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Author SHA1 Message Date
nayan bc6e823976 don't like this. but whatever 2026-08-20 15:17:31 -04:00
nayan cee6a6bdac more 2026-08-20 15:09:29 -04:00
nayan 8d9f3971b0 no 2026-08-20 14:59:12 -04:00
Nayan 931ebf1f5a Merge branch 'master' into model-panel-upgrades 2026-08-20 14:47:30 -04:00
nayan bdda9006fd init 2026-08-20 14:29:52 -04:00
593 changed files with 15812 additions and 27406 deletions
+1 -3
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@@ -1,10 +1,8 @@
* text=auto eol=lf
* text=auto
# to move existing files into LFS:
# git add --renormalize .
*.onnx filter=lfs diff=lfs merge=lfs -text
openpilot/selfdrive/modeld/models/big_*_tinygrad.pkl filter=lfs diff=lfs merge=lfs -text
openpilot/sunnypilot/modeld_v2/models/*.pkl filter=lfs diff=lfs merge=lfs -text
*.svg filter=lfs diff=lfs merge=lfs -text
*.png filter=lfs diff=lfs merge=lfs -text
*.gif filter=lfs diff=lfs merge=lfs -text
+11
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@@ -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
+43
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@@ -0,0 +1,43 @@
exclude-labels:
- 'no-changelog'
categories:
- title: '🚀 Features'
labels:
- 'feature'
- 'enhancement'
- title: '🐛 Bug Fixes'
collapse-after: 5
labels:
- 'fix'
- 'bugfix'
- 'bug'
- title: '🧰 Maintenance'
collapse-after: 5
label: 'chore'
change-template: '- $TITLE @$AUTHOR (#$NUMBER)'
change-title-escapes: '\<*_&'
replacers:
- search: '/[Ss][Uu][Nn][Nn][Yy][Pp][Ii][Ll][Oo][Tt]/g'
replace: 'sunnypilot'
- search: '/\b[Ss][Pp]\b/g'
replace: 'SP'
version-resolver:
major:
labels:
- 'major'
minor:
labels:
- 'minor'
patch:
labels:
- 'patch'
default: patch
name-template: 'v$RESOLVED_VERSION 🚀'
tag-template: 'v$RESOLVED_VERSION'
version-template: "0.$MAJOR.$MINOR.$PATCH" # The day OP becomes v1, we need to bump this
tag-prefix: "v0." # The day OP becomes v1, we need to bump this
prerelease-identifier: "staging"
template: |
## Changes
$CHANGES
@@ -8,23 +8,18 @@ on:
required: true
type: string
target_hardware:
description: 'Hardware target to compile for (qcom or chestnut)'
description: 'Hardware target to compile for (qcom or usbgpu)'
required: true
type: choice
default: 'qcom'
options:
- qcom
- chestnut
- usbgpu
hf_repo:
description: 'Hugging Face dataset repository'
required: false
type: string
default: 'sunnypilot/sunnypilot_models_v1'
docs_repo:
description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
required: false
type: string
default: 'sunnypilot/sunnypilot-models'
jobs:
setup:
@@ -39,9 +34,9 @@ jobs:
- name: Checkout sunnypilot repo
uses: actions/checkout@v4
with:
repository: sunnypilot/sunnypilot
path: sunnypilot
submodules: recursive
fetch-depth: 1
- name: Get tinygrad_repo ref
id: get-tinygrad-ref
@@ -52,20 +47,19 @@ jobs:
echo "tinygrad_ref=$ref" >> $GITHUB_OUTPUT
echo "tinygrad_ref is $ref"
- name: Checkout docs repo (gh-pages)
- name: Checkout docs repo (sunnypilot-models, gh-pages)
uses: actions/checkout@v4
with:
repository: ${{ inputs.docs_repo }}
repository: sunnypilot/sunnypilot-models
ref: gh-pages
path: docs
ssh-key: ${{ secrets.CI_SUNNYPILOT_DOCS_PRIVATE_KEY }}
fetch-depth: 1
- name: Get next JSON version to use (from GitHub docs repo)
id: get-json
run: |
cd docs/docs
PREFIX="driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_' || '' }}v"
PREFIX="driving_models_${{ inputs.target_hardware == 'usbgpu' && 'usbgpu_' || '' }}v"
latest=$(ls ${PREFIX}*.json | sed -E "s/${PREFIX}([0-9]+)\.json/\1/" | sort -n | tail -1)
next=$((latest+1))
json_file="${PREFIX}${next}.json"
@@ -84,7 +78,6 @@ jobs:
- name: Get next recompiled dir number
id: create-recompiled-dir
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
HF_REPO: ${{ github.event.inputs.hf_repo }}
run: |
pip install huggingface_hub
@@ -124,7 +117,6 @@ jobs:
json_version: ${{ needs.setup.outputs.json_version }}
target_hardware: ${{ github.event.inputs.target_hardware }}
hf_repo: ${{ github.event.inputs.hf_repo }}
docs_repo: ${{ inputs.docs_repo }}
set_min_version: ${{ github.event.inputs.set_min_version }}
tinygrad_ref: ${{ needs.setup.outputs.tinygrad_ref }}
secrets: inherit
@@ -169,7 +161,6 @@ jobs:
target_hardware: ${{ github.event.inputs.target_hardware }}
artifact_suffix: -retry
hf_repo: ${{ github.event.inputs.hf_repo }}
docs_repo: ${{ inputs.docs_repo }}
set_min_version: ${{ github.event.inputs.set_min_version }}
tinygrad_ref: ${{ needs.setup.outputs.tinygrad_ref }}
secrets: inherit
-492
View File
@@ -1,492 +0,0 @@
name: Build default models
on:
workflow_dispatch:
inputs:
target:
description: 'Model target to build'
required: true
type: choice
options:
- small
- big
- dm
workflow_call:
inputs:
target:
description: 'Model target to build (small, big, or dm)'
required: true
type: string
concurrency:
group: build-default-models-${{ inputs.target }}
cancel-in-progress: false
env:
HF_REPO: sunnypilot/sunnypilot_models_v1
jobs:
resolve:
runs-on: ubuntu-24.04
outputs:
model_name: ${{ steps.resolve.outputs.model_name }}
safe_model_name: ${{ steps.resolve.outputs.safe_model_name }}
onnx_ref: ${{ steps.resolve.outputs.onnx_ref }}
onnx_path: ${{ steps.resolve.outputs.onnx_path }}
hf_defaults_path: ${{ steps.resolve.outputs.hf_defaults_path }}
tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- id: resolve
run: |
export PYTHONPATH=${{ github.workspace }}
if [ "${{ inputs.target }}" = "big" ]; then
NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
HF_DEFAULTS_PATH="models/defaults/big"
ONNX_PATH="openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl"
elif [ "${{ inputs.target }}" = "dm" ]; then
ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
HF_DEFAULTS_PATH="models/defaults/dm"
NAME="dmonitoring_model ($(git log -1 --format=%cd --date=format:'%B %d, %Y' -- "$ONNX_PATH"))"
else
NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL; print(DEFAULT_MODEL)")
ONNX_PATH="openpilot/selfdrive/modeld/models/driving_supercombo.onnx"
HF_DEFAULTS_PATH="models/defaults/small"
fi
ONNX_REF=""
[ -n "$ONNX_PATH" ] && ONNX_REF=$(git log -1 --format='%H' -- "$ONNX_PATH")
TINYGRAD_REF=$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)
if [ -z "$TINYGRAD_REF" ]; then
echo "::error::Failed to resolve tinygrad ref"
exit 1
fi
SAFE_NAME="${NAME// /-}"
echo "model_name=${NAME}" >> $GITHUB_OUTPUT
echo "safe_model_name=${SAFE_NAME}" >> $GITHUB_OUTPUT
echo "onnx_ref=${ONNX_REF}" >> $GITHUB_OUTPUT
echo "onnx_path=${ONNX_PATH}" >> $GITHUB_OUTPUT
echo "hf_defaults_path=${HF_DEFAULTS_PATH}" >> $GITHUB_OUTPUT
echo "tinygrad_ref=${TINYGRAD_REF}" >> $GITHUB_OUTPUT
build_small_model:
needs: resolve
if: ${{ inputs.target == 'small' }}
runs-on: [self-hosted, tici]
env:
MODELS_DIR: openpilot/selfdrive/modeld/models
COMPILER: tinygrad_repo/examples/openpilot
SMALL_ONNX: openpilot/selfdrive/modeld/models/driving_supercombo.onnx
SMALL_PKL: openpilot/selfdrive/modeld/models/driving_tinygrad.pkl
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Pull small ONNX via LFS
run: git lfs pull -I "${{ env.SMALL_ONNX }}"
- name: Set environment variables
run: |
source /etc/profile
export UV_PROJECT_ENVIRONMENT=${HOME}/venv
export UV_PYTHON_PREFERENCE=managed
export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
uv sync --frozen
printenv >> $GITHUB_ENV
- name: Disable powersave
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
- name: Compile small model from ONNX
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
env ${TG_FLAGS} python3 ${{ github.workspace }}/${{ env.COMPILER }}/compile_onnx.py \
${{ github.workspace }}/${{ env.SMALL_ONNX }} \
${{ github.workspace }}/${{ env.SMALL_PKL }} \
--device-input "*" --out-of-band --benchmark-runs 1
- name: Prepare output
env:
MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
export PYTHONPATH=${{ github.workspace }}
MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
OUTPUT_DIR="${{ github.workspace }}/small_output"
PKL_BASE="driving_tinygrad.pkl"
mkdir -p "$OUTPUT_DIR"
cp "$MODELS_DIR/${PKL_BASE}" "$OUTPUT_DIR/"
ONNX_SHA256=$(git cat-file blob "$(git ls-files -s "${{ github.workspace }}/${{ env.SMALL_ONNX }}" | awk '{print $2}')" | grep '^oid sha256:' | cut -d: -f2)
python3 "${{ github.workspace }}/release/ci/model_generator.py" \
--model-dir "$MODELS_DIR" \
--output-dir "$OUTPUT_DIR" \
--custom-name "$MODEL_NAME" \
--upstream-branch "${{ needs.resolve.outputs.onnx_ref }}" \
--onnx-sha256 "$ONNX_SHA256"
echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
- name: Upload small model artifact
uses: actions/upload-artifact@v4
with:
name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
path: ${{ github.workspace }}/small_output/
- name: Upload artifact name file
uses: actions/upload-artifact@v4
with:
name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
path: ${{ github.workspace }}/small_output/artifact_name.txt
- name: Re-enable powersave
if: always()
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
build_big_model:
needs: resolve
if: ${{ inputs.target == 'big' }}
runs-on: [self-hosted, chestnut]
env:
MODELS_DIR: openpilot/selfdrive/modeld/models
COMPILER: tinygrad_repo/examples/openpilot
BIG_PKL: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Pull big PKL via LFS
run: git lfs pull -I "${{ env.BIG_PKL }}"
- name: Set environment variables
run: |
source /etc/profile
export UV_PROJECT_ENVIRONMENT=${HOME}/venv
export UV_PYTHON_PREFERENCE=managed
export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
uv sync --frozen
printenv >> $GITHUB_ENV
- name: Disable powersave
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
- name: Wait for chestnut PCIe link
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
python3 -c "
import time
from openpilot.system.hardware.chestnut.flash import link_up
for i in range(10):
if link_up():
print(f'PCIe link up after {i+1} attempt(s)')
break
time.sleep(1)
else:
raise RuntimeError('Chestnut PCIe link not ready after 10 attempts')
"
- name: Compile big warp
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
CHESTNUT_TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32"
COMPILER="${{ github.workspace }}/tinygrad_repo/examples/openpilot"
MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
for res in $(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')"); do
CAM_W=$(echo $res | cut -d x -f1)
CAM_H=$(echo $res | cut -d x -f2)
STRIDE_INFO=$(python3 -c "
import sys
from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
s,y,u,sz = get_nv12_info(int(sys.argv[1]), int(sys.argv[2]))
print(f'{s},{y},{u},{sz}')
" $CAM_W $CAM_H)
WARP_PKL="${MODELS_DIR}/big_driving_warp_${res}_tinygrad.pkl"
env ${CHESTNUT_TG_FLAGS} python3 "${COMPILER}/compile_warp.py" \
--frame ${CAM_W},${CAM_H},${STRIDE_INFO} \
--warp-to ${MODEL_SIZE} \
--layout yuv420 \
--frames 2 \
--output "${WARP_PKL}"
done
- name: Prepare output
env:
MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
export PYTHONPATH=${{ github.workspace }}
MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
OUTPUT_DIR="${{ github.workspace }}/big_output"
PKL_BASE="big_driving_tinygrad.pkl"
mkdir -p "$OUTPUT_DIR"
cp "$MODELS_DIR/${PKL_BASE}" "$OUTPUT_DIR/"
PKL_LFS_SHA256=$(git cat-file blob "$(git ls-files -s "${{ github.workspace }}/${{ env.BIG_PKL }}" | awk '{print $2}')" | grep '^oid sha256:' | cut -d: -f2)
python3 "${{ github.workspace }}/release/ci/model_generator.py" \
--model-dir "$MODELS_DIR" \
--output-dir "$OUTPUT_DIR" \
--custom-name "$MODEL_NAME" \
--upstream-branch "${{ needs.resolve.outputs.onnx_ref }}" \
--onnx-sha256 "$PKL_LFS_SHA256"
cp "$MODELS_DIR"/big_driving_warp_* "$OUTPUT_DIR/" || true
echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
- name: Upload big model artifact
uses: actions/upload-artifact@v4
with:
name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
path: ${{ github.workspace }}/big_output/
- name: Upload artifact name file
uses: actions/upload-artifact@v4
with:
name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
path: ${{ github.workspace }}/big_output/artifact_name.txt
- name: Re-enable powersave
if: always()
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
upload_defaults:
needs: [ resolve, build_small_model, build_big_model, build_dm_model ]
if: |
${{
!cancelled() &&
(inputs.target == 'big' && needs.build_big_model.result == 'success' ||
inputs.target == 'small' && needs.build_small_model.result == 'success' ||
inputs.target == 'dm' && needs.build_dm_model.result == 'success')
}}
runs-on: ubuntu-24.04
permissions:
id-token: write
contents: write
steps:
- uses: actions/checkout@v4
- name: Pull LFS for resolved ONNX files
if: ${{ needs.resolve.outputs.onnx_path != '' }}
run: git lfs pull -I "${{ needs.resolve.outputs.onnx_path }}"
- name: Install huggingface_hub
run: pip install --upgrade "huggingface_hub>=0.22.0"
- name: Download artifact name
if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
uses: actions/download-artifact@v4
with:
name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
path: artifact_name
- name: Read artifact name
if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
id: artifact
run: |
ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
- name: Download model artifact
if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
uses: actions/download-artifact@v4
with:
name: ${{ steps.artifact.outputs.artifact_name }}
path: output
- name: Upload model to HF
if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
run: |
rm -f output/artifact_name.txt
export PYTHONPATH=$(pwd)
python3 release/ci/upload_default_model.py \
--hf-repo "${{ env.HF_REPO }}" \
--hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
--artifact-name "$ARTIFACT_NAME" \
--model-dir output \
--onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
--onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
--model-name "${{ needs.resolve.outputs.model_name }}" \
--tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
--run-number "${{ github.run_number }}"
- name: Download DM artifact
if: ${{ inputs.target == 'dm' }}
uses: actions/download-artifact@v4
with:
name: dm-model-${{ github.run_number }}
path: dm_output
- name: Generate DM metadata and upload to HF
if: ${{ inputs.target == 'dm' }}
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
export PYTHONPATH=$(pwd)
python3 -c "
import json, hashlib
from pathlib import Path
from datetime import datetime, UTC
dm_dir = Path('dm_output')
matches = sorted(dm_dir.glob('dmonitoring_*_tinygrad.pkl'))
assert len(matches) == 1, f'expected one DM pkl in {dm_dir}, found {matches}'
pkl_name = matches[0].name
digest = hashlib.sha256()
with open(dm_dir / pkl_name, 'rb') as f:
while block := f.read(1024*1024):
digest.update(block)
metadata = {
'bundles': [{
'short_name': 'DMMODEL',
'display_name': '${{ needs.resolve.outputs.model_name }}',
'ref': '${{ needs.resolve.outputs.onnx_ref }}',
'tinygrad_ref': '${{ needs.resolve.outputs.tinygrad_ref }}',
'runner': 'tinygrad',
'build_time': datetime.now(UTC).strftime('%Y-%m-%dT%H:%M:%SZ'),
'models': [{
'type': 'chunked',
'artifact': {
'file_name': pkl_name,
'download_uri': {'url': '', 'sha256': digest.hexdigest()}
}
}]
}]
}
with open(dm_dir / 'metadata.json', 'w') as f:
json.dump(metadata, f, indent=2)
print('Generated DM metadata.json')
"
python3 release/ci/upload_default_model.py \
--hf-repo "${{ env.HF_REPO }}" \
--hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
--artifact-name "dm-model-${{ github.run_number }}" \
--model-dir dm_output \
--onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
--onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
--model-name "${{ needs.resolve.outputs.model_name }}" \
--tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
--run-number "${{ github.run_number }}"
build_dm_model:
needs: resolve
if: ${{ inputs.target == 'dm' }}
runs-on: [self-hosted, tici]
env:
DM_ONNX: openpilot/selfdrive/modeld/models/dmonitoring_model.onnx
DM_PKL: openpilot/selfdrive/modeld/models/dmonitoring_model_tinygrad.pkl
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Pull DM ONNX via LFS
run: git lfs pull -I "${{ env.DM_ONNX }}"
- name: Set environment variables
run: |
source /etc/profile
export UV_PROJECT_ENVIRONMENT=${HOME}/venv
export UV_PYTHON_PREFERENCE=managed
export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
uv sync --frozen
printenv >> $GITHUB_ENV
- name: Disable powersave
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
- name: Compile DM model
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
taskset -c 7 env ${TG_FLAGS} python3 \
${{ github.workspace }}/tinygrad_repo/examples/openpilot/compile3.py \
${{ github.workspace }}/${{ env.DM_ONNX }} \
${{ github.workspace }}/${{ env.DM_PKL }}
- name: Compile DM warp
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
COMPILER="${{ github.workspace }}/tinygrad_repo/examples/openpilot"
MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
DM_SIZE=$(python3 -c "from openpilot.common.transformations.model import DM_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
for res in $(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')"); do
CAM_W=$(echo $res | cut -d x -f1)
CAM_H=$(echo $res | cut -d x -f2)
STRIDE_INFO=$(python3 -c "
import sys
from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
s,y,u,sz = get_nv12_info(int(sys.argv[1]), int(sys.argv[2]))
print(f'{s},{y},{u},{sz}')
" $CAM_W $CAM_H)
WARP_PKL="${MODELS_DIR}/dm_warp_${res}_tinygrad.pkl"
taskset -c 7 env ${TG_FLAGS} python3 "${COMPILER}/compile_warp.py" \
--frame ${CAM_W},${CAM_H},${STRIDE_INFO} \
--warp-to ${DM_SIZE} \
--layout luma \
--border-fill 16 \
--transform-device NPY \
--output "${WARP_PKL}"
done
- name: Prepare DM output
run: |
mkdir -p dm_output
cp ${{ github.workspace }}/${{ env.DM_PKL }} dm_output/
cp ${{ github.workspace }}/openpilot/selfdrive/modeld/models/dm_warp_* dm_output/
- name: Upload DM artifact
uses: actions/upload-artifact@v4
with:
name: dm-model-${{ github.run_number }}
path: dm_output/
- name: Re-enable powersave
if: always()
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
@@ -30,7 +30,7 @@ on:
type: boolean
default: true
target_hardware:
description: 'Hardware target to compile for (qcom or chestnut)'
description: 'Hardware target to compile for (qcom or usbgpu)'
required: false
type: string
default: 'qcom'
@@ -39,11 +39,6 @@ on:
required: false
type: string
default: 'sunnypilot/sunnypilot_models_v1'
docs_repo:
description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
required: false
type: string
default: 'sunnypilot/sunnypilot-models'
set_min_version:
description: 'Minimum selector version'
required: false
@@ -106,20 +101,15 @@ on:
default: 'qcom'
options:
- qcom
- chestnut
- usbgpu
hf_repo:
description: 'Hugging Face dataset repository'
required: false
type: string
default: 'sunnypilot/sunnypilot_models_v1'
docs_repo:
description: 'GitHub repo holding the driving_models JSON on its gh-pages branch'
required: false
type: string
default: 'sunnypilot/sunnypilot-models'
env:
RECOMPILED_DIR: recompiled${{ inputs.recompiled_dir }}
JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'chestnut' && 'chestnut_v' || 'v' }}${{ inputs.json_version }}.json
JSON_FILE: docs/docs/driving_models_${{ inputs.target_hardware == 'usbgpu' && 'usbgpu_v' || 'v' }}${{ inputs.json_version }}.json
jobs:
build_model:
@@ -134,17 +124,19 @@ jobs:
publish_model:
if: ${{ !cancelled() && needs.build_model.result == 'success' }}
concurrency:
group: hf-push-${{ inputs.recompiled_dir }}
cancel-in-progress: false
needs: build_model
runs-on: ubuntu-latest
permissions:
actions: read
id-token: write
contents: write
steps:
- name: Checkout docs repo
uses: actions/checkout@v4
with:
repository: ${{ inputs.docs_repo }}
repository: sunnypilot/sunnypilot-models
ref: gh-pages
path: docs
ssh-key: ${{ secrets.CI_SUNNYPILOT_DOCS_PRIVATE_KEY }}
@@ -154,7 +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 $JSON_FILE does not exist!"
@@ -163,8 +155,13 @@ jobs:
python3 -c "
import sys
from huggingface_hub import HfApi
HfApi().repo_info(repo_id=sys.argv[1], repo_type='dataset')
print(f'Success: Repo {sys.argv[1]} exists.')
try:
api = HfApi()
api.repo_info(repo_id=sys.argv[1], repo_type='dataset')
print(f'Success: Repo {sys.argv[1]} exists.')
except Exception as e:
print('HF validation failed:', e)
sys.exit(1)
" "${{ inputs.hf_repo }}"
- name: Download artifact name file
@@ -180,25 +177,22 @@ jobs:
echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
- name: Download and extract model artifact
env:
GH_TOKEN: ${{ github.token }}
ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
run: |
id=$(gh api -X GET "repos/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID/artifacts" -f name="$ARTIFACT_NAME" --jq '.artifacts[0].id')
url=$(curl -sf -o /dev/null -w '%{redirect_url}' -H "Authorization: Bearer $GH_TOKEN" "https://api.github.com/repos/$GITHUB_REPOSITORY/actions/artifacts/$id/zip")
sudo apt-get install -y -qq aria2 > /dev/null
aria2c -q -x16 -s16 -k8M --max-tries=5 --file-allocation=none -o model.zip "$url" && unzip -q model.zip -d output && rm model.zip
uses: actions/download-artifact@v4
with:
name: ${{ steps.read-artifact-name.outputs.artifact_name }}
path: output
- name: Create models folder
env:
ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
run: |
mkdir -p "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}"
cp output/metadata.json "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/"
cp -r output/* "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/"
rm -f "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/artifact_name.txt"
- name: Upload to Hugging Face
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
run: |
hf upload ${{ inputs.hf_repo }} \
@@ -206,12 +200,13 @@ jobs:
"models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/" \
--repo-type=dataset
- name: Update and push JSON to docs repo
- name: Pull gh-pages
run: |
cd docs
git config --global user.name "GitHub Action"
git config --global user.email "action@github.com"
git pull origin gh-pages
- name: Run json_parser.py to update JSON
run: |
FOLDER="${{ inputs.model_folder }}"
if [ "$FOLDER" = "Other" ]; then
FOLDER="${{ inputs.custom_model_folder }}"
@@ -224,27 +219,18 @@ jobs:
[ -n "${{ inputs.version }}" ] && ARGS="$ARGS --version \"${{ inputs.version }}\""
[ -n "${{ inputs.set_min_version }}" ] && ARGS="$ARGS --set-min-version \"${{ inputs.set_min_version }}\""
[ -n "${{ inputs.tinygrad_ref }}" ] && ARGS="$ARGS --tinygrad-ref \"${{ inputs.tinygrad_ref }}\""
eval python3 docs/json_parser.py \
--json-path "$JSON_FILE" \
--recompiled-dir "local_models/$RECOMPILED_DIR" \
--sort-by-date \
$ARGS
for attempt in $(seq 1 10); do
git fetch origin gh-pages
git reset --hard origin/gh-pages
eval python3 json_parser.py \
--json-path "docs/$(basename $JSON_FILE)" \
--recompiled-dir "../local_models/$RECOMPILED_DIR" \
--sort-by-date \
$ARGS
git add docs/"$(basename $JSON_FILE)"
git commit -m "Update $(basename $JSON_FILE) after recompiling model" || { echo "No changes to commit"; exit 0; }
if git push origin gh-pages; then
echo "Push succeeded on attempt $attempt"
exit 0
fi
echo "Push failed (attempt $attempt/10), retrying after backoff..."
sleep $((RANDOM % 10 + 3))
done
echo "All 10 push attempts failed"
exit 1
- name: Push updated JSON to GitHub docs repo
run: |
cd docs
git config --global user.name "GitHub Action"
git config --global user.email "action@github.com"
git checkout gh-pages
git add docs/"$(basename $JSON_FILE)"
git commit -m "Update $(basename $JSON_FILE) after recompiling model" || echo "No changes to commit"
git push origin gh-pages
@@ -1,71 +0,0 @@
name: Compile warp for sunnypilot modeld
on:
workflow_dispatch:
jobs:
compile_warps:
runs-on: [self-hosted, chestnut]
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Set environment variables
run: |
source /etc/profile
export UV_PROJECT_ENVIRONMENT=${HOME}/venv
export UV_PYTHON_PREFERENCE=managed
export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
uv sync --frozen
printenv >> $GITHUB_ENV
- name: Disable powersave
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
- name: Compile Warp Kernels
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
mkdir -p openpilot/sunnypilot/modeld_v2/models/
MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
echo "Model size: $MODEL_SIZE"
echo "Camera resolutions: $CAMERA_RES"
for res in $CAMERA_RES; do
FRAME_PARAM=$(python3 -c "from openpilot.system.camerad.cameras.nv12_info import get_nv12_info; w, h = map(int, '${res}'.split('x')); stride, y_h, uv_h, _ = get_nv12_info(w, h); print(f'{w},{h},{stride},{y_h},{uv_h},{stride * (y_h + uv_h)}')")
WARP_PKL="openpilot/sunnypilot/modeld_v2/models/driving_warp_${res}_tinygrad.pkl"
echo "Compiling $WARP_PKL on QCOM"
taskset -c 7 env DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1 python3 openpilot/sunnypilot/modeld_v2/compile_warp.py \
--frame ${FRAME_PARAM} --warp-to ${MODEL_SIZE} --output "${WARP_PKL}"
BIG_WARP_PKL="openpilot/sunnypilot/modeld_v2/models/big_driving_warp_${res}_tinygrad.pkl"
echo "Compiling $BIG_WARP_PKL on AMD"
taskset -c 7 env DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32 python3 openpilot/sunnypilot/modeld_v2/compile_warp.py \
--frame ${FRAME_PARAM} --warp-to ${MODEL_SIZE} --output "${BIG_WARP_PKL}"
done
- name: Re-enable powersave
if: always()
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
- name: Create Pull Request
uses: peter-evans/create-pull-request@9153d834b60caba6d51c9b9510b087acf9f33f83
with:
author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
token: ${{ secrets.GITHUB_TOKEN }}
commit-message: "[bot] Update warp pkl for modeld_v2"
title: "[bot] Update modeld_v2 Warp"
branch: "auto/compile-warp-kernels"
base: "master"
delete-branch: true
labels: bot
add-paths: |
openpilot/sunnypilot/modeld_v2/models/*.pkl
+8 -9
View File
@@ -18,25 +18,24 @@ concurrency:
env:
GIT_CONFIG_COUNT: 1
GIT_CONFIG_KEY_0: lfs.fetchexclude
GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
jobs:
docs:
name: build docs
runs-on: ${{
(github.repository == 'commaai/openpilot') &&
((github.event_name != 'pull_request') ||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))
&& fromJSON('["namespace-profile-amd64-8x16"]')
|| fromJSON('["ubuntu-24.04"]') }}
runs-on: ubuntu-24.04
steps:
- uses: commaai/timeout@v1
- uses: actions/checkout@v7
- run: ./tools/op.sh setup
with:
submodules: true
# Build
- name: Build docs
run: ./tools/op.sh docs --build
run: |
git lfs pull
python docs/serve.py --build
# Push to docs.comma.ai
- uses: actions/checkout@v7
@@ -1,89 +0,0 @@
name: Download HF model
description: Resolve and download models from HuggingFace in parallel
inputs:
hf_repo:
description: HuggingFace dataset repo
required: true
models:
description: 'JSON array of {hf_path, onnx_hash, canonical} objects'
required: true
dest_dir:
description: Destination directory for downloaded chunks
required: true
tinygrad_ref:
description: 'Tinygrad ref to match bundle against'
required: false
default: ''
runs:
using: composite
steps:
- name: Download models
shell: bash
env:
HF_REPO: ${{ inputs.hf_repo }}
MODELS_JSON: ${{ inputs.models }}
DEST_DIR: ${{ inputs.dest_dir }}
TINYGRAD_REF: ${{ inputs.tinygrad_ref }}
run: |
set -eo pipefail
DOWNLOAD_LIST=$(mktemp)
resolve_chunks() {
local HF_PATH="$1" ONNX_HASH="$2" CANONICAL="$3" DEST_DIR="$4"
local JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_PATH}/default_models.json"
local DEFAULTS BUNDLE ARTIFACT FILE_URL BASE_URL
DEFAULTS=$(curl -fsSL "$JSON_URL")
if [ -n "$TINYGRAD_REF" ]; then
BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" --arg tg "$TINYGRAD_REF" '
. as $root | [.bundles[] | select(.onnx_sha256 == $hash and (.tinygrad_ref == $tg or (.tinygrad_ref == null and $root.tinygrad_ref == $tg)))] | .[0] // empty
')
else
BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '
[.bundles[] | select(.onnx_sha256 == $hash)] | .[0] // empty
')
fi
if [ -z "$BUNDLE" ] || [ "$BUNDLE" = "null" ]; then
echo "::error::No model bundle found matching ONNX hash $ONNX_HASH (tinygrad ref: $TINYGRAD_REF) in $HF_PATH"
return 1
fi
ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
FILE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url')
BASE_URL=$(echo "$FILE_URL" | sed 's|/[^/]*$||')
mkdir -p "$DEST_DIR"
ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${FILE_URL}', safe=':/'))")
printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${CANONICAL}" >> "$DOWNLOAD_LIST"
if [ "$CANONICAL" = "dmonitoring_model_tinygrad.pkl" ]; then
for warp in dm_warp_1928x1208_tinygrad.pkl dm_warp_1344x760_tinygrad.pkl; do
ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${warp}', safe=':/'))")
printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${warp}" >> "$DOWNLOAD_LIST"
done
elif [ "$CANONICAL" = "big_driving_tinygrad.pkl" ]; then
for warp in big_driving_warp_1928x1208_tinygrad.pkl big_driving_warp_1344x760_tinygrad.pkl; do
ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${warp}', safe=':/'))")
printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${warp}" >> "$DOWNLOAD_LIST"
done
fi
}
echo "$MODELS_JSON" | jq -c '.[]' | while IFS= read -r model; do
HF_PATH=$(echo "$model" | jq -r '.hf_path')
ONNX_HASH=$(echo "$model" | jq -r '.onnx_hash')
CANONICAL=$(echo "$model" | jq -r '.canonical')
resolve_chunks "$HF_PATH" "$ONNX_HASH" "$CANONICAL" "$DEST_DIR"
done
TOTAL=$(wc -l < "$DOWNLOAD_LIST")
echo "Downloading $TOTAL files with 8 parallel connections..."
xargs -P8 -d'\n' -I{} bash -c '
URL="${1%% *}"
DEST="${1#* }"
echo "Downloading $(basename "$DEST")"
curl -fsSL --retry 3 --retry-delay 5 -o "$DEST" "$URL"
' _ {} < "$DOWNLOAD_LIST"
rm -f "$DOWNLOAD_LIST"
+9 -7
View File
@@ -1,8 +1,8 @@
name: Sync comma's LFS
env:
LFS_URL: 'https://huggingface.co/sunnypilot/sunnypilot-lfs.git/info/lfs'
LFS_PUSH_URL: 'https://huggingface.co/sunnypilot/sunnypilot-lfs.git/info/lfs'
LFS_URL: 'https://gitlab.com/sunnypilot/public/sunnypilot-new-lfs.git/info/lfs'
LFS_PUSH_URL: 'ssh://git@gitlab.com/sunnypilot/public/sunnypilot-new-lfs.git'
on:
schedule:
@@ -40,12 +40,14 @@ jobs:
git config --global user.name 'GitHub Action'
git config --global user.email 'action@github.com'
- name: Setup hf
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
- name: Set up SSH
uses: webfactory/ssh-agent@v0.9.0
with:
ssh-private-key: ${{ secrets.SSH_PRIVATE_KEY }}
- name: Add GitLab public keys
run: |
git config --global credential.helper store
echo "https://user:${HF_TOKEN}@huggingface.co" > ~/.git-credentials
ssh-keyscan -H gitlab.com >> ~/.ssh/known_hosts
- name: Ensure branch
run: |
+28
View File
@@ -0,0 +1,28 @@
name: Release Drafter
on:
push:
branches:
- master
tags:
- 'v*'
pull_request_target:
types: [opened, reopened, synchronize]
workflow_dispatch:
permissions:
contents: read
jobs:
update_release_draft:
permissions:
contents: write
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: release-drafter/release-drafter@v6
with:
config-name: release-drafter.yml
prerelease: ${{ !startsWith(github.ref, 'refs/tags/v') }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+1 -5
View File
@@ -7,7 +7,7 @@ on:
env:
GIT_CONFIG_COUNT: 1
GIT_CONFIG_KEY_0: lfs.fetchexclude
GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
jobs:
build___nightly:
@@ -34,7 +34,3 @@ jobs:
- run: ./tools/op.sh setup
- name: Push __nightly
run: BRANCH=__nightly tools/release/build_stripped.sh
- name: Push chestnut nightly
run: |
git lfs pull --exclude=''
INCLUDE_BIG_MODEL=1 BRANCH=__nightly-chestnut tools/release/build_stripped.sh
+1 -1
View File
@@ -11,7 +11,7 @@ env:
PYTHONPATH: ${{ github.workspace }}
GIT_CONFIG_COUNT: 1
GIT_CONFIG_KEY_0: lfs.fetchexclude
GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
jobs:
package_updates:
+68 -124
View File
@@ -31,7 +31,7 @@ on:
type: string
default: ''
target_hardware:
description: 'Hardware target to compile for (qcom or chestnut)'
description: 'Hardware target to compile for (qcom or usbgpu)'
required: false
type: string
default: 'qcom'
@@ -57,7 +57,7 @@ on:
type: choice
options:
- qcom
- chestnut
- usbgpu
default: 'qcom'
@@ -100,60 +100,23 @@ jobs:
commit_date=$(git log -1 --format=%cd --date=format:'%B %d, %Y')
echo "model_date=${commit_date}" >> $GITHUB_OUTPUT
cat $GITHUB_OUTPUT
- name: Fetch Models
run: |
- run: |
cd ${{ github.workspace }}/openpilot/openpilot
fetch_lfs() {
sudo apt-get install -y -qq aria2 > /dev/null # Parallel ranges because gh is flaky
LFS_URL=$(git config -f "$(git rev-parse --show-toplevel)/.lfsconfig" lfs.url)
for f in "$@"; do
grep -qs "^version https://git-lfs" "$f" || continue
OID=$(awk -F'sha256:' '/^oid/{print $2}' "$f"); SIZE=$(awk '/^size/{print $2}' "$f")
HREF=$(curl -fsSL --retry 3 -X POST -H "Accept: application/vnd.git-lfs+json" -H "Content-Type: application/vnd.git-lfs+json" "$LFS_URL/objects/batch" \
-d "{\"operation\":\"download\",\"transfer\":[\"basic\"],\"objects\":[{\"oid\":\"$OID\",\"size\":$SIZE}]}" | jq -r '.objects[0].actions.download.href')
aria2c -x 16 -s 16 -k 16M --max-tries=5 --retry-wait=5 --file-allocation=none --summary-interval=30 --allow-overwrite=true \
-d "$(dirname "$f")" -o "$(basename "$f")" "$HREF"
echo "$OID $f" | sha256sum -c -
done
}
UPSTREAM_PKL=selfdrive/modeld/models/big_driving_tinygrad.pkl
if [ "${{ inputs.target_hardware }}" != "chestnut" ]; then
git lfs pull -X "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/dmonitoring_*.onnx,**/selfdrive/modeld/models/big_*.pkl,**/selfdrive/modeld/models/dmonitoring_*.pkl"
rm -f selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/dmonitoring_*.onnx selfdrive/modeld/models/big_*.pkl selfdrive/modeld/models/dmonitoring_*.pkl
elif compgen -G "selfdrive/modeld/models/big_*.onnx" > /dev/null; then
fetch_lfs selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/big_*.pkl
find selfdrive/modeld/models -type f \( -name "*.onnx" -o -name "*.pkl" \) ! -name "big_*.onnx" ! -name "big_*.pkl" -delete
elif [ -f "$UPSTREAM_PKL" ]; then
echo "No big model ONNX tracked: converting commaai's precompiled $UPSTREAM_PKL, with the tinygrad it was built with"
fetch_lfs "$UPSTREAM_PKL"
find selfdrive/modeld/models -type f \( -name "*.onnx" -o -name "*.pkl" \) ! -path "$UPSTREAM_PKL" -delete
GITMODULES="$(git rev-parse --show-toplevel)/.gitmodules"
TG_NAME=$(git config -f "$GITMODULES" --get-regexp '^submodule\..*\.path$' | awk '$2 == "tinygrad_repo" {sub(/^submodule\./, "", $1); sub(/\.path$/, "", $1); print $1}')
TG_URL=$(git config -f "$GITMODULES" "submodule.$TG_NAME.url" | sed 's|^\.\./\.\./|https://github.com/|')
echo "$TG_URL $(git rev-parse HEAD:tinygrad_repo) $(sha256sum "$UPSTREAM_PKL" | cut -d' ' -f1)" > selfdrive/modeld/models/upstream_pkl.txt
if [ "${{ inputs.target_hardware }}" != "usbgpu" ]; then
git lfs pull -X "selfdrive/modeld/models/big_*.onnx" -X "selfdrive/modeld/models/dmonitoring_*.onnx"
rm -f selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/dmonitoring_*.onnx
else
echo "::error::no big model ONNX or precompiled big_driving_tinygrad.pkl at this ref"
exit 1
fi
if grep -lIF "version https://git-lfs.github.com/spec/v1" selfdrive/modeld/models/*.onnx selfdrive/modeld/models/*.pkl 2>/dev/null; then
echo "::error::the ONNX or PKL files above are still LFS pointers, not real models"
exit 1
git lfs pull -I "selfdrive/modeld/models/big_*.onnx"
find selfdrive/modeld/models -name "*.onnx" ! -name "big_*.onnx" -delete
fi
- name: 'Upload Artifact'
uses: actions/upload-artifact@v4
with:
name: models-${{ env.REF }}${{ inputs.artifact_suffix }}
compression-level: 0
path: |
${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.pkl
${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/upstream_pkl.txt
if-no-files-found: error
path: ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
build_model:
runs-on: [self-hosted, "${{ inputs.target_hardware == 'chestnut' && 'chestnut' || 'tici' }}"]
runs-on: [self-hosted, tici]
needs: get_model
env:
MODEL_NAME: ${{ inputs.custom_name || inputs.upstream_branch }} (${{ needs.get_model.outputs.model_date }})
@@ -164,6 +127,8 @@ jobs:
fetch-depth: 1
submodules: recursive
- run: git lfs pull
- name: Set environment variables
id: set-env
run: |
@@ -175,6 +140,9 @@ jobs:
export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
uv sync --frozen
printenv >> $GITHUB_ENV
if [[ "${{ runner.debug }}" == "1" ]]; then
cat $GITHUB_OUTPUT
fi
- name: Setup build environment
run: |
@@ -186,9 +154,13 @@ jobs:
echo "VERSION: ${{ steps.set-env.outputs.version }}"
echo "UV_PROJECT_ENVIRONMENT: ${UV_PROJECT_ENVIRONMENT}"
echo "VIRTUAL_ENV: ${VIRTUAL_ENV}"
echo "-------"
if [[ "${{ runner.debug }}" == "1" ]]; then
printenv
fi
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
rm -rf ${{ env.MODELS_DIR }}/*.onnx*
rm -rf ${{ env.MODELS_DIR }}/*.onnx
- name: Download model artifacts
uses: actions/download-artifact@v4
@@ -208,89 +180,62 @@ jobs:
MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
TG_FLAGS_QCOM="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 OPENPILOT_HACKS=1"
if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
echo "CHESTNUT build"
export CHESTNUT=1
TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32"
if [ "${{ inputs.target_hardware }}" == "usbgpu" ]; then
echo "USBGPU build"
export USBGPU=1
TG_FLAGS="DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
else
echo "QCOM build"
TG_FLAGS="$TG_FLAGS_QCOM"
TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
OUTPUT_PKL="${{ env.MODELS_DIR }}/driving_tinygrad.pkl"
fi
NATIVE_PKL=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "*.pkl" -print -quit)
# Generate metadata for all ONNX files
find "${{ env.MODELS_DIR }}" -maxdepth 1 -name '*.onnx' | while IFS= read -r onnx_file; do
echo "Generating metadata: $onnx_file"
env ${TG_FLAGS} python3 "${{ env.MODELS_DIR }}/../get_model_metadata.py" "$onnx_file" || true
done
if [ -f "${{ env.MODELS_DIR }}/upstream_pkl.txt" ]; then
read -r TG_URL TG_SHA _ < "${{ env.MODELS_DIR }}/upstream_pkl.txt"
echo "Converting commaai's precompiled model with tinygrad $TG_SHA"
UPSTREAM_TG="${{ runner.temp }}/upstream_tinygrad"
rm -rf "$UPSTREAM_TG" && git init -q "$UPSTREAM_TG" && git -C "$UPSTREAM_TG" fetch -q --depth 1 "$TG_URL" "$TG_SHA" && git -C "$UPSTREAM_TG" checkout -q FETCH_HEAD
CONVERTED="${{ runner.temp }}/big_driving_tinygrad_plain.pkl"
env DEV=USB+AMD PYTHONPATH="$UPSTREAM_TG:${{ github.workspace }}" taskset -c 7 python3 openpilot/sunnypilot/modeld_v2/convert_upstream_pkl.py \
"${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl" "$CONVERTED"
mv "$CONVERTED" "$OUTPUT_PKL"
elif NEW_ARCH_ONNX=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "${{ inputs.target_hardware == 'chestnut' && 'big_' || '' }}*driving*.onnx" -print -quit) &&
[ -n "$NEW_ARCH_ONNX" ] && grep -qa new_img "$NEW_ARCH_ONNX"; then # the new architecture: one ONNX taking the warped frames as new_img
echo "Compiling new architecture ONNX: $NEW_ARCH_ONNX"
env ${TG_FLAGS} taskset -c 7 python3 openpilot/sunnypilot/modeld_v2/compile_modeld_v2.py \
"$NEW_ARCH_ONNX" "$OUTPUT_PKL" --device-input "*" --benchmark-runs 1
else
echo "Detected onnx architecture. Routing to native compile_modeld.py."
# Detect model type and build compile args
VISION_ONNX=""
for f in "${{ env.MODELS_DIR }}/driving_vision.onnx" "${