required by your cellular carrier. Leave blank for automatic configuration.")
+    self._apn_btn = BigButton("apn settings", "edit")
     self._apn_btn.set_click_callback(self._edit_apn)
 
     # ******** Cellular metered toggle ********
-    self._cellular_metered_btn = BigParamControl("cellular metered", "GsmMetered", description="Prevent large uploads over the cellular connection.")
+    self._cellular_metered_btn = BigParamControl("cellular metered", "GsmMetered")
 
     # Main scroller ----------------------------------
     self._scroller.add_widgets([
       self._wifi_button,
-      self._esim_button,
       self._network_metered_btn,
       self._tethering_toggle_btn,
       self._tethering_password_btn,
@@ -106,7 +91,8 @@ class NetworkLayoutMici(NavScroller):
   def _update_state(self):
     super()._update_state()
 
-    show_cell_settings = not ui_state.prime_state.is_full_prime()
+    # If not using prime SIM, show GSM settings and enable IPv4 forwarding
+    show_cell_settings = ui_state.prime_state.get_type() in (PrimeType.NONE, PrimeType.LITE)
     self._wifi_manager.set_ipv4_forward(show_cell_settings)
     self._roaming_btn.set_visible(show_cell_settings)
     self._apn_btn.set_visible(show_cell_settings)
@@ -116,16 +102,14 @@ class NetworkLayoutMici(NavScroller):
     super().show_event()
     self._wifi_manager.set_active(True)
 
-    # Process wifi and esim callbacks while at any point in the nav stack
+    # Process wifi callbacks while at any point in the nav stack
     gui_app.add_nav_stack_tick(self._wifi_manager.process_callbacks)
-    gui_app.add_nav_stack_tick(self._cellular_manager.process_callbacks)
 
   def hide_event(self):
     super().hide_event()
     self._wifi_manager.set_active(False)
 
     gui_app.remove_nav_stack_tick(self._wifi_manager.process_callbacks)
-    gui_app.remove_nav_stack_tick(self._cellular_manager.process_callbacks)
 
   def _edit_apn(self):
     def update_apn(apn: str):

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

@@ -3,7 +3,7 @@ from openpilot.system.ui.widgets.scroller import NavScroller
 from openpilot.selfdrive.ui.mici.widgets.button import BigButton
 from openpilot.selfdrive.ui.mici.layouts.settings.toggles import TogglesLayoutMici
 from openpilot.selfdrive.ui.mici.layouts.settings.network.network_layout import NetworkLayoutMici
-from openpilot.selfdrive.ui.mici.layouts.settings.device import DeviceLayoutMici
+from openpilot.selfdrive.ui.mici.layouts.settings.device import DeviceLayoutMici, PairBigButton
 from openpilot.selfdrive.ui.mici.layouts.settings.developer import DeveloperLayoutMici
 from openpilot.selfdrive.ui.mici.layouts.settings.software import SoftwareLayoutMici
 from openpilot.selfdrive.ui.mici.layouts.settings.firehose import FirehoseLayout
@@ -49,6 +49,7 @@ class SettingsLayout(NavScroller):
       network_btn,
       device_btn,
       software_btn,
+      PairBigButton(),
       firehose_btn,
       developer_btn,
     ])

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

@@ -74,10 +74,6 @@ 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)
@@ -101,20 +97,15 @@ 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():
-      subprocess.run(f"pkill -{sig} -f {self.UPDATER_PROC}", shell=True)
+      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)
 
     threading.Thread(target=run, daemon=True).start()
 
@@ -193,7 +184,7 @@ class CheckUpdateButton(BigButton):
 
 class InstallUpdateButton(BigButton):
   def __init__(self):
-    super().__init__("install now", "", gui_app.texture("icons_mici/settings/device/reboot.png", 64, 70))
+    super().__init__("install update", "", 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):
@@ -241,10 +232,8 @@ class BranchSelectPage(NavScroller):
 
 
 class TargetBranchButton(BigButton):
-  def __init__(self, check_update_btn: CheckUpdateButton):
-    super().__init__("target branch", ui_state.params.get("UpdaterTargetBranch") or "",
-                     description="Select the software branch to download on the next update check.")
-    self._check_update_btn = check_update_btn
+  def __init__(self):
+    super().__init__("target branch", ui_state.params.get("UpdaterTargetBranch") or "")
     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())
@@ -257,15 +246,12 @@ 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)
-    self._check_update_btn.check_for_update()
+    subprocess.run("pkill -SIGUSR1 -f openpilot.system.updated.updated", shell=True)
 
 
 class SoftwareLayoutMici(NavScroller):
@@ -277,15 +263,12 @@ class SoftwareLayoutMici(NavScroller):
 
     uninstall_openpilot_btn = EngagedConfirmationButton("uninstall sunnypilot", "uninstall",
                                                         gui_app.texture("icons_mici/settings/device/uninstall.png", 64, 64),
-                                                        uninstall_openpilot_callback, exit_on_confirm=False,
-                                                        description="Remove openpilot from this device.",
-                                                        description_icon=gui_app.texture("icons_mici/setup/factory_reset.png", 64, 64))
+                                                        uninstall_openpilot_callback, exit_on_confirm=False)
 
-    check_update_btn = CheckUpdateButton()
     self._scroller.add_widgets([
       SoftwareInfoLayoutMici(),
-      check_update_btn,
+      CheckUpdateButton(),
       InstallUpdateButton(),
-      TargetBranchButton(check_update_btn),
+      TargetBranchButton(),
       uninstall_openpilot_btn,
     ])

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

@@ -41,34 +41,15 @@ class TogglesLayoutMici(NavScroller):
   def __init__(self):
     super().__init__()
 
-    self._personality_toggle = BigMultiParamToggle("driving personality", "LongitudinalPersonality", ["aggressive", "standard", "relaxed"],
-                                                   description="Standard is recommended.\n" +
-                                                               "Aggressive follows closer, with firmer gas and braking.\n" +
-                                                               "Relaxed leaves more space.\n" +
-                                                               "Use the steering wheel distance button on supported cars.")
-    self._experimental_btn = BigToggle("experimental mode", description_icon=gui_app.texture("icons_mici/experimental_mode.png", 64, 64),
-                                       initial_state=ui_state.params.get_bool("ExperimentalMode"), toggle_callback=self._on_experimental_mode,
-                                       description="Let the driving model control gas and brakes.\n" +
-                                                   "Includes stopping for red lights and stop signs.\n" +
-                                                   "Set speed is a maximum, not a target.\n" +
-                                                   "These are alpha features. Expect mistakes.\n" +
-                                                   "The path colors show acceleration and braking.")
+    self._personality_toggle = BigMultiParamToggle("driving personality", "LongitudinalPersonality", ["aggressive", "standard", "relaxed"])
+    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")
-    ldw_toggle = BigParamControl("lane departure warnings", "IsLdwEnabled",
-                                 description="Warn when you drift across a detected lane line.\n" +
-                                             "Only above 31 mph (50 km/h), with no turn signal.")
-    always_on_dm_toggle = BigParamControl("always-on driver monitor", "AlwaysOnDM", description="Monitor the driver even when sunnypilot is not engaged.")
-    record_front = BigParamControl("record & upload cabin camera", "RecordFront",
-                                   description_icon=gui_app.texture("icons_mici/settings/device/cameras.png", 64, 64),
-                                   toggle_callback=restart_needed_callback, description="Upload cabin camera data to help improve driver monitoring.")
-    record_mic = BigParamControl("record & upload mic audio", "RecordAudio", description_icon=gui_app.texture("icons_mici/microphone.png", 64, 64),
-                                 toggle_callback=restart_needed_callback,
-                                 description="Record microphone audio while driving.\n" +
-                                             "Audio is included in dashcam videos in sunnylink.")
-    enable_openpilot = BigParamControl("enable sunnypilot", "OpenpilotEnabledToggle", toggle_callback=restart_needed_callback,
-                                       description="Enable to use sunnypilot driver assistance.\n" +
-                                                   "Disable to use your car's stock driver assistance.")
-
+    ldw_toggle = BigParamControl("lane departure warnings", "IsLdwEnabled")
+    always_on_dm_toggle = BigParamControl("always-on driver monitor", "AlwaysOnDM")
+    record_front = BigParamControl("record & upload cabin camera", "RecordFront", toggle_callback=restart_needed_callback)
+    record_mic = BigParamControl("record & upload mic audio", "RecordAudio", toggle_callback=restart_needed_callback)
+    enable_openpilot = BigParamControl("enable sunnypilot", "OpenpilotEnabledToggle", toggle_callback=restart_needed_callback)
 
     self._scroller.add_widgets([
       self._personality_toggle,