zoom zoom

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

@@ -8,13 +8,13 @@ on:
         required: true
         type: string
       target_hardware:
-        description: 'Hardware target to compile for (qcom or 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
@@ -59,7 +59,7 @@ jobs:
         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"
@@ -78,7 +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

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

@@ -30,7 +30,6 @@ jobs:
     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 }}
@@ -65,9 +64,7 @@ jobs:
             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
@@ -138,7 +135,7 @@ jobs:
 
       - name: Prepare output
         env:
-          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
+          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           export PYTHONPATH=${{ github.workspace }}
@@ -161,13 +158,13 @@ jobs:
       - name: Upload small model artifact
         uses: actions/upload-artifact@v4
         with:
-          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
+          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
           path: ${{ github.workspace }}/small_output/
 
       - name: Upload artifact name file
         uses: actions/upload-artifact@v4
         with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
           path: ${{ github.workspace }}/small_output/artifact_name.txt
 
       - name: Re-enable powersave
@@ -179,7 +176,7 @@ jobs:
   build_big_model:
     needs: resolve
     if: ${{ inputs.target == 'big' }}
-    runs-on: [self-hosted, chestnut]
+    runs-on: [self-hosted, usbgpu]
     env:
       BIG_ONNX: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
       BIG_PKL: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
@@ -257,7 +254,7 @@ jobs:
 
       - name: Prepare output
         env:
-          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
+          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           export PYTHONPATH=${{ github.workspace }}
@@ -280,13 +277,13 @@ jobs:
       - name: Upload big model artifact
         uses: actions/upload-artifact@v4
         with:
-          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
+          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
           path: ${{ github.workspace }}/big_output/
 
       - name: Upload artifact name file
         uses: actions/upload-artifact@v4
         with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
           path: ${{ github.workspace }}/big_output/artifact_name.txt
 
       - name: Re-enable powersave
@@ -321,7 +318,7 @@ jobs:
         if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
         uses: actions/download-artifact@v4
         with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
           path: artifact_name
 
       - name: Read artifact name
@@ -341,7 +338,7 @@ jobs:
       - name: Upload model to HF
         if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
         env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
           ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
         run: |
           rm -f output/artifact_name.txt
@@ -367,7 +364,7 @@ jobs:
       - name: Generate DM metadata and upload to HF
         if: ${{ inputs.target == 'dm' }}
         env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
         run: |
           export PYTHONPATH=$(pwd)
           python3 -c "
@@ -484,29 +481,11 @@ jobs:
           print(f'Chunked {pkl} into {len(targets)} chunks')
           "
 
-      - name: Compile DM warp
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-
-          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-          MODEL_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld"
-          DM_SIZE=$(python3 -c "from openpilot.common.transformations.model import DM_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
-
-          for res in $(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')"); do
-            WARP_PKL="${MODEL_DIR}/models/dm_warp_${res}_tinygrad.pkl"
-            taskset -c 7 env ${TG_FLAGS} python3 ${MODEL_DIR}/compile_dm_warp.py \
-              --camera-resolution ${res} \
-              --warp-to ${DM_SIZE} \
-              --output ${WARP_PKL}
-          done
-
       - name: Prepare DM output
         run: |
           mkdir -p dm_output
           cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunk* dm_output/
           cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunkmanifest dm_output/
-          cp ${{ github.workspace }}/openpilot/selfdrive/modeld/models/dm_warp_* dm_output/
 
       - name: Upload DM artifact
         uses: actions/upload-artifact@v4

.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'
@@ -101,7 +101,7 @@ on:
         default: 'qcom'
         options:
           - qcom
-          - chestnut
+          - usbgpu
       hf_repo:
         description: 'Hugging Face dataset repository'
         required: false
@@ -109,7 +109,7 @@ on:
         default: 'sunnypilot/sunnypilot_models_v1'
 env:
   RECOMPILED_DIR: recompiled${{ inputs.recompiled_dir }}
-  JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == '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 +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 $JSON_FILE does not exist!"
@@ -155,8 +155,13 @@ jobs:
           python3 -c "
           import sys
           from huggingface_hub import HfApi
-          HfApi().repo_info(repo_id=sys.argv[1], repo_type='dataset')
+          try:
-          print(f'Success: Repo {sys.argv[1]} exists.')
+              api = HfApi()
+              api.repo_info(repo_id=sys.argv[1], repo_type='dataset')
+              print(f'Success: Repo {sys.argv[1]} exists.')
+          except Exception as e:
+              print('HF validation failed:', e)
+              sys.exit(1)
           " "${{ inputs.hf_repo }}"
 
       - name: Download artifact name file
@@ -187,7 +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/download-hf-model-chunks/action.yml

@@ -46,13 +46,6 @@ runs:
             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

.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'
 
 
@@ -102,7 +102,7 @@ jobs:
           cat $GITHUB_OUTPUT
       - run: |
           cd ${{ github.workspace }}/openpilot/openpilot
-          if [ "${{ inputs.target_hardware }}" != "chestnut" ]; then
+          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
@@ -121,7 +121,7 @@ jobs:
           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 }})
@@ -185,10 +185,10 @@ jobs:
           CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
 
           TG_FLAGS_QCOM="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-          if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
+          if [ "${{ inputs.target_hardware }}" == "usbgpu" ]; then
-            echo "CHESTNUT build"
+            echo "USBGPU build"
-            export CHESTNUT=1
+            export USBGPU=1
-            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1"
+            TG_FLAGS="DEBUG=1 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"

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

@@ -216,9 +216,6 @@ 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: ${{ steps.resolve.outputs.onnx_sha256 }}
     env:
@@ -231,10 +228,8 @@ jobs:
         run: |
           REF="${{ github.head_ref || github.ref_name }}"
 
-          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx?ref=${REF}" --jq '.sha')
+          ONNX_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          ONNX_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
           echo "ONNX hash: $ONNX_HASH"
-          [ -n "$ONNX_HASH" ] || { echo "::error::Failed to extract ONNX hash"; exit 1; }
           echo "onnx_sha256=$ONNX_HASH" >> $GITHUB_OUTPUT
 
           TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
@@ -243,7 +238,7 @@ jobs:
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
-            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
             TINYGRAD_MATCH=$(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)
@@ -257,35 +252,18 @@ jobs:
 
           echo "No matching model on HF — dispatching build"
           gh workflow run build-default-models.yaml --ref "$REF" -f target=big
-          sleep 10
 
-          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Polling HF for big model availability..."
-          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')
+            if check_defaults; then
-            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+              echo "Big model available on HF after $((i * 30))s"
-            echo "Poll $i/90: status=$STATUS conclusion=$CONCLUSION"
+              exit 0
-            if [ "$STATUS" = "completed" ]; then
-              if [ "$CONCLUSION" = "success" ]; then
-                echo "Build run succeeded, verifying HF..."
-                sleep 10
-                if check_defaults; then
-                  echo "Big model verified on HF"
-                  exit 0
-                fi
-                echo "::error::Build succeeded but model not found on HF"
-                exit 1
-              else
-                echo "::error::Build run failed with conclusion=$CONCLUSION"
-                exit 1
-              fi
             fi
+            echo "Poll $i/90: not yet available"
           done
 
-          echo "::error::Build run did not complete within 45 minutes"
+          echo "::error::Big model not available on HF after 45 minutes"
           exit 1
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -299,9 +277,6 @@ jobs:
   prepare_small_model:
     needs: [ prepare_strategy ]
     runs-on: ubuntu-24.04
-    concurrency:
-      group: prepare-small-model
-      cancel-in-progress: false
     outputs:
       driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
     env:
@@ -314,10 +289,8 @@ jobs:
         run: |
           REF="${{ 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/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          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=${REF}" --jq '.sha')
@@ -326,7 +299,7 @@ jobs:
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
-            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
             TINYGRAD_MATCH=$(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)
@@ -340,35 +313,18 @@ jobs:
 
           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 "Polling HF for model availability..."
-          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')
+            if check_defaults; then
-            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+              echo "Model available on HF after $((i * 30))s"
-            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
+              exit 0
-            if [ "$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
+            echo "Poll $i/60: not yet available"
           done
 
-          echo "::error::Small model build did not complete within 30 minutes"
+          echo "::error::Small driving model not available on HF after 30 minutes"
           exit 1
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -382,9 +338,6 @@ jobs:
   prepare_dm_model:
     needs: [ prepare_strategy ]
     runs-on: ubuntu-24.04
-    concurrency:
-      group: prepare-dm-model
-      cancel-in-progress: false
     outputs:
       dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
     env:
@@ -397,10 +350,8 @@ jobs:
         run: |
           REF="${{ 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/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          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=${REF}" --jq '.sha')
@@ -409,7 +360,7 @@ jobs:
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
-            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
             TINYGRAD_MATCH=$(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)
@@ -423,35 +374,18 @@ jobs:
 
           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 "Polling HF for DM model availability..."
-          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')
+            if check_defaults; then
-            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+              echo "DM model available on HF after $((i * 30))s"
-            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
+              exit 0
-            if [ "$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
+            echo "Poll $i/60: not yet available"
           done
 
-          echo "::error::DM model build did not complete within 30 minutes"
+          echo "::error::DM model not available on HF after 30 minutes"
           exit 1
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.gitmodules

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

launch_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

@@ -204,16 +204,11 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
   aTarget @5 :Float32;
   events @6 :List(OnroadEventSP.Event);
   e2eAlerts @7 :E2eAlerts;
-  accelController @8 :AccelController;
 
   struct DynamicExperimentalControl {
     state @0 :DynamicExperimentalControlState;
     enabled @1 :Bool;
     active @2 :Bool;
-    decelIntent @3 :Float32;
-    curveDetected @4 :Bool;
-    wantBlended @5 :Bool;
-    leadVeto @6 :Bool;
 
     enum DynamicExperimentalControlState {
       acc @0;
@@ -311,17 +306,6 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
     greenLightAlert @0 :Bool;
     leadDepartAlert @1 :Bool;
   }
-
-  struct AccelController {
-    enabled @0 :Bool;
-    active @1 :Bool;
-    profile @2 :Profile;
-    enum Profile {
-      eco @0;
-      normal @1;
-      sport @2;
-    }
-  }
 }
 
 struct OnroadEventSP @0xda96579883444c35 {
@@ -369,7 +353,6 @@ 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;
 

openpilot/common/hardware/comma/agnos.json

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

@@ -92,12 +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}},
@@ -136,9 +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}},
+    {"UsbGpuActive", {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}},
+    {"UsbGpuLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
-    {"ChestnutModelError", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
     {"Version", {PERSISTENT, STRING}},
 
     // --- sunnypilot params --- //
@@ -194,12 +187,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"StandstillTimer", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"TrueVEgoUI", {PERSISTENT | BACKUP, BOOL, "0"}},
 
-    // toyota specific params
-    {"ToyotaAutoHold", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"ToyotaEnhancedBsm", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"ToyotaTSS2Long", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"ToyotaDriveMode", {PERSISTENT | BACKUP, BOOL, "0"}},
-
     // MADS params
     {"Mads", {PERSISTENT | BACKUP, BOOL, "1"}},
     {"MadsMainCruiseAllowed", {PERSISTENT | BACKUP, BOOL, "1"}},
@@ -208,16 +195,15 @@ 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_ActiveBundleUSBGPU", {PERSISTENT, JSON}},
-    {"ModelManager_ActiveBundleChestnut", {PERSISTENT, JSON}},
     {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, JSON}},
     {"ModelManager_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
     {"ModelManager_DownloadRef", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
     {"ModelManager_Favs", {PERSISTENT | BACKUP, STRING}},
     {"ModelManager_LastSyncTime", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
-    {"ModelManager_LastSyncTime_Chestnut", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
+    {"ModelManager_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"}},
@@ -249,10 +235,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"DynamicExperimentalControl", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"BlindSpot", {PERSISTENT | BACKUP, BOOL, "0"}},
 
-    // Accel Controller profiles (Eco / Normal / Sport)
-    {"AccelPersonalityEnabled", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"AccelPersonality", {PERSISTENT | BACKUP, INT, "1"}},
-
     // sunnypilot model params
     {"CameraOffset", {PERSISTENT | BACKUP, FLOAT, "0.0"}},
     {"LagdToggle", {PERSISTENT | BACKUP, BOOL, "1"}},

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 %s -rf", 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", msgq_path.c_str()));
     unsetenv("OPENPILOT_PREFIX");
   }
 

openpilot/common/tests/test_params.py

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

openpilot/selfdrive/assets/icons_mici/chestnut_orange.png

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

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/car/card.py

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

openpilot/selfdrive/car/cruise.py

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

openpilot/selfdrive/controls/lib/drive_helpers.py

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

openpilot/selfdrive/controls/lib/longcontrol.py

@@ -7,8 +7,6 @@ from openpilot.selfdrive.modeld.constants import ModelConstants
 
 CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
 
-STOPPING_DECEL_RATE = 0.3  # m/s^2/s while trying to stop
-
 LongCtrlState = car.CarControl.Actuators.LongControlState
 
 
@@ -70,7 +68,7 @@ class LongControl:
       if output_accel > self.CP.stopAccel:
         output_accel = min(output_accel, 0.0)
         # TODO: can we just go straight to stopAccel?
-        output_accel -= STOPPING_DECEL_RATE * DT_CTRL
+        output_accel -= 1.0 * DT_CTRL  # m/s^2/s while trying to stop
       self.reset()
 
     else:  # LongCtrlState.pid

openpilot/selfdrive/controls/lib/longitudinal_planner.py

@@ -37,6 +37,7 @@ def get_coast_accel(pitch):
 
 def get_cruise_accel(e2e, v_cruise, v_ego, a_cruise_prev, angle_steers, CP, dt, accel_coast, allow_throttle):
   max_accel = ACCEL_MAX if e2e else get_max_accel(v_ego)
+
   if not e2e:
     a_total_max = np.interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
     a_y = v_ego ** 2 * angle_steers * CV.DEG_TO_RAD / (CP.steerRatio * CP.wheelbase)
@@ -83,8 +84,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     v_ego = sm['carState'].vEgo
     v_cruise_kph = min(sm['carState'].vCruise, V_CRUISE_MAX)
     v_cruise = v_cruise_kph * CV.KPH_TO_MS
-    force_decel = sm['controlsState'].forceDecel
+    if sm['controlsState'].forceDecel:
-    if force_decel:
       v_cruise = 0.0
 
     long_control_off = sm['controlsState'].longControlState == LongCtrlState.off
@@ -118,7 +118,6 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     self.mpc.set_weights(prev_accel_constraint, personality=sm['selfdriveState'].personality)
     self.mpc.set_cur_state(self.v_desired_filter.x, self.output_a_target)
     self.mpc.update(sm['radarState'], personality=sm['selfdriveState'].personality)
-    self.update_dec(sm)
 
     self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
     self.a_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.a_solution)
@@ -141,15 +140,9 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
 
     is_e2e = self.is_e2e(sm)
 
-    a_cruise_prev = self.a_cruise
+    self.a_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego,
-    gated_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego, a_cruise_prev, steer_angle_without_offset,
+                                     self.a_cruise, steer_angle_without_offset, self.CP, self.dt,
-                                    self.CP, self.dt, accel_coast, self.allow_throttle)
+                                     accel_coast, self.allow_throttle)
-    ungated_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego, a_cruise_prev, steer_angle_without_offset,
-                                      self.CP, self.dt, accel_coast, True)
-    self.a_cruise = self.arbitrate_cruise_candidate(
-      sm, gated_cruise, ungated_cruise, output_a_target_mpc, self.mpc.source,
-      allow_throttle=self.allow_throttle, e2e=is_e2e, force_decel=force_decel,
-    )
     cruise_should_stop = should_stop(v_ego, self.a_cruise)
 
     candidates = [(output_a_target_mpc, self.mpc.source, output_should_stop_mpc),
@@ -157,11 +150,9 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     if is_e2e:
       candidates.append((output_a_target_e2e, LongitudinalPlanSource.e2e, output_should_stop_e2e))
 
-    output_a_target, self.mpc.source, self.output_should_stop = min(candidates, key=lambda candidate: candidate[0])
+    output_a_target, self.mpc.source, _ = min(candidates, key=lambda c: c[0])
-    output_a_target = self.accel_controller.limit_accel(output_a_target, v_ego)
+    self.output_should_stop = any(should_stop for _, _, should_stop in candidates)
-
     self.output_a_target = np.clip(output_a_target, ACCEL_MIN, ACCEL_MAX)
-    self.accel_controller_active = self.is_accel_controller_active(force_decel, self.output_a_target)
 
     self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.output_a_target + a_prev) / 2.0
 

openpilot/selfdrive/controls/tests/test_longcontrol.py

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

openpilot/selfdrive/modeld/SConscript

@@ -7,9 +7,14 @@ from openpilot.common.file_chunker import chunk_file, get_chunk_targets, get_exi
 from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
 from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE, DM_INPUT_SIZE
 from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.selfdrive.modeld.helpers import TG_INPUT_DEVICES_PATH, chestnut_present, modeld_pkl_path
+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()
@@ -19,32 +24,30 @@ tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "
                   if 'pycache' not in x and os.path.isfile(os.path.join(tinygrad_root, x))]
 
 def estimate_pickle_max_size(onnx_size):
-  # QCOM programs for models with spatial recurrent features can approach 2x
+  return 1.2 * onnx_size  + 10 * 1024 * 1024  # 20% + 10MB is plenty
-  # the ONNX size. Overestimating only adds an empty trailing chunk.
-  return 2.0 * onnx_size + 10 * 1024 * 1024
 
 if arch == 'comma_arm64':
-  from openpilot.common.hardware import HARDWARE
-  camera = _os_fisheye if HARDWARE.get_device_type() == "mici" else _ar_ox_fisheye
-  camera_configs = [(camera.width, camera.height)]
   tg_backend = 'QCOM'
   tg_flags = f'DEV={tg_backend} IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1'
 else:
-  camera_configs = [(c.width, c.height) for c in (_ar_ox_fisheye, _os_fisheye)]
   tg_backend = 'CPU'
   tg_flags = f'DEV=CPU' if arch == 'Darwin' else 'DEV=CPU:LLVM'
 
 tg_devices = { # which device to put jit inputs to at runtime
+  'openpilot.selfdrive.modeld.modeld': {
+    'default': {'WARP_DEV': tg_backend, 'QUEUE_DEV': tg_backend},
+    'usbgpu': {'WARP_DEV': tg_backend, 'QUEUE_DEV': 'AMD'}
+  },
   'openpilot.selfdrive.modeld.dmonitoringmodeld': {
     'default': {'DEV': tg_backend}
   },
 }
 
-CHESTNUT = chestnut_present()
+USBGPU = usbgpu_present()
-if CHESTNUT:
+if USBGPU:
-  chestnut_tg_flags = 'DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1'
+  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:
@@ -71,11 +74,12 @@ model_w, model_h = MEDMODEL_INPUT_SIZE
 frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
 
 if not os.getenv('SKIP_TINYGRAD_COMPILE'):
-  for chestnut in [False, True] if CHESTNUT else [False]:
+  for usbgpu in [False, True] if USBGPU else [False]:
-    target_pkl_path = File(modeld_pkl_path(chestnut)).abspath
+    target_pkl_path = File(modeld_pkl_path(usbgpu)).abspath
-    file_prefix, cmd_flags = ('big_', chestnut_tg_flags) if chestnut else ('', tg_flags)
+    # 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)
+    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 '
@@ -100,14 +104,14 @@ if not os.getenv('SKIP_TINYGRAD_COMPILE'):
       chunk_file(pkl, chunks)
     def do_chunk(target, source, env, pkl=target_pkl_path, chunks=chunk_targets):
       chunk_file(pkl, chunks)
-    actions = Action(do_compile, "  [CHESTNUT] $TARGET") if chestnut else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
+    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(camera_res_args), Value(chunk_targets), chunker_file],
+      tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
       actions,
     )
-    if chestnut:
+    if usbgpu:
-      lenv.SideEffect(chestnut_lock, node)
+      lenv.SideEffect(usbgpu_lock, node)
 
 # get model metadata
 fn = File(f"models/dmonitoring_model").abspath
@@ -117,7 +121,7 @@ lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files + script_file
 
 dm_w, dm_h = DM_INPUT_SIZE
 compile_dm_warp_script = [File(f"{modeld_dir}/compile_dm_warp.py")]
-for cam_w, cam_h in camera_configs:
+for cam_w, cam_h in CAMERA_CONFIGS:
   dm_pkl_path = File(f"models/dm_warp_{cam_w}x{cam_h}_tinygrad.pkl").abspath
   cmd = (f'{tg_flags} {mac_brew_string} python3 {modeld_dir}/compile_dm_warp.py '
          f'--camera-resolution {cam_w}x{cam_h} --warp-to {dm_w}x{dm_h} '
@@ -139,4 +143,5 @@ def tg_compile(flags, model_name):
      Action(do_chunk, "  [CHUNK] $TARGET")],
   )
 
-tg_compile(tg_flags, 'dmonitoring_model')
+if not os.getenv('SKIP_TINYGRAD_COMPILE'):
+  tg_compile(tg_flags, 'dmonitoring_model')

openpilot/selfdrive/modeld/compile_modeld.py

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

openpilot/selfdrive/modeld/dmonitoringmodeld.py

@@ -29,7 +29,7 @@ class ModelState:
   output: np.ndarray
 
   def __init__(self, cam_w: int, cam_h: int):
-    self.DEV = get_tg_input_devices(PROCESS_NAME, chestnut=False)['DEV']
+    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']

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/helpers.py

@@ -7,20 +7,18 @@ 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'
-CHESTNUT_POWERED_VOLTAGE = 5000
-CHESTNUT_PCIE_READY = 0x78
 
 
-def get_tg_input_devices(process_name: str, chestnut: bool):
+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 chestnut else 'chestnut']
+    return json.load(f)[process_name]['default' if not usbgpu else 'usbgpu']
 
-def modeld_pkl_path(chestnut: bool):
+def modeld_pkl_path(usbgpu: bool):
-  prefix = 'big_' if chestnut else ''
+  prefix = 'big_' if usbgpu else ''
   return MODELS_DIR / f'{prefix}driving_tinygrad.pkl'
 
 def dump_oob(obj, f):
@@ -47,20 +45,16 @@ def load_oob(f):
       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:
+def usbgpu_compiled() -> bool:
-  return Path(get_manifest_path(modeld_pkl_path(chestnut=True))).is_file()
+  return Path(get_manifest_path(modeld_pkl_path(usbgpu=True))).is_file()
-
-
-def chestnut_ready(state) -> bool:
-  return state.supplyVoltage >= CHESTNUT_POWERED_VOLTAGE and not state.supplyFault and state.pcieLtssm == CHESTNUT_PCIE_READY

openpilot/selfdrive/modeld/modeld.py

@@ -1,11 +1,9 @@
 #!/usr/bin/env python3
-from collections.abc import Callable
-import ctypes
 from functools import cached_property
 import os
-os.environ['GMMU'] = '0' # for chestnut fast loading, noop for qcom
+os.environ['GMMU'] = '0' # for usbgpu fast loading, noop for qcom
+from tinygrad.tensor import Tensor
 from tinygrad.device import Device
-import usb1
 import struct
 import threading
 import time
@@ -28,17 +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, nv12_copy_size, MODELD_INPUTS
+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.common.hardware.usb import CHESTNUT_USB_IDS
 from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
-from openpilot.selfdrive.modeld.helpers import chestnut_present, chestnut_compiled, chestnut_ready, 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
@@ -83,37 +81,6 @@ class ChestnutState:
     self.valid = True
     self.sends = 0
     self.metrics = {}
-    self._asm_usb = None
-
-  def _close_asm_usb(self) -> None:
-    if self._asm_usb is not None:
-      self._asm_usb.close()
-      self._asm_usb = None
-
-  def _open_asm_usb(self):
-    context = usb1.USBContext()
-    for vendor_id, product_id in CHESTNUT_USB_IDS:
-      if (handle := context.openByVendorIDAndProductID(vendor_id, product_id, skip_on_error=True)) is not None:
-        return handle
-    context.close()
-
-  def _read_ina(self) -> tuple[int, int, bool]:
-    if "AMD" in Device._opened_devices and self._asm_usb is None:
-      try:
-        raw = Device["AMD"].iface.pci_dev.usb.usb.control_read(0xC0, 5)
-        return struct.unpack('<Hh?', bytes(raw))
-      except Exception:
-        pass
-    if self._asm_usb is None:
-      self._asm_usb = self._open_asm_usb()
-    if self._asm_usb is None:
-      raise usb1.USBErrorNoDevice
-    try:
-      raw = self._asm_usb.controlRead(0xC0, 0xC0, 0, 0, 5, timeout=100)
-    except usb1.USBError:
-      self._close_asm_usb()
-      raise
-    return struct.unpack('<Hh?', bytes(raw))
 
   @cached_property
   def power_limit(self) -> int:
@@ -127,10 +94,8 @@ class ChestnutState:
     if self.big and "AMD" in Device._opened_devices and self.sends % 100 == 1:
       try:
         smu = Device["AMD"].iface.dev_impl.smu
-        metrics_t = smu.smu_mod.SmuMetricsExternal_t
         smu._send_msg(smu.smu_mod.PPSMC_MSG_TransferTableSmu2Dram, smu.smu_mod.TABLE_SMU_METRICS, timeout=100)
-        metrics_buf = bytearray(smu.adev.vram.view(smu.driver_table_paddr, ctypes.sizeof(metrics_t))[:])
+        metrics = smu.read_table(smu.smu_mod.SmuMetricsExternal_t, smu.smu_mod.TABLE_SMU_METRICS).SmuMetrics
-        metrics = metrics_t.from_buffer(metrics_buf).SmuMetrics
         self.metrics = {'tempC': metrics.AvgTemperature[smu.smu_mod.TEMP_HOTSPOT],
                         'memoryTempC': metrics.AvgTemperature[smu.smu_mod.TEMP_MEM],
                         'powerDrawW': metrics.AverageSocketPower,
@@ -149,15 +114,13 @@ class ChestnutState:
         setattr(state, k, v)
 
     asm_valid = False
-    try:
-      # ASM runs on USB-C power, these still read without a gpu
-      state.supplyVoltage, state.supplyCurrent, state.supplyFault = self._read_ina()
-      asm_valid = True
-    except Exception:
-      pass
     if "AMD" in Device._opened_devices:
       try:
-        state.pcieLtssm = Device["AMD"].iface.pci_dev.usb.read(0xB450, 1)[0]
+        # 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
 
@@ -178,34 +141,42 @@ class FrameMeta:
 class ModelState(ModelStateBase):
   prev_desire: np.ndarray  # for tracking the rising edge of the pulse
 
-  def __init__(self, cam_w: int, cam_h: int, chestnut: bool):
+  def __init__(self, cam_w: int, cam_h: int, usbgpu: bool):
     ModelStateBase.__init__(self)
-    jits = load_oob(open_file_chunked(modeld_pkl_path(chestnut)))
+    input_devices = get_tg_input_devices(PROCESS_NAME, usbgpu)
-    input_devices = jits['input_devices']
+    self.WARP_DEV, self.QUEUE_DEV = input_devices['WARP_DEV'], input_devices['QUEUE_DEV']
-    self.model_device = input_devices['model']
+    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
 
     self.frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
-    self.frame_copy_size = nv12_copy_size(*get_nv12_info(cam_w, cam_h)[:3])
+    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
-    self.input_queues, self.npy, self.frame_views = make_input_queues(
+    self.full_frames: dict[str, Tensor] = {}
-      self.input_shapes, self.frame_skip, device=self.model_device, frame_copy_size=self.frame_copy_size)
+    self._blob_cache: dict[tuple[str, int], Tensor] = {}
     self.parser = Parser()
-    self.run_model = jits['run_model'][(cam_w,cam_h)]
+    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]:
     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]:
+          inputs: dict[str, np.ndarray]) -> dict[str, np.ndarray] | None:
-    for key, buf in bufs.items():
+    for key in bufs.keys():
-      np.copyto(self.frame_views[key], np.frombuffer(buf.data, dtype=np.uint8, count=self.frame_copy_size))
+      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
@@ -216,12 +187,16 @@ class ModelState(ModelStateBase):
     self.npy['tfm'][:,:] = transforms['img'][:,:]
     self.npy['big_tfm'][:,:] = transforms['big_img'][:,:]
 
-    outs, = self.run_model(**{k: self.input_queues[k] for k in MODELD_INPUTS})
+    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'])
-    if after_enqueue is not None:
+
-      after_enqueue()
+    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.chestnut and not np.all(np.isfinite(model_output)):
+    if self.usbgpu and not np.all(np.isfinite(model_output)):
-      raise RuntimeError("model output not finite")
+      # 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']]
 
@@ -230,37 +205,25 @@ class ModelState(ModelStateBase):
     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.input_queues, self.npy, self.frame_views = make_input_queues(
+    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
-      self.input_shapes, self.frame_skip, device=self.model_device, frame_copy_size=self.frame_copy_size)
     self.prev_desire[:] = 0
+    self.full_frames.clear()
+    self._blob_cache.clear()
 
 
 def main(demo=False):
   cloudlog.warning("modeld init")
 
-  chestnut_available = chestnut_present() and chestnut_compiled()
+  USBGPU = usbgpu_present() and usbgpu_compiled()
-  CHESTNUT = False
+  if USBGPU:
-  if chestnut_available:
-    poller = messaging.Poller()
-    sock = messaging.sub_sock("chestnutState", poller=poller, conflate=True)
-    deadline = time.monotonic() + 4. / SERVICE_LIST['deviceState'].frequency
-    while not CHESTNUT and (remaining := deadline - time.monotonic()) > 0.:
-      if not poller.poll(round(remaining * 1000)):
-        break
-      msg = messaging.recv_one_or_none(sock)
-      CHESTNUT = msg is not None and msg.valid and chestnut_ready(msg.chestnutState)
-  if CHESTNUT:
     os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
   params = Params()
-  params.put_bool("ChestnutLoading", CHESTNUT)
+  params.put_bool("UsbGpuLoading", USBGPU)
-  if chestnut_available and not CHESTNUT:
+  params.remove("UsbGpuActive")
-    params.put_bool("ChestnutActive", False)
-  else:
-    params.remove("ChestnutActive")
 
   config_realtime_process(7, 54)
 
@@ -290,7 +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
@@ -304,27 +267,23 @@ def main(demo=False):
     loader.start()
     loader.join(BIG_MODEL_TIMEOUT)
     model = big_model
-    if model is None:
+    params.put_bool("UsbGpuActive", model is not None)
-      params.put_bool("ChestnutModelError", True)
-    params.put_bool("ChestnutActive", model is not None)
-    if model is not None:
-      params.remove("ChestnutModelError")
 
-  small_model = ModelState(vipc_client_main.width, vipc_client_main.height, False) if model is None or 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", "modelDataV2SP"] + (["chestnutState"] 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 = ChestnutState(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)
@@ -434,16 +393,13 @@ def main(demo=False):
 
     mt1 = time.perf_counter()
     try:
-      send_chestnut = (chestnut_state is not None and
+      model_output = model.run(bufs, transforms, inputs)
-                       run_count % round(ModelConstants.MODEL_RUN_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0)
-      model_output = model.run(bufs, transforms, inputs, chestnut_state.send if send_chestnut else None)
     except Exception:
-      if not params.get_bool("ChestnutActive"):
+      if not params.get_bool("UsbGpuActive"):
         raise
       # fallback to small model
       cloudlog.exception("big model failed, fall back to small")
-      params.put_bool("ChestnutModelError", True)
+      params.put_bool("UsbGpuActive", False)
-      params.put_bool("ChestnutActive", False)
       assert small_model is not None
       model = small_model
       if chestnut_state is not None:
@@ -463,17 +419,18 @@ 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]
       r_lane_change_prob = desire_state[log.Desire.laneChangeRight]
       lane_change_prob = l_lane_change_prob + r_lane_change_prob
-      mdv2sp_send = messaging.new_message('modelDataV2SP')
+      DH.update(sm['carState'], sm['carControl'].latActive, lane_change_prob)
-      left_edge, right_edge = RELC.update_and_fill(modelv2_send.modelV2, mdv2sp_send.modelDataV2SP, v_ego)
-      DH.update(sm['carState'], sm['carControl'].latActive, lane_change_prob, left_edge, right_edge)
       modelv2_send.modelV2.meta.laneChangeState = DH.lane_change_state
       modelv2_send.modelV2.meta.laneChangeDirection = DH.lane_change_direction
+
+      mdv2sp_send = 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)
@@ -484,6 +441,10 @@ def main(demo=False):
       pm.send('modelDataV2SP', mdv2sp_send)
     last_vipc_frame_id = meta_main.frame_id
 
+    if chestnut_state is not None and run_count % round(ModelConstants.MODEL_RUN_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0:
+      chestnut_state.send()
+
+
 if __name__ == "__main__":
   try:
     import argparse

openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx

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

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.setIgnitionLine(health.ignition_line_pkt);
-  ps.setIgnitionCan((health.flags_pkt & HEALTH_FLAG_IGNITION_CAN) != 0U);
+  ps.setIgnitionCan(health.ignition_can_pkt);
-  ps.setControlsAllowed((health.flags_pkt & HEALTH_FLAG_CONTROLS_ALLOWED) != 0U);
+  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.setPowerSaveEnabled((bool)(health.power_save_enabled_pkt));
-  ps.setHeartbeatLost((health.flags_pkt & HEALTH_FLAG_HEARTBEAT_LOST) != 0U);
+  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);
   }
 

openpilot/selfdrive/pandad/spi.cc

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

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")
+    big_active = self.params.get("UsbGpuActive")
-    chestnut_present = self.sm['deviceState'].chestnutPresent
+    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

openpilot/selfdrive/test/longitudinal_maneuvers/plant.py

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

openpilot/selfdrive/test/process_replay/migration.py

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

@@ -33,9 +33,9 @@ MODEL_REPLAY_BUCKET="model_replay_master"
 GITHUB = GithubUtils(API_TOKEN, DATA_TOKEN)
 
 EXEC_TIMINGS = [
-  # model, instant max, average max, chestnut average max
+  # model, instant max, average max
-  ("modelV2", 0.05, 0.03, 0.05),
+  ("modelV2", 0.05, 0.028),
-  ("driverStateV2", 0.05, 0.018, 0.018),
+  ("driverStateV2", 0.05, 0.018),
 ]
 
 def get_log_fn(test_route, ref="master"):
@@ -169,13 +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")
 
   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:
+  for (s, instant_max, avg_max) in EXEC_TIMINGS:
-    avg_max = chestnut_avg_max if chestnut else avg_max
     ts = [getattr(m, s).modelExecutionTime for m in msgs if m.which() == s]
     # TODO some init can happen in first iteration
     ts = ts[1:]

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

@@ -1,7 +1,7 @@
 import time
 import pyray as rl
 
-from openpilot.system.ui.lib.application import gui_app, FontWeight, 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=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                       alignment_vertical=TextAlignmentVertical.MIDDLE)
+                                       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/settings/toggles.py

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

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

@@ -1,5 +1,4 @@
 import datetime
-import math
 import time
 
 from openpilot.cereal import log
@@ -9,8 +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.system.ui.lib.application import gui_app, FontWeight, MousePos
-from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
+from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.common.version import RELEASE_BRANCHES
 
 HEAD_BUTTON_FONT_SIZE = 40
@@ -70,8 +69,8 @@ class AlertsPill(Widget):
 
       count_rect = rl.Rectangle(self.rect.x + self.COUNT_OFFSET, self.rect.y, pill_w - self.COUNT_OFFSET, pill_h)
       gui_label(count_rect, str(alert_count), font_size=36,
-                alignment=TextAlignment.CENTER,
+                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                alignment_vertical=TextAlignmentVertical.MIDDLE)
+                alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
 
 
 class NetworkIcon(Widget):
@@ -140,10 +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._egpu_icon = IconWidget("icons_mici/egpu_green.png", (50, 37))
-    self._chestnut_icon = IconWidget("icons_mici/chestnut_green.png", (68, 40))
+    self._egpu_icon_gray = IconWidget("icons_mici/egpu_gray.png", (50, 37))
-    self._chestnut_loading_icon = IconWidget("icons_mici/chestnut.png", (68, 40))
-    self._chestnut_failed_icon = IconWidget("icons_mici/chestnut_orange.png", (68, 40))
     self._mic_icon = IconWidget("icons_mici/microphone.png", (32, 46))
     self._body_icon = IconWidget("icons_mici/body.png", (54, 37))
 
@@ -153,15 +150,13 @@ class MiciHomeLayout(Widget):
       IconWidget("icons_mici/settings.png", (48, 48), opacity=0.9),
       NetworkIcon(),
       self._experimental_icon,
-      self._usb_icon,
+      self._egpu_icon,
-      self._chestnut_icon,
+      self._egpu_icon_gray,
-      self._chestnut_loading_icon,
-      self._chestnut_failed_icon,
       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)
@@ -252,20 +247,12 @@ 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()
+      self._set_egpu_visibility()
     else:
-      self._usb_icon.set_visible(usb_connected and usb_unknown)
+      self._egpu_icon.set_visible(ui_state.sm["deviceState"].chestnutPresent and ui_state.usbgpu_compiled)
-      self._chestnut_icon.set_visible(not usb_unknown and chestnut_state not in
+      self._egpu_icon_gray.set_visible(ui_state.sm["deviceState"].chestnutPresent and not ui_state.usbgpu_compiled)
-                                      (ChestnutState.LOADING, ChestnutState.UNCOMPILED, ChestnutState.FAILED) and
-                                      (usb_connected or chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE)))
-      self._chestnut_loading_icon.set_visible(not usb_unknown and chestnut_state == ChestnutState.LOADING)
-      self._chestnut_loading_icon.set_opacity(0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0)))
-      self._chestnut_failed_icon.set_visible(not usb_unknown and chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
     self._mic_icon.set_visible(ui_state.recording_audio)
     self._body_icon.set_visible(bool(ui_state.is_body))
 

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

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

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

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

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

@@ -4,7 +4,7 @@ import pyray as rl
 from collections.abc import Callable
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.qrcode import make_texture
-from openpilot.system.ui.lib.application import FontWeight, gui_app, 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/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):
@@ -241,9 +232,8 @@ class BranchSelectPage(NavScroller):
 
 
 class TargetBranchButton(BigButton):
-  def __init__(self, check_update_btn: CheckUpdateButton):
+  def __init__(self):
     super().__init__("target branch", ui_state.params.get("UpdaterTargetBranch") or "")
-    self._check_update_btn = check_update_btn
     self.set_click_callback(self._on_click)
     self.set_visible(not ui_state.params.get_bool("IsTestedBranch"))
     self.set_enabled(lambda: ui_state.is_offroad())
@@ -256,15 +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):
@@ -278,11 +265,10 @@ class SoftwareLayoutMici(NavScroller):
                                                         gui_app.texture("icons_mici/settings/device/uninstall.png", 64, 64),
                                                         uninstall_openpilot_callback, exit_on_confirm=False)
 
-    check_update_btn = CheckUpdateButton()
     self._scroller.add_widgets([
       SoftwareInfoLayoutMici(),
-      check_update_btn,
+      CheckUpdateButton(),
       InstallUpdateButton(),
-      TargetBranchButton(check_update_btn),
+      TargetBranchButton(),
       uninstall_openpilot_btn,
     ])

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

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

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

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

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

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

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

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

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

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

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

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

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

@@ -6,7 +6,7 @@ from collections.abc import Callable
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets.scroller import DO_ZOOM
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
 from openpilot.common.filter_simple import BounceFilter
 
 if TYPE_CHECKING:
@@ -125,10 +125,10 @@ class BigButton(Widget):
     self._rotate_icon_t: float | None = None
 
     self._label = UnifiedLabel(text, font_size=self._get_label_font_size(), font_weight=FontWeight.BOLD,
-                               text_color=LABEL_COLOR, alignment_vertical=TextAlignmentVertical.BOTTOM, scroll=scroll,
+                               text_color=LABEL_COLOR, alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM, scroll=scroll,
                                line_height=0.9)
     self._sub_label = UnifiedLabel(value, font_size=COMPLICATION_SIZE, font_weight=FontWeight.ROMAN,
-                                   text_color=COMPLICATION_GREY, alignment_vertical=TextAlignmentVertical.BOTTOM)
+                                   text_color=COMPLICATION_GREY, alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
     self._update_label_layout()
 
     self._load_images()
@@ -167,9 +167,9 @@ class BigButton(Widget):
   def _update_label_layout(self):
     self._label.set_font_size(self._get_label_font_size())
     if self.value:
-      self._label.set_alignment_vertical(TextAlignmentVertical.TOP)
+      self._label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP)
     else:
-      self._label.set_alignment_vertical(TextAlignmentVertical.BOTTOM)
+      self._label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
 
   def set_text(self, text: str):
     self.text = text
@@ -356,8 +356,8 @@ class GreyBigButton(BigButton):
     self._sub_label.set_font_size(36)
     self._sub_label.set_text_color(rl.Color(255, 255, 255, int(255 * 0.9)))
     self._sub_label.set_font_weight(FontWeight.DISPLAY_REGULAR)
-    self._sub_label.set_alignment_vertical(TextAlignmentVertical.MIDDLE if not self._label.text else
+    self._sub_label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE if not self._label.text else
-                                           TextAlignmentVertical.BOTTOM)
+                                           rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
     self._sub_label.set_line_height(0.95)
 
   @property
@@ -383,18 +383,13 @@ class BigMultiParamToggle(BigMultiToggle):
     self._load_value()
 
   def _load_value(self):
-    value = self._params.get(self._param, return_default=True)
+    self.set_value(self._options[self._params.get(self._param) or 0])
-    index = value if isinstance(value, int) else 0
-    self.set_value(self._options[max(0, min(index, len(self._options) - 1))])
 
   def _handle_mouse_release(self, mouse_pos: MousePos):
     super()._handle_mouse_release(mouse_pos)
     new_idx = self._options.index(self.value)
     self._params.put(self._param, new_idx)
 
-  def refresh(self):
-    self._load_value()
-
 
 class BigParamControl(BigToggle):
   def __init__(self, text: str, param: str, toggle_callback: Callable | None = None):

openpilot/selfdrive/ui/onroad/alert_renderer.py

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

openpilot/selfdrive/ui/onroad/cabin_camera_dialog.py

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

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

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

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

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

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

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

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

@@ -62,14 +62,14 @@ class ModelsLayout(Widget):
     self.big_model_item = ListItemSP(
       title=tr("Big Model"),
       action_item=ScrollingButtonAction(tr("SELECT")),
-      callback=lambda: self._open_source_dialog("chestnut")
+      callback=lambda: self._open_source_dialog("usbgpu")
     )
 
     self.download_item = download_status_item(lambda: tr("Download") if self._downloading else tr("Model Status"))
 
     self.refresh_item = button_item(tr("Refresh Model List"), tr("REFRESH"), "",
                                     lambda: (ui_state.params.put("ModelManager_LastSyncTime", 0),
-                                             ui_state.params.put("ModelManager_LastSyncTime_Chestnut", 0),
+                                             ui_state.params.put("ModelManager_LastSyncTime_USBGPU", 0),
                                              gui_app.push_widget(alert_dialog(tr("Fetching Latest Models")))))
 
     self.clear_cache_item = ListItemSP(
@@ -177,14 +177,14 @@ class ModelsLayout(Widget):
     big_state = big_model_state()
     carry_source, carry_internal, _ = carrying_model()
     segments = []
-    for source, label in (("qcom", tr("small")), ("chestnut", tr("big"))):
+    for source, label in (("qcom", tr("small")), ("usbgpu", tr("big"))):
       if segments:
         segments.append(("|", rl.GRAY, None, None))
       bundle = get_selected_bundle(ui_state.params, source)
       name = bundle.internalName if bundle else default_model_name(source)
       color = ON_COLOR if (source == carry_source and name == carry_internal) else rl.LIGHTGRAY
       name = "● " + name
-      if source == "chestnut":
+      if source == "usbgpu":
         if big_state == 'failed':
           color = rl.RED
         elif big_state == 'loading':
@@ -208,10 +208,10 @@ class ModelsLayout(Widget):
     """The failover story for the Model Status row. One-way big -> small, and the
     fallback is runner-matched: a Default big can only fall back to the Default
     small (stock modeld), a custom big has no automatic fallback yet."""
-    if not ui_state.chestnut_present:
+    if not ui_state.usbgpu:
       return ""
-    big_bundle = get_selected_bundle(ui_state.params, "chestnut")
+    big_bundle = get_selected_bundle(ui_state.params, "usbgpu")
-    big_name = big_bundle.internalName if big_bundle else default_model_name("chestnut")
+    big_name = big_bundle.internalName if big_bundle else default_model_name("usbgpu")
     big_is_default = big_bundle is None
     fallback_name = default_model_name("qcom")
     state = big_model_state()
@@ -225,7 +225,7 @@ class ModelsLayout(Widget):
       return tr("Getting the big model ready.")
     if big_is_default:
       return tr("{} will drive. If it fails during a drive, {} takes over until the next drive.").format(big_name, fallback_name)
-    return tr("{} will drive when the chestnut is ready.").format(big_name)
+    return tr("{} will drive when the eGPU is ready.").format(big_name)
 
   @staticmethod
   def _download_row_state(progresses, name: str) -> dict:
@@ -261,7 +261,7 @@ class ModelsLayout(Widget):
       ui_state.params.put("ModelManager_DownloadRef", selected_bundle.ref)
 
   def _resolve_selected_bundle(self, ref):
-    source_bundles = {source: bundles_for_source(source) for source in ("qcom", "chestnut")}
+    source_bundles = {source: bundles_for_source(source) for source in ("qcom", "usbgpu")}
     resolved = resolve_bundle_by_ref(ref, source_bundles)
     return resolved[0] if resolved else None
 
@@ -329,7 +329,7 @@ class ModelsLayout(Widget):
     self._handle_bundle_download_progress()
 
     carry_source, _, carry_display = carrying_model()
-    for item, item_source in ((self.small_model_item, "qcom"), (self.big_model_item, "chestnut")):
+    for item, item_source in ((self.small_model_item, "qcom"), (self.big_model_item, "usbgpu")):
       bundle = get_selected_bundle(ui_state.params, item_source)
       name = bundle.displayName if bundle else default_model_name(item_source)
       color = ON_COLOR if (item_source == carry_source and name == carry_display) else style.ITEM_TEXT_VALUE_COLOR

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

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

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

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

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

@@ -9,7 +9,7 @@ import math
 import pyray as rl
 import time
 from dataclasses import dataclass
-from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
+from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.sunnypilot.sunnylink.api import UNREGISTERED_SUNNYLINK_DONGLE_ID
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.lib.multilang import tr_noop
@@ -21,8 +21,8 @@ METRIC_MARGIN = 30
 METRIC_START_Y = 300
 HOME_BTN = rl.Rectangle(60, 860, 180, 180)
 
-CHESTNUT_ICON_WIDTH = 180
+EGPU_ICON_WIDTH = 180
-CHESTNUT_ICON_HEIGHT = 133
+EGPU_ICON_HEIGHT = 133
 
 
 # Color scheme
@@ -59,9 +59,10 @@ class MetricData:
 class SidebarSP:
   def __init__(self):
     self._sunnylink_status = MetricData(tr_noop("SUNNYLINK"), tr_noop("OFFLINE"), Colors.WARNING)
-    self._chestnut_green_img = gui_app.texture("icons_mici/chestnut_green.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)
+    self._egpu_green_img = gui_app.texture("icons_mici/egpu_green.png", EGPU_ICON_WIDTH, EGPU_ICON_HEIGHT)
-    self._chestnut_default_img = gui_app.texture("icons_mici/chestnut.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)
+    self._egpu_default_img = gui_app.texture("icons_mici/egpu.png", EGPU_ICON_WIDTH, EGPU_ICON_HEIGHT)
-    self._chestnut_orange_img = gui_app.texture("icons_mici/chestnut_orange.png", CHESTNUT_ICON_WIDTH, CHESTNUT_ICON_HEIGHT)
+    self._egpu_orange_img = gui_app.texture("icons_mici/egpu_orange.png", EGPU_ICON_WIDTH, EGPU_ICON_HEIGHT)
+    self._egpu_gray_img = gui_app.texture("icons_mici/egpu_gray.png", EGPU_ICON_WIDTH, EGPU_ICON_HEIGHT)
 
   def _update_sunnylink_status(self):
     if not ui_state.params.get_bool("SunnylinkEnabled"):
@@ -89,17 +90,22 @@ class SidebarSP:
 
   def _get_home_icon(self, default_img: rl.Texture) -> tuple[rl.Texture, rl.Vector2, float]:
     default_pos = rl.Vector2(HOME_BTN.x, HOME_BTN.y)
-    state = ui_state.chestnut_state
+    if not ui_state.sm["deviceState"].chestnutPresent:
-    if state == ChestnutState.DISCONNECTED:
       return default_img, default_pos, 1.0
 
-    if state == ChestnutState.LOADING:
+    big_model_selected = ui_state.usbgpu_compiled or ui_state.model_runner_tinygrad
-      icon = self._chestnut_default_img
+    big_model_failed = ui_state.started and ui_state.big_model_failed
+    loading = ui_state.usbgpu_loading or (big_model_selected and ui_state.started and ui_state.usbgpu_active is None)
+
+    if loading:
+      icon = self._egpu_default_img
       opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
-    elif state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED):
+    elif big_model_selected and big_model_failed:
-      icon, opacity = self._chestnut_orange_img, 1.0
+      icon, opacity = self._egpu_orange_img, 1.0
+    elif big_model_selected:
+      icon, opacity = self._egpu_green_img, 1.0
     else:
-      icon, opacity = self._chestnut_green_img, 1.0
+      icon, opacity = self._egpu_gray_img, 1.0
 
     x = HOME_BTN.x + (HOME_BTN.width - icon.width) / 2
     y = HOME_BTN.y + (HOME_BTN.height - icon.height) / 2

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

@@ -9,8 +9,9 @@ import math
 import pyray as rl
 
 from openpilot.selfdrive.ui.mici.layouts.home import MiciHomeLayout
-from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
+from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.system.ui.lib.application import FontWeight
+from openpilot.system.ui.widgets.icon_widget import IconWidget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 
 
@@ -18,16 +19,35 @@ class MiciHomeLayoutSP(MiciHomeLayout):
   def __init__(self):
     super().__init__()
     self._openpilot_label = UnifiedLabel("sunnypilot", font_size=88, font_weight=FontWeight.AUDIOWIDE, max_width=480, wrap_text=False)
+    self._egpu_icon_default = IconWidget("icons_mici/egpu.png", (50, 37))
+    self._egpu_icon_default.set_visible(False)
+    self._egpu_icon_orange = IconWidget("icons_mici/egpu_orange.png", (50, 37))
+    self._egpu_icon_orange.set_visible(False)
+    gray_idx = self._status_bar_layout.widgets.index(self._egpu_icon_gray)
+    self._status_bar_layout.widgets.insert(gray_idx + 1, self._egpu_icon_default)
+    self._status_bar_layout.widgets.insert(gray_idx + 2, self._egpu_icon_orange)
 
-  def _set_chestnut_visibility(self):
+  def _set_egpu_visibility(self):
-    usb_connected = ui_state.usb_connected
+    chestnut = ui_state.sm["deviceState"].chestnutPresent
-    usb_unknown = ui_state.usb_unknown
+    if not chestnut:
-    chestnut_state = ui_state.chestnut_state
+      self._egpu_icon.set_visible(False)
-    loading = chestnut_state == ChestnutState.LOADING
+      self._egpu_icon_default.set_visible(False)
+      self._egpu_icon_orange.set_visible(False)
+      self._egpu_icon_gray.set_visible(False)
+      return
 
-    self._usb_icon.set_visible(usb_connected and usb_unknown)
+    big_model_selected = ui_state.usbgpu_compiled or ui_state.model_runner_tinygrad
-    self._chestnut_loading_icon.set_opacity(0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0)))
+    big_model_failed = ui_state.started and ui_state.big_model_failed
-    self._chestnut_loading_icon.set_visible(not usb_unknown and loading)
+    loading = ui_state.usbgpu_loading or (big_model_selected and ui_state.started and ui_state.usbgpu_active is None)
-    self._chestnut_icon.set_visible(not usb_unknown and not loading and
+
-                                    chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE))
+    if loading:
-    self._chestnut_failed_icon.set_visible(not usb_unknown and chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
+      self._egpu_icon_default._opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
+      self._egpu_icon_default.set_visible(True)
+      self._egpu_icon.set_visible(False)
+      self._egpu_icon_orange.set_visible(False)
+      self._egpu_icon_gray.set_visible(False)
+    else:
+      self._egpu_icon_default.set_visible(False)
+      self._egpu_icon.set_visible(big_model_selected and not big_model_failed)
+      self._egpu_icon_orange.set_visible(big_model_selected and big_model_failed)
+      self._egpu_icon_gray.set_visible(not big_model_selected)

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

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

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

@@ -27,14 +27,14 @@ def _model_info() -> tuple[str, str, str]:
   state = big_model_state()
   _, _, carry_display = carrying_model()
   if carry_display is None:
-    big = get_selected_bundle(ui_state.params, "chestnut")
+    big = get_selected_bundle(ui_state.params, "usbgpu")
-    carry_display = big.displayName if big else default_model_name("chestnut")
+    carry_display = big.displayName if big else default_model_name("usbgpu")
   active_text = (carry_display or active_name).lower()
   if state == 'failed':
     return active_text, tr("big model"), tr("unavailable")
   if state == 'loading':
     return active_text, tr("big model"), tr("getting ready")
-  header = tr("small model") if source == "chestnut" else tr("big model")
+  header = tr("small model") if source == "usbgpu" else tr("big model")
   return active_text, header, other_name.lower()
 
 
@@ -113,7 +113,7 @@ class ModelsLayoutMici(NavScroller):
 
     hardware_btns = []
     active = active_source()
-    for source, label in (("qcom", tr("small models")), ("chestnut", tr("big models"))):
+    for source, label in (("qcom", tr("small models")), ("usbgpu", tr("big models"))):
       bundle = get_selected_bundle(ui_state.params, source)
       value = (bundle.internalName if bundle else default_model_name(source)).lower()
       if source == active:

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

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

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

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

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

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

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

@@ -7,6 +7,7 @@ See the LICENSE.md file in the root directory for more details.
 import pyray as rl
 
 from openpilot.selfdrive.ui.mici.onroad.hud_renderer import HudRenderer
+from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.selfdrive.ui.sunnypilot.onroad.blind_spot_indicators import BlindSpotIndicators
 
 
@@ -21,6 +22,8 @@ class HudRendererSP(HudRenderer):
 
   def _render(self, rect: rl.Rectangle) -> None:
     super()._render(rect)
+    if ui_state.usbgpu and not ui_state.usbgpu_compiled and ui_state.model_runner_tinygrad:
+      self._draw_model_source(rect)
     self.blind_spot_indicators.render(rect)
 
   def _has_blind_spot_detected(self) -> bool:

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

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

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

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

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

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

openpilot/selfdrive/ui/sunnypilot/model_info.py

@@ -4,15 +4,15 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
-from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
+from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.sunnypilot.models.fetcher import get_cached_bundles
 from openpilot.sunnypilot.models.helpers import get_active_source, get_selected_bundle, resolve_bundle_by_ref
 from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL, DEFAULT_MODEL
 
 
 def active_source() -> str:
-  return get_active_source(chestnut=ui_state.chestnut_present,
+  return get_active_source(usbgpu=ui_state.usbgpu,
-                           chestnut_active=ui_state.chestnut_active, chestnut_loading=ui_state.chestnut_loading,
+                           usbgpu_active=ui_state.usbgpu_active, usbgpu_loading=ui_state.usbgpu_loading,
                            offroad=ui_state.is_offroad())
 
 
@@ -23,7 +23,7 @@ def bundles_for_source(source: str):
 
 
 def default_model(source: str) -> str:
-  return DEFAULT_BIG_MODEL if source == 'chestnut' else DEFAULT_MODEL
+  return DEFAULT_BIG_MODEL if source == 'usbgpu' else DEFAULT_MODEL
 
 
 def default_model_name(source: str) -> str:
@@ -31,10 +31,13 @@ def default_model_name(source: str) -> str:
 
 
 def big_model_state() -> str | None:
-  """'failed' | 'loading' | None, from the same state the icons render."""
+  """'failed' | 'loading' | None, mirroring the sidebar's detection (#1969)."""
-  return {ChestnutState.UNCOMPILED: 'failed',
+  if ui_state.started and ui_state.usbgpu and ui_state.big_model_failed:
-          ChestnutState.FAILED: 'failed',
+    return 'failed'
-          ChestnutState.LOADING: 'loading'}.get(ui_state.chestnut_state)
+  big_selected = ui_state.usbgpu_compiled or ui_state.model_runner_tinygrad
+  if ui_state.usbgpu_loading or (big_selected and ui_state.started and ui_state.usbgpu_active is None):
+    return 'loading'
+  return None
 
 
 def carrying_model() -> tuple[str | None, str | None, str | None]:
@@ -42,14 +45,14 @@ def carrying_model() -> tuple[str | None, str | None, str | None]:
   when a Default big cannot carry, stock modeld runs the Default small, never the
   small slot's pick; a custom big has no automatic fallback yet -> (None, None, None)."""
   source = active_source()
-  if source == "chestnut":
+  if source == "usbgpu":
-    bundle = get_selected_bundle(ui_state.params, "chestnut")
+    bundle = get_selected_bundle(ui_state.params, "usbgpu")
     if bundle:
-      return "chestnut", bundle.internalName, bundle.displayName
+      return "usbgpu", bundle.internalName, bundle.displayName
-    name = default_model_name("chestnut")
+    name = default_model_name("usbgpu")
-    return "chestnut", name, name
+    return "usbgpu", name, name
-  if ui_state.chestnut_present:
+  if ui_state.usbgpu:
-    if get_selected_bundle(ui_state.params, "chestnut") is None:
+    if get_selected_bundle(ui_state.params, "usbgpu") is None:
       name = default_model_name("qcom")
       return "qcom", name, name
     return None, None, None
@@ -63,7 +66,7 @@ def carrying_model() -> tuple[str | None, str | None, str | None]:
 def queued_name(current_ref) -> str | None:
   ref = ui_state.params.get("ModelManager_DownloadRef")
   if ref and ref != current_ref:
-    source_bundles = {source: bundles_for_source(source) for source in ("qcom", "chestnut")}
+    source_bundles = {source: bundles_for_source(source) for source in ("qcom", "usbgpu")}
     if resolved := resolve_bundle_by_ref(ref, source_bundles):
       return resolved[0].internalName
   return None
@@ -76,7 +79,7 @@ def model_info() -> tuple[str, str, str]:
   manager republishes a tick after a chestnut change, so the stale bundle
   would flash the wrong model."""
   source = active_source()
-  other = "qcom" if source == "chestnut" else "chestnut"
+  other = "qcom" if source == "usbgpu" else "usbgpu"
   active_bundle = get_selected_bundle(ui_state.params, source)
   other_bundle = get_selected_bundle(ui_state.params, other)
 

openpilot/selfdrive/ui/sunnypilot/ui_state.py

@@ -152,13 +152,10 @@ class UIStateSP:
       self.has_icbm = self.CP_SP.intelligentCruiseButtonManagementAvailable and self.params.get_bool("IntelligentCruiseButtonManagement")
 
     self._enforce_constraints()
-    source = get_active_source(chestnut=self.chestnut_present, chestnut_active=self.chestnut_active,
+    source = get_active_source(usbgpu=self.usbgpu, usbgpu_active=self.usbgpu_active,
-                               chestnut_loading=self.chestnut_loading, offroad=self.is_offroad())
+                               usbgpu_loading=self.usbgpu_loading, offroad=self.is_offroad())
     self.active_bundle = self.params.get(ACTIVE_BUNDLE_KEYS[source])
     self.model_runner_tinygrad = self.active_bundle is not None and self.active_bundle.get("runner") == "tinygrad"
-    # stock only counts the default big model's compiled pkl. a downloaded big bundle runs on the
-    # chestnut just the same, so ChestnutState has to see it as available too.
-    self.chestnut_compiled = self.chestnut_compiled or self.model_runner_tinygrad
     self.blindspot = self.params.get_bool("BlindSpot")
     self.chevron_metrics = self.params.get("ChevronInfo")
     self.custom_interactive_timeout = self.params.get("InteractivityTimeout", return_default=True)

openpilot/selfdrive/ui/ui.py

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

openpilot/selfdrive/ui/ui_state.py

@@ -12,8 +12,7 @@ from openpilot.common.swaglog import cloudlog
 from openpilot.selfdrive.ui.lib.prime_state import PrimeState
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.common.hardware import HARDWARE, PC
-from openpilot.common.hardware.usb import TYPEC_CC_ORIENTATION_PATH, get_usb_state, is_chestnut_usb_id, read_int
+from openpilot.selfdrive.modeld.helpers import usbgpu_compiled
-from openpilot.selfdrive.modeld.helpers import chestnut_compiled
 
 from openpilot.selfdrive.ui.sunnypilot.ui_state import UIStateSP, DeviceSP
 
@@ -29,15 +28,6 @@ class UIStatus(Enum):
   LONG_ONLY = "long_only"
 
 
-class ChestnutState(Enum):
-  DISCONNECTED = "disconnected"
-  UNCOMPILED = "uncompiled"
-  READY = "ready"
-  LOADING = "loading"
-  ACTIVE = "active"
-  FAILED = "failed"
-
-
 class UIState(UIStateSP):
   _instance: 'UIState | None' = None
 
@@ -92,15 +82,10 @@ class UIState(UIStateSP):
     self.always_on_dm: bool = self.params.get_bool("AlwaysOnDM")
     self.experimental_mode: bool = self.params.get_bool("ExperimentalMode")
     self.experimental_mode_confirmed: bool = self.params.get_bool("ExperimentalModeConfirmed")
-    self.chestnut_present: bool = False
+    self.usbgpu: bool = False
-    self.chestnut_compiled: bool = chestnut_compiled()
+    self.usbgpu_compiled: bool = usbgpu_compiled()
-    self.chestnut_active: bool | None = None
+    self.usbgpu_active: bool | None = self.params.get("UsbGpuActive")
-    self.chestnut_loading: bool = False
+    self.usbgpu_loading: bool = self.params.get_bool("UsbGpuLoading")
-    self.usb_connected: bool = False
-    self.usb_connected_ts: float | None = None
-    self.usb_disconnected_ts: float | None = None
-    self.usb_unknown: bool = False
-    self.chestnut_state = ChestnutState.DISCONNECTED
     self.started: bool = False
     self.ignition: bool = False
     self.recording_audio: bool = False
@@ -127,6 +112,15 @@ class UIState(UIStateSP):
   def add_on_body_changed_callbacks(self, callback: Callable[[], None]):
     self._on_body_changed_callbacks.append(callback)
 
+  @property
+  def big_model_failed(self) -> bool:
+    # Mirrors the onroad HUD's four-condition check so sidebar and home icons reflect the same failure states
+    return (self.usbgpu_active is False or
+            not self.sm['deviceState'].chestnutPresent or
+            (self.usbgpu_active is True and self.sm.recv_frame['modelV2'] > self.started_frame and
+             not self.sm.alive['modelV2']) or
+            (self.usbgpu_active is None and self.sm.recv_frame['modelV2'] > self.started_frame))
+
   @property
   def engaged(self) -> bool:
     return self.started and (self.sm["selfdriveState"].enabled or self.sm["selfdriveStateSP"].mads.enabled)
@@ -146,7 +140,6 @@ class UIState(UIStateSP):
     self.sm.update(0)
     self._update_state()
     self._update_status()
-    self._update_chestnut_state()
     device.update()
     UIStateSP.update(self)
 
@@ -210,35 +203,12 @@ class UIState(UIStateSP):
         self.status = UIStatus.DISENGAGED
         self.started_frame = self.sm.frame
         self.started_time = time.monotonic()
-        self.chestnut_present = self.sm["deviceState"].chestnutPresent
 
       for callback in self._offroad_transition_callbacks:
         callback()
 
       self._started_prev = self.started
 
-  def _update_chestnut_state(self) -> None:
-    detected = self.sm["deviceState"].chestnutPresent
-    if not self.started:
-      self.chestnut_present = detected
-      self.chestnut_state = (ChestnutState.READY if detected and self.chestnut_compiled else
-                             ChestnutState.UNCOMPILED if detected else ChestnutState.DISCONNECTED)
-      return
-
-    model_seen = self.sm.recv_frame["modelV2"] > self.started_frame
-    if not self.chestnut_present:
-      self.chestnut_state = ChestnutState.DISCONNECTED
-    elif not self.chestnut_compiled:
-      self.chestnut_state = ChestnutState.UNCOMPILED
-    elif self.chestnut_state == ChestnutState.FAILED or not detected or (model_seen and (not self.sm.alive["modelV2"] or not self.sm["modelV2"].big)):
-      self.chestnut_state = ChestnutState.FAILED
-    elif self.chestnut_loading or not model_seen:
-      self.chestnut_state = ChestnutState.LOADING
-    elif self.chestnut_active is False:
-      self.chestnut_state = ChestnutState.FAILED
-    else:
-      self.chestnut_state = ChestnutState.ACTIVE
-
   def update_params(self) -> None:
     # For slower operations
     # Update longitudinal control state
@@ -255,27 +225,12 @@ class UIState(UIStateSP):
     self.always_on_dm = self.params.get_bool("AlwaysOnDM")
     self.experimental_mode = self.params.get_bool("ExperimentalMode")
     self.experimental_mode_confirmed = self.params.get_bool("ExperimentalModeConfirmed")
-    if not self.chestnut_compiled:
+    # keep usbgpu UI active until offroad transition when gpu disappears
-      self.chestnut_compiled = chestnut_compiled()
+    self.usbgpu = self.sm["deviceState"].chestnutPresent or (self.usbgpu and self.started)
-    self.chestnut_active = self.params.get("ChestnutActive")
+    if not self.usbgpu_compiled:
-    self.chestnut_loading = self.params.get_bool("ChestnutLoading")
+      self.usbgpu_compiled = usbgpu_compiled()
-    now = time.monotonic()
+    self.usbgpu_active = self.params.get("UsbGpuActive")
-    if read_int(TYPEC_CC_ORIENTATION_PATH) != 0:
+    self.usbgpu_loading = self.params.get_bool("UsbGpuLoading")
-      self.usb_disconnected_ts = None
-      if not self.usb_connected:
-        self.usb_connected = True
-        self.usb_connected_ts = now
-        self.usb_unknown = False
-      elif self.usb_connected_ts is not None and now - self.usb_connected_ts > 10.:
-        self.usb_unknown = not any(is_chestnut_usb_id(d["vendorId"], d["productId"], True) for d in get_usb_state())
-        self.usb_connected_ts = None
-    elif self.usb_connected:
-      if self.usb_disconnected_ts is None:
-        self.usb_disconnected_ts = now
-      elif now - self.usb_disconnected_ts > PARAM_UPDATE_TIME:
-        self.usb_connected = False
-        self.usb_connected_ts = None
-        self.usb_unknown = False
 
     UIStateSP.update_params(self)
 

openpilot/sunnypilot/modeld_v2/__init__.py

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

openpilot/sunnypilot/modeld_v2/compile_modeld.py

@@ -32,7 +32,7 @@ def _patch_tinygrad_fetch_fw():
   helpers.fetch_fw = fetch_fw
 _patch_tinygrad_fetch_fw()
 
-import openpilot.selfdrive.modeld.compile_modeld as stock
+from openpilot.selfdrive.modeld.compile_modeld import NV12Frame, make_frame_prepare, sample_desire, sample_skip, shift_and_sample
 from tinygrad import dtypes
 from tinygrad.device import Device
 from tinygrad.engine.jit import TinyJit
@@ -41,7 +41,8 @@ from tinygrad.tensor import Tensor
 MODEL_TYPES = ('vision_policy', 'supercombo', 'vision_multi_policy')
 WARP_INPUTS = ['tfm', 'big_tfm']
 POLICY_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']
-nv12_copy_size = stock.nv12_copy_size
+WARP_DEV = os.getenv('WARP_DEV')
+
 
 def _detect_desire_key(shapes: dict) -> str | None:
   return next((key for key in shapes if key.startswith('desire')), None)
@@ -138,7 +139,7 @@ def make_supercombo_input_queues(input_shapes: dict, frame_skip: int,
   return generate_queues_and_npy(input_shapes, frame_skip, device, is_supercombo=True)
 
 
-def make_random_images(keys, shape, device, rng=None):
+def make_random_images(keys, shape, device):
   return {k: Tensor.randint(shape, low=0, high=256, dtype=dtypes.uint8, device=device).realize() for k in keys}
 
 
@@ -151,9 +152,24 @@ def make_warp_queues(device=Device.DEFAULT):
   return queues, npy
 
 
+def make_warp(nv12: NV12Frame, model_w: int, model_h: int):
+  frame_prepare = make_frame_prepare(nv12, model_w, model_h)
+  WARP_DEV = os.getenv('WARP_DEV', Device.DEFAULT)
+
+  def warp(tfm, big_tfm, frame, big_frame):
+    tfm = tfm.to(WARP_DEV)
+    big_tfm = big_tfm.to(WARP_DEV)
+    Tensor.realize(tfm, big_tfm)
+
+    warped_frame = frame_prepare(frame, tfm).unsqueeze(0)
+    warped_big_frame = frame_prepare(big_frame, big_tfm).unsqueeze(0)
+    return Tensor.cat(warped_frame, warped_big_frame)
+  return warp
+
+
 def make_run_policy(vision_runner, policy_runners: list, features_slice: slice, frame_skip: int, input_shapes: dict):
-  sample_skip_fn = partial(stock.sample_skip, frame_skip=frame_skip)
+  sample_skip_fn = partial(sample_skip, frame_skip=frame_skip)
-  sample_desire_fn = partial(stock.sample_desire, frame_skip=frame_skip)
+  sample_desire_fn = partial(sample_desire, frame_skip=frame_skip)
 
   desire_key = _detect_desire_key(input_shapes)
   road_key, wide_key = _detect_vision_keys(input_shapes)
@@ -170,14 +186,14 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
     warped_dev = warped.to(Device.DEFAULT)
     Tensor.realize(packed_npy_inputs_dev, warped_dev)
 
-    img = stock.shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn)
+    img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn)
-    big_img = stock.shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn)
+    big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn)
 
     unpacked_tensors = [tensor.reshape(shape) for tensor, shape in zip(packed_npy_inputs_dev.split(npy_sizes), npy_shapes.values(), strict=True)]
     unpacked_dict = dict(zip(npy_shapes.keys(), unpacked_tensors, strict=True))
 
     desire_dev = unpacked_dict['desire']
-    desire_buf = stock.shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn)
+    desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn)
 
     inputs = {desire_key: desire_buf}
     for key, tensor_val in unpacked_dict.items():
@@ -186,13 +202,13 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
 
     if 'prev_feat' in unpacked_dict:
       prev_feat_dev = unpacked_dict['prev_feat']
-      inputs['features_buffer'] = stock.shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).reshape(input_shapes['features_buffer'])
+      inputs['features_buffer'] = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).reshape(input_shapes['features_buffer'])
 
     if vision_runner:
       vision_out_cast = next(iter(vision_runner({road_key: img, wide_key: big_img}).values())).cast('float32').realize()
       if 'features_buffer' not in inputs:
         new_feat = vision_out_cast[:, features_slice].reshape(1, -1).unsqueeze(0)
-        inputs['features_buffer'] = stock.shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
+        inputs['features_buffer'] = shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
       policy_outs = [next(iter(pol_runner(inputs).values())).cast('float32').realize() for pol_runner in policy_runners]
       return (vision_out_cast, *policy_outs) if len(policy_outs) > 1 else (vision_out_cast, policy_outs[0])
 
@@ -203,28 +219,27 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
     policy_out = next(iter(policy_runners[0](inputs).values())).cast('float32').realize()
     if 'features_buffer' not in inputs and features_slice is not None:
       new_feat = policy_out[:, features_slice].reshape(1, -1).unsqueeze(0)
-      stock.shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
+      shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
     return policy_out
 
   return run_policy
 
 
-def compile_jit(jit, input_keys, make_queues, make_random_inputs=None, benchmark_runs: int = 1):
+def compile_jit(jit, make_random_inputs, input_keys, make_queues):
   SEED = 42
-  def random_inputs_run(fn, seed, n_runs, test_val=None, test_buffers=None, expect_match=True):
+  def random_inputs_run(fn, seed, test_val=None, test_buffers=None, expect_match=True):
-    queues_res = make_queues(Device.DEFAULT)
+    input_queues, npy = make_queues(Device.DEFAULT)
-    input_queues, npy = queues_res[0], queues_res[1]
-    frame_views = queues_res[2] if len(queues_res) > 2 else {}
     rng = np.random.default_rng(seed)
     Tensor.manual_seed(seed)
 
+    testing = test_val is not None or test_buffers is not None
+    n_runs = 1 if testing else 3
+
     for i in range(n_runs):
       for v in npy.values():
         v[:] = rng.standard_normal(v.shape).astype(v.dtype)
-      for v in frame_views.values():
-        v[:] = rng.integers(0, 256, size=v.shape, dtype=np.uint8)
       Device.default.synchronize()
-      random_inputs = make_random_inputs(rng=rng) if make_random_inputs is not None else {}
+      random_inputs = make_random_inputs()
       st = time.perf_counter()
       outs = fn(**{k: input_queues[k] for k in input_keys if k in input_queues}, **random_inputs)
       mt = time.perf_counter()
@@ -245,15 +260,14 @@ def compile_jit(jit, input_keys, make_queues, make_random_inputs=None, benchmark
     return val, buffers
 
   print('capture + replay')
-  test_val, test_buffers = random_inputs_run(jit, SEED, 3)
+  test_val, test_buffers = random_inputs_run(jit, SEED)
-  print(f'pickle round trip ({benchmark_runs} runs per seed)')
+  print('pickle round trip')
   with tempfile.TemporaryFile(dir=".") as f:
     dump_oob(jit, f)
     f.seek(0)
-    loaded_jit = load_oob(f)
+    deserialized_jit = load_oob(f)
-  random_inputs_run(loaded_jit, SEED, benchmark_runs, test_val, test_buffers, expect_match=True)
+  random_inputs_run(deserialized_jit, SEED, test_val=test_val, test_buffers=test_buffers)
-  random_inputs_run(loaded_jit, SEED+1, benchmark_runs, test_val, test_buffers, expect_match=False)
+  return deserialized_jit
-  return jit
 
 
 def _parse_size(size_str: str) -> tuple[int, int]:
@@ -284,7 +298,7 @@ def _load_policy_runners(args: argparse.Namespace) -> tuple[list, list]:
 
 
 if __name__ == "__main__":
-  if 'USB' in os.getenv('DEV', '') or os.getenv('CHESTNUT'):
+  if 'USB' in os.getenv('DEV', '') or os.getenv('USBGPU'):
     from openpilot.system.hardware.chestnut.flash import link_up
     for _ in range(10):
       if link_up():
@@ -303,7 +317,6 @@ if __name__ == "__main__":
   parser.add_argument('--model-size', type=_parse_size, required=True, help='model input WxH')
   parser.add_argument('--camera-resolutions', type=_parse_size, nargs='+', required=True)
   parser.add_argument('--frame-skip', type=int, default=None, help='frame skip value (auto-derived if not provided)')
-  parser.add_argument('--benchmark-runs', type=int, default=1, help='benchmark runs')
   parser.add_argument('--output', required=True)
 
   parser.add_argument('--vision-onnx', help='vision ONNX (for split models)')
@@ -322,64 +335,48 @@ if __name__ == "__main__":
   args.on_policy_onnx = read_file_chunked_to_disk(args.on_policy_onnx)
   args.supercombo_onnx = read_file_chunked_to_disk(args.supercombo_onnx)
 
-  if args.model_type == 'supercombo':
+  vision_runner = OnnxRunner(args.vision_onnx) if args.vision_onnx else None
+
+  if args.model_type == 'vision_policy':
+    assert vision_runner and args.policy_onnx
+    policy_runners = [OnnxRunner(args.policy_onnx)]
+    output_data['metadata'] = {'vision': make_metadata_dict(args.vision_onnx), 'policy': make_metadata_dict(args.policy_onnx)}
+  elif args.model_type == 'supercombo':
     assert args.supercombo_onnx
-    model_metadata = make_metadata_dict(args.supercombo_onnx)
+    policy_runners = [OnnxRunner(args.supercombo_onnx)]
-    output_data['metadata'] = {'model': model_metadata, **model_metadata}
+    output_data['metadata'] = {'model': make_metadata_dict(args.supercombo_onnx)}
-    output_data['input_devices'] = {'model': Device.DEFAULT}
+  elif args.model_type == 'vision_multi_policy':
-    output_data['run_model'] = {}
+    assert vision_runner
-    derived_frame_skip = args.frame_skip or derive_frame_skip({}, model_metadata['input_shapes'])
+    policy_runners, policy_names = _load_policy_runners(args)
-    model_runner = OnnxRunner(args.supercombo_onnx)
+    output_data['metadata'] = {'vision': make_metadata_dict(args.vision_onnx)}
-    run_policy = stock.make_run_policy(model_runner, model_metadata, derived_frame_skip)
+    for name in policy_names:
-    for cam_w, cam_h in args.camera_resolutions:
+      runner_arg = getattr(args, f"{name}_onnx")
-      print(f"Compiling unified run_model JIT for {cam_w}x{cam_h}...")
+      output_data['metadata'][name] = make_metadata_dict(runner_arg)
-      nv12 = stock.NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-      frame_copy_size = stock.nv12_copy_size(nv12.stride, nv12.y_height, nv12.uv_height)
-      make_model_queues = partial(stock.make_input_queues, model_metadata['input_shapes'], derived_frame_skip,
-                                  frame_copy_size=frame_copy_size)
-      warp = stock.make_warp(nv12, model_w, model_h)
-      run_model_jit = TinyJit(stock.make_run_model(warp, run_policy, model_metadata, frame_copy_size), prune=True)
-      output_data['run_model'][(cam_w, cam_h)] = compile_jit(run_model_jit, stock.MODELD_INPUTS, make_model_queues, benchmark_runs=args.benchmark_runs)
-  else:
-    vision_runner = OnnxRunner(args.vision_onnx) if args.vision_onnx else None
-    if args.model_type == 'vision_policy':
-      assert vision_runner and args.policy_onnx
-      policy_runners = [OnnxRunner(args.policy_onnx)]
-      output_data['metadata'] = {'vision': make_metadata_dict(args.vision_onnx), 'policy': make_metadata_dict(args.policy_onnx)}
-    elif args.model_type == 'vision_multi_policy':
-      assert vision_runner
-      policy_runners, policy_names = _load_policy_runners(args)
-      output_data['metadata'] = {'vision': make_metadata_dict(args.vision_onnx)}
-      for name in policy_names:
-        runner_arg = getattr(args, f"{name}_onnx")
-        output_data['metadata'][name] = make_metadata_dict(runner_arg)
 
-    policy_keys = [key for key in output_data['metadata'].keys() if key != 'vision']
+  policy_keys = [key for key in output_data['metadata'].keys() if key != 'vision']
-    first_policy_meta = output_data['metadata'][policy_keys[0]] if policy_keys else {}
+  first_policy_meta = output_data['metadata'][policy_keys[0]] if policy_keys else {}
-    vision_meta = output_data['metadata'].get('vision', {})
+  vision_meta = output_data['metadata'].get('vision', {})
 
-    derived_frame_skip = args.frame_skip or derive_frame_skip(vision_meta.get('input_shapes', {}), first_policy_meta.get('input_shapes', {}))
+  derived_frame_skip = args.frame_skip or derive_frame_skip(vision_meta.get('input_shapes', {}), first_policy_meta.get('input_shapes', {}))
-    all_shapes = {key: value for meta in output_data['metadata'].values() for key, value in meta['input_shapes'].items()}
+  all_shapes = {key: value for meta in output_data['metadata'].values() for key, value in meta['input_shapes'].items()}
-    feat_meta = output_data['metadata'].get('vision') or output_data['metadata'].get('policy')
+  feat_meta = output_data['metadata'].get('vision') or output_data['metadata'].get('model') or output_data['metadata'].get('policy')
-    assert feat_meta is not None
+  assert feat_meta is not None
-    features_slice = feat_meta['output_slices']['hidden_state']
+  features_slice = feat_meta['output_slices']['hidden_state']
+  is_supercombo = vision_runner is None
 
-    print(f"Compiling run_policy JIT (model_size={model_w}x{model_h}, frame_skip={derived_frame_skip})...")
+  print(f"Compiling run_policy JIT (model_size={model_w}x{model_h}, frame_skip={derived_frame_skip})...")
-    run_policy_func = make_run_policy(vision_runner, policy_runners, features_slice, derived_frame_skip, all_shapes)
+  run_policy_func = make_run_policy(vision_runner, policy_runners, features_slice, derived_frame_skip, all_shapes)
-    run_policy_jit = TinyJit(run_policy_func, prune=True)
+  run_policy_jit = TinyJit(run_policy_func, prune=True)
-    make_policy_queues = partial(generate_queues_and_npy, all_shapes, derived_frame_skip, is_supercombo=False)
+  make_policy_queues = partial(generate_queues_and_npy, all_shapes, derived_frame_skip, is_supercombo=is_supercombo)
-    make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, model_h // 2, model_w // 2), device=Device.DEFAULT)
+  make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, model_h // 2, model_w // 2), device=WARP_DEV)
-    output_data['run_policy'] = compile_jit(run_policy_jit, POLICY_INPUTS, make_policy_queues, make_random_inputs=make_random_model_inputs)
+  output_data['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:
+  for cam_w, cam_h in args.camera_resolutions:
-      print(f"Compiling warp JIT for {cam_w}x{cam_h}...")
+    print(f"Compiling warp JIT for {cam_w}x{cam_h}...")
-      nv12 = stock.NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
+    nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-      frame_copy_size = stock.nv12_copy_size(nv12.stride, nv12.y_height, nv12.uv_height)
+    make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=nv12.size, device=WARP_DEV)
-      make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=frame_copy_size, device=Device.DEFAULT)
+    warp = TinyJit(make_warp(nv12, model_w, model_h), prune=True)
-      warp = TinyJit(stock.make_warp(nv12, model_w, model_h), prune=True)
+    output_data[(cam_w, cam_h)] = compile_jit(warp, make_random_warp_inputs, WARP_INPUTS, make_warp_queues)
-      output_data[(cam_w, cam_h)] = compile_jit(warp, WARP_INPUTS, make_warp_queues, make_random_inputs=make_random_warp_inputs)
-
-    output_data['metadata']['warp_dev'] = Device.DEFAULT
 
   with open(args.output, "wb") as file:
     dump_oob(output_data, file)

openpilot/sunnypilot/modeld_v2/constants.py

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

openpilot/sunnypilot/modeld_v2/meta_helper.py

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

openpilot/sunnypilot/modeld_v2/modeld.py

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

openpilot/sunnypilot/modeld_v2/parse_model_outputs.py

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

openpilot/sunnypilot/modeld_v2/parse_model_outputs_split.py

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

openpilot/sunnypilot/modeld_v2/tests/helpers.py

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

openpilot/sunnypilot/modeld_v2/tests/test_combined_pkl_loader.py

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

openpilot/sunnypilot/modeld_v2/tests/test_compile_modeld.py

@@ -7,7 +7,6 @@ See the LICENSE.md file in the root directory for more details.
 
 import os
 import tempfile
-import unittest
 from pathlib import Path
 
 import numpy as np
@@ -249,27 +248,23 @@ class TestStockCompileModeldEquivalence(OpenpilotTestCase):
     input_shapes = {
       'img': (1, 12, 128, 256),
       'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 32, 512),
+      'features_buffer': (1, 24, 512),  # when https://github.com/commaai/openpilot/pull/38681 merges, update to 1,24,32,512
       'traffic_convention': (1, 2),
       'action_t': (1, 2),
     }
     frame_skip = 4
 
-    stock_queues, stock_npy, _frame_views = stock_make_input_queues(input_shapes, frame_skip, device='NPY', frame_copy_size=49152)
+    stock_queues, stock_npy = stock_make_input_queues(input_shapes, frame_skip, device='NPY')
     sunny_queues, sunny_npy = sunny_make_supercombo_input_queues(input_shapes, frame_skip, device='NPY')
-    # sunnypilot split pipeline has tfm/big_tfm as queues; packed_npy_inputs size differs (different frame packing)
+    assert set(sunny_queues.keys()) == set(stock_queues.keys())
-    assert set(stock_queues.keys()) <= set(sunny_queues.keys())
     for key in stock_queues:
-      if key == 'packed_npy_inputs':
-        continue
       assert sunny_queues[key].shape == stock_queues[key].shape, \
         f"Queue shape mismatch for {key}: sunny {sunny_queues[key].shape} != stock {stock_queues[key].shape}"
-    assert set(stock_npy.keys()) <= set(sunny_npy.keys())
+    assert set(sunny_npy.keys()) == set(stock_npy.keys())
     for key in stock_npy:
       assert sunny_npy[key].shape == stock_npy[key].shape, \
         f"Numpy array shape mismatch for {key}: sunny {sunny_npy[key].shape} != stock {stock_npy[key].shape}"
 
-  @unittest.skip("upstream removed make_warp_input_queues — warp merged into run_model")
   def test_make_warp_queues_stock_equivalence(self):
     from openpilot.selfdrive.modeld.compile_modeld import make_warp_input_queues as stock_make_warp_queues
     from openpilot.sunnypilot.modeld_v2.compile_modeld import make_warp_queues as sunny_make_warp_queues

openpilot/sunnypilot/modeld_v2/tests/test_fallback.py

@@ -1,62 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import io
-import requests
-
-from openpilot.common.file_chunker import get_chunk_name
-from openpilot.common.hardware import hw
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.modeld.helpers import dump_oob
-import openpilot.sunnypilot.modeld_v2.modeld as modeld_module
-from openpilot.sunnypilot.modeld_v2.tests import helpers as tests_helpers
-from openpilot.sunnypilot.modeld_v2.tests.helpers import DummyModel, DummyBundle, CAM_W, CAM_H
-from openpilot.sunnypilot.models.fetcher import ModelParser, ModelFetcher
-
-tmp_path = tests_helpers.tmp_path
-
-
-class TestFallback(OpenpilotTestCase):
-  def test_find_dual_model_in_bundle(self, tmp_path, monkeypatch):
-    lebowski_file = 'driving_lebowski.pkl'
-    tsfdo_file = 'driving_tsfdo.pkl'
-    (tmp_path / lebowski_file).write_bytes(b'fkasdjfkljf')
-    (tmp_path / tsfdo_file).write_bytes(b'dskfajklsdjlsfka')
-
-    monkeypatch.setattr(hw.Paths, 'model_root', staticmethod(lambda: str(tmp_path)))
-    big_bundle = DummyBundle(models=[DummyModel('supercombo', lebowski_file)])
-    small_bundle = DummyBundle(models=[DummyModel('supercombo', tsfdo_file)])
-    big_pkl = modeld_module._find_driving_pkl(big_bundle)
-    small_pkl = modeld_module._find_driving_pkl(small_bundle)
-
-    assert big_pkl is not None and lebowski_file in big_pkl
-    assert small_pkl is not None and tsfdo_file in small_pkl
-
-  def test_download_models_and_init_modelstate_fallback(self, tmp_path, monkeypatch):
-    monkeypatch.setattr(hw.Paths, 'model_root', staticmethod(lambda: str(tmp_path)))
-    big_json = requests.get(ModelFetcher.MODEL_URL_CHESTNUT).json()
-    big_bundle = ModelParser.parse_models(big_json)[-1]
-    small_json = requests.get(ModelFetcher.MODEL_URL).json()
-    small_bundle = ModelParser.parse_models(small_json)[-1]
-
-    buf = io.BytesIO()
-    dump_oob(tests_helpers.make_pkl_data(tests_helpers.ARCHETYPES['supercombo_non20hz']), buf)
-    oob_bytes = buf.getvalue()
-
-    for bundle in (big_bundle, small_bundle):
-      artifact = bundle.models[0].artifact
-      for i in range(len(artifact.chunks)):
-        (tmp_path / get_chunk_name(artifact.fileName, i, len(artifact.chunks))).write_bytes(oob_bytes if i == 0 else b"")
-
-    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, chestnut=None: small_bundle)
-    assert modeld_module.ModelState(CAM_W, CAM_H, chestnut=False).chestnut is False
-
-    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, chestnut=None: big_bundle)
-    try:
-      assert modeld_module.ModelState(CAM_W, CAM_H, chestnut=True).chestnut is True
-    except Exception as e:
-      assert "AMD" in str(e) or "device" in str(e).lower()

openpilot/sunnypilot/modeld_v2/tests/test_parse_model_outputs.py

@@ -1,81 +0,0 @@
-import numpy as np
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.sunnypilot.modeld_v2.constants import ModelConstants
-from openpilot.sunnypilot.modeld_v2.parse_model_outputs import Parser, _infer_mhp, sigmoid, softmax
-
-
-class TestParseModelOutputs(OpenpilotTestCase):
-  def test_infer_mhp_lead(self):
-    in_hypotheses, out_selections = _infer_mhp(102, 24)
-    assert in_hypotheses == 2
-    assert out_selections == 3
-
-  def test_infer_mhp_plan(self):
-    in_hypotheses, out_selections = _infer_mhp(4955, 495)
-    assert in_hypotheses == 5
-    assert out_selections == 1
-
-  def test_infer_mhp_non_mdn(self):
-    in_hypotheses, out_selections = _infer_mhp(48, 24)
-    assert in_hypotheses == 1
-    assert out_selections == 0
-
-  def test_check_missing_raises(self):
-    parser = Parser(ignore_missing=False)
-    with self.assertRaises(ValueError):
-      parser.check_missing({}, "missing_key")
-
-  def test_check_missing_ignored(self):
-    parser = Parser(ignore_missing=True)
-    assert parser.check_missing({}, "missing_key") is True
-
-  def test_binary_crossentropy(self):
-    parser = Parser()
-    raw_logits = np.array([[-10.0, 0.0, 10.0]], dtype=np.float32)
-    outs = {"meta": raw_logits.copy()}
-    parser.parse_binary_crossentropy("meta", outs)
-    expected_probabilities = sigmoid(raw_logits)
-    np.testing.assert_allclose(outs["meta"], expected_probabilities, rtol=1e-5, atol=1e-6)
-
-  def test_categorical_crossentropy(self):
-    parser = Parser()
-    raw_logits = np.array([[1.0, 2.0, 3.0]], dtype=np.float32)
-    outs = {"desire_state": raw_logits.copy()}
-    parser.parse_categorical_crossentropy("desire_state", outs)
-    expected_probabilities = softmax(raw_logits)
-    np.testing.assert_allclose(outs["desire_state"], expected_probabilities, rtol=1e-5, atol=1e-6)
-
-  def test_parse_vision_outputs(self):
-    parser = Parser()
-    pose_raw = np.zeros((1, ModelConstants.POSE_WIDTH * 2), dtype=np.float32)
-    road_transform_raw = np.zeros((1, ModelConstants.POSE_WIDTH * 2), dtype=np.float32)
-    lead_raw = np.zeros((1, 102), dtype=np.float32)
-    meta_raw = np.zeros((1, 55), dtype=np.float32)
-    vision_outputs = {"pose": pose_raw, "road_transform": road_transform_raw, "lead": lead_raw, "meta": meta_raw}
-    parsed = parser.parse_vision_outputs(vision_outputs)
-    assert "pose" in parsed
-    assert "road_transform" in parsed
-    assert "lead" in parsed
-    assert "meta" in parsed
-    assert parsed["pose"].shape == (1, ModelConstants.POSE_WIDTH)
-    assert parsed["lead"].shape == (1, ModelConstants.LEAD_MHP_SELECTION, ModelConstants.LEAD_TRAJ_LEN, ModelConstants.LEAD_WIDTH)
-
-  def test_parse_policy_outputs(self):
-    parser = Parser()
-    plan_raw = np.zeros((1, 4955), dtype=np.float32)
-    desire_state_raw = np.zeros((1, ModelConstants.DESIRE_PRED_WIDTH), dtype=np.float32)
-    action_raw = np.zeros((1, ModelConstants.ACTION_WIDTH * 2), dtype=np.float32)
-    policy_outputs = {"plan": plan_raw, "desire_state": desire_state_raw, "action": action_raw}
-    parsed = parser.parse_policy_outputs(policy_outputs)
-    assert parsed["plan"].shape == (1, ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH)
-    assert parsed["action"].shape == (1, ModelConstants.ACTION_WIDTH)
-    assert parsed["desire_state"].shape == (1, ModelConstants.DESIRE_PRED_WIDTH)
-
-  def test_parse_outputs_combined(self):
-    parser = Parser()
-    outputs = {"plan": np.zeros((1, 4955), dtype=np.float32), "pose": np.zeros((1, ModelConstants.POSE_WIDTH * 2),
-               dtype=np.float32), "meta": np.zeros((1, 55), dtype=np.float32)}
-    parsed = parser.parse_outputs(outputs)
-    assert parsed["plan"].shape == (1, ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH)
-    assert parsed["pose"].shape == (1, ModelConstants.POSE_WIDTH)
-    assert parsed["meta"].shape == (1, 55)

openpilot/sunnypilot/models/constants.py

@@ -0,0 +1,121 @@
+import numpy as np
+
+def index_function(idx, max_val=192, max_idx=32):
+  return max_val * ((idx/max_idx)**2)
+
+
+class ModelConstants:
+  # time and distance indices
+  IDX_N = 33
+  T_IDXS = [index_function(idx, max_val=10.0) for idx in range(IDX_N)]
+  X_IDXS = [index_function(idx, max_val=192.0) for idx in range(IDX_N)]
+  LEAD_T_IDXS = [0., 2., 4., 6., 8., 10.]
+  LEAD_T_OFFSETS = [0., 2., 4.]
+  META_T_IDXS = [2., 4., 6., 8., 10.]
+
+  # model inputs constants
+  MODEL_FREQ = 20
+  FEATURE_LEN = 512
+  HISTORY_BUFFER_LEN = 99
+  DESIRE_LEN = 8
+  TRAFFIC_CONVENTION_LEN = 2
+  NAV_FEATURE_LEN = 256
+  NAV_INSTRUCTION_LEN = 150
+  LAT_PLANNER_STATE_LEN = 4
+  LATERAL_CONTROL_PARAMS_LEN = 2
+  PREV_DESIRED_CURV_LEN = 1
+
+  # model outputs constants
+  FCW_THRESHOLDS_5MS2 = np.array([.05, .05, .15, .15, .15], dtype=np.float32)
+  FCW_THRESHOLDS_3MS2 = np.array([.7, .7], dtype=np.float32)
+  FCW_5MS2_PROBS_WIDTH = 5
+  FCW_3MS2_PROBS_WIDTH = 2
+
+  DISENGAGE_WIDTH = 5
+  POSE_WIDTH = 6
+  WIDE_FROM_DEVICE_WIDTH = 3
+  SIM_POSE_WIDTH = 6
+  LEAD_WIDTH = 4
+  LANE_LINES_WIDTH = 2
+  ROAD_EDGES_WIDTH = 2
+  PLAN_WIDTH = 15
+  DESIRE_PRED_WIDTH = 8
+  LAT_PLANNER_SOLUTION_WIDTH = 4
+  DESIRED_CURV_WIDTH = 1
+
+  NUM_LANE_LINES = 4
+  NUM_ROAD_EDGES = 2
+
+  LEAD_TRAJ_LEN = 6
+  DESIRE_PRED_LEN = 4
+
+  PLAN_MHP_N = 5
+  LEAD_MHP_N = 2
+  PLAN_MHP_SELECTION = 1
+  LEAD_MHP_SELECTION = 3
+
+  FCW_THRESHOLD_5MS2_HIGH = 0.15
+  FCW_THRESHOLD_5MS2_LOW = 0.05
+  FCW_THRESHOLD_3MS2 = 0.7
+
+  CONFIDENCE_BUFFER_LEN = 5
+  RYG_GREEN = 0.01165
+  RYG_YELLOW = 0.06157
+
+  POLY_PATH_DEGREE = 4
+
+
+# model outputs slices
+class Plan:
+  POSITION = slice(0, 3)
+  VELOCITY = slice(3, 6)
+  ACCELERATION = slice(6, 9)
+  T_FROM_CURRENT_EULER = slice(9, 12)
+  ORIENTATION_RATE = slice(12, 15)
+
+
+class Meta:
+  ENGAGED = slice(0, 1)
+  # next 2, 4, 6, 8, 10 seconds
+  GAS_DISENGAGE = slice(1, 31, 6)
+  BRAKE_DISENGAGE = slice(2, 31, 6)
+  STEER_OVERRIDE = slice(3, 31, 6)
+  HARD_BRAKE_3 = slice(4, 31, 6)
+  HARD_BRAKE_4 = slice(5, 31, 6)
+  HARD_BRAKE_5 = slice(6, 31, 6)
+  # next 0, 2, 4, 6, 8, 10 seconds
+  GAS_PRESS = slice(31, 55, 4)
+  BRAKE_PRESS = slice(32, 55, 4)
+  LEFT_BLINKER = slice(33, 55, 4)
+  RIGHT_BLINKER = slice(34, 55, 4)
+
+
+class MetaTombRaider:
+  ENGAGED = slice(0, 1)
+  # next 2, 4, 6, 8, 10 seconds
+  GAS_DISENGAGE = slice(1, 41, 8)
+  BRAKE_DISENGAGE = slice(2, 41, 8)
+  STEER_OVERRIDE = slice(3, 41, 8)
+  HARD_BRAKE_3 = slice(4, 41, 8)
+  HARD_BRAKE_4 = slice(5, 41, 8)
+  HARD_BRAKE_5 = slice(6, 41, 8)
+  GAS_PRESS = slice(7, 41, 8)
+  BRAKE_PRESS = slice(8, 41, 8)
+  # next 0, 2, 4, 6, 8, 10 seconds
+  LEFT_BLINKER = slice(41, 53, 2)
+  RIGHT_BLINKER = slice(42, 53, 2)
+
+
+class MetaSimPose:
+  ENGAGED = slice(0, 1)
+  # next 2, 4, 6, 8, 10 seconds
+  GAS_DISENGAGE = slice(1, 36, 7)
+  BRAKE_DISENGAGE = slice(2, 36, 7)
+  STEER_OVERRIDE = slice(3, 36, 7)
+  HARD_BRAKE_3 = slice(4, 36, 7)
+  HARD_BRAKE_4 = slice(5, 36, 7)
+  HARD_BRAKE_5 = slice(6, 36, 7)
+  GAS_PRESS = slice(7, 36, 7)
+  # next 0, 2, 4, 6, 8, 10 seconds
+  LEFT_BLINKER = slice(36, 48, 2)
+  RIGHT_BLINKER = slice(37, 48, 2)

openpilot/sunnypilot/models/default_model.py

@@ -1,89 +1,43 @@
 import argparse
 import os
 import hashlib
-import requests
-import re
 
 from openpilot.common.basedir import BASEDIR
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.sunnypilot import get_file_hash
 from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL, DEFAULT_BIG_MODEL
-from openpilot.sunnypilot.models.fetcher import ModelFetcher
 
 
 def get_default_model() -> str:
-  show_big_model = (ui_state.chestnut_present
+  show_big_model = (ui_state.usbgpu
-                    and (ui_state.chestnut_active or ui_state.chestnut_loading or ui_state.is_offroad()))
+                    and (ui_state.usbgpu_active or ui_state.usbgpu_loading or ui_state.is_offroad()))
 
   return DEFAULT_BIG_MODEL if show_big_model else DEFAULT_MODEL
 
 
 DEFAULT_MODEL_NAME_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "models", "model_name.py")
 MODEL_HASH_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "models", "tests", "model_hash")
-BIG_MODEL_HASH_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "models", "tests", "big_model_hash")
 SUPERCOMBO_ONNX_PATH = os.path.join(BASEDIR, "openpilot", "selfdrive", "modeld", "models", "driving_supercombo.onnx")
-BIG_SUPERCOMBO_ONNX_PATH = os.path.join(BASEDIR, "openpilot", "selfdrive", "modeld", "models", "big_driving_supercombo.onnx")
-
-
-def _read_model_name_fields():
-  with open(DEFAULT_MODEL_NAME_PATH) as f:
-    content = f.read()
-  fields = {}
-  for line in content.splitlines():
-    if "=" in line:
-      key, val = line.split("=", 1)
-      fields[key.strip()] = val.strip().strip('"')
-  return fields
 
 
 def update_model_hash():
-  fields = _read_model_name_fields()
   supercombo_hash = get_file_hash(SUPERCOMBO_ONNX_PATH)
-  fingerprint = f"{supercombo_hash}:{fields.get('DEFAULT_MODEL', '')}:{fields.get('DEFAULT_MODEL_REF', '')}"
+  combined_hash = hashlib.sha256(supercombo_hash.encode()).hexdigest()
-  combined_hash = hashlib.sha256(fingerprint.encode()).hexdigest()
 
   with open(MODEL_HASH_PATH, "w") as f:
     f.write(combined_hash)
 
   print(f"Generated and updated new combined model hash to {MODEL_HASH_PATH}")
 
-  if os.path.exists(BIG_SUPERCOMBO_ONNX_PATH):
-    import subprocess
-    rel = os.path.relpath(BIG_SUPERCOMBO_ONNX_PATH, os.getcwd())
-    pointer = subprocess.check_output(["git", "show", f"HEAD:{rel}"], text=True)
-    oid = next(l.split(":", 1)[1] for l in pointer.splitlines() if l.startswith("oid sha256:"))
-    big_fingerprint = f"{oid}:{fields.get('DEFAULT_BIG_MODEL', '')}:{fields.get('DEFAULT_BIG_MODEL_REF', '')}"
-    big_combined_hash = hashlib.sha256(big_fingerprint.encode()).hexdigest()
-
-    with open(BIG_MODEL_HASH_PATH, "w") as f:
-      f.write(big_combined_hash)
-
-    print(f"Generated and updated new big model hash to {BIG_MODEL_HASH_PATH}")
-
-
-def get_ref_for_name(url: str, name: str) -> str:
-  response = requests.get(url, timeout=10)
-  if response.status_code == 200:
-    bundles = response.json()["bundles"]
-    matching = [b for b in bundles if re.search(name, f"{b['short_name']} {b['display_name']}", re.IGNORECASE)]
-    if matching:
-      return max(matching, key=lambda b: int(b["index"]))["ref"]
-  return ""
-
 
 def update_default_model_names(default_model_name: str, default_big_model_name: str):
   print("[CHANGE DEFAULT MODEL NAMES]")
-  small_ref = get_ref_for_name(ModelFetcher.MODEL_URL, default_model_name)
-  big_ref = get_ref_for_name(ModelFetcher.MODEL_URL_CHESTNUT, default_big_model_name)
-
   with open(DEFAULT_MODEL_NAME_PATH, "w") as f:
     f.write(f'DEFAULT_MODEL = "{default_model_name}"\n')
-    f.write(f'DEFAULT_MODEL_REF = "{small_ref}"\n')
     f.write(f'DEFAULT_BIG_MODEL = "{default_big_model_name}"\n')
-    f.write(f'DEFAULT_BIG_MODEL_REF = "{big_ref}"\n')
 
-  print(f'New default small model name: "{default_model_name}" (ref: {small_ref})')
+  print(f'New default small model name: "{default_model_name}"')
-  print(f'New default big model name: "{default_big_model_name}" (ref: {big_ref})')
+  print(f'New default big model name: "{default_big_model_name}"')
   print("[DONE]")
 
 

openpilot/sunnypilot/models/fetcher.py

@@ -138,12 +138,12 @@ class ModelCache:
 
 class ModelFetcher:
   """Handles fetching and caching of model data from remote source"""
-  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v22.json"
+  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v21.json"
-  MODEL_URL_CHESTNUT = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_chestnut_v25.json"
+  MODEL_URL_USBGPU = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_usbgpu_v22.json"
 
   MODEL_SOURCES = {
     "qcom": (MODEL_URL, ""),
-    "chestnut": (MODEL_URL_CHESTNUT, "_Chestnut"),
+    "usbgpu": (MODEL_URL_USBGPU, "_USBGPU"),
   }
 
   def __init__(self, params: Params):
@@ -156,12 +156,12 @@ class ModelFetcher:
     self._refetched: set[str] = set()
     self.params.put("ModelManager_ActiveJson", {
       "qcom": self.MODEL_URL,
-      "chestnut": self.MODEL_URL_CHESTNUT,
+      "usbgpu": self.MODEL_URL_USBGPU,
     }, block=True)
 
   @staticmethod
   def active_source(chestnut_present: bool) -> str:
-    return "chestnut" if chestnut_present else "qcom"
+    return "usbgpu" if chestnut_present else "qcom"
 
   def _fetch_and_cache_models(self, source: str) -> list[custom.ModelManagerSP.ModelBundle] | None:
     """Fetches fresh model data from remote and updates cache.
@@ -200,7 +200,7 @@ class ModelFetcher:
   @staticmethod
   def _cache_matches_source(source: str, cached_data: dict) -> bool:
     bundles = cached_data.get("bundles", [])
-    if source == "chestnut":
+    if source == "usbgpu":
       return any(bundle.get("is_big") is True for bundle in bundles)
     return not any(bundle.get("is_big") is True for bundle in bundles)
 
@@ -261,10 +261,10 @@ def get_cached_bundles(params: Params, source: str) -> list[custom.ModelManagerS
 
 
 if __name__ == "__main__":
-  from openpilot.selfdrive.modeld.helpers import chestnut_present
+  from openpilot.selfdrive.modeld.helpers import usbgpu_present
   params = Params()
   model_fetcher = ModelFetcher(params)
-  bundles = model_fetcher.get_bundles_for_source(ModelFetcher.active_source(chestnut_present()))
+  bundles = model_fetcher.get_bundles_for_source(ModelFetcher.active_source(usbgpu_present()))
   for bundle in bundles:
     for model in bundle.models:
       model_overrides = {override.key: override.value for override in bundle.overrides}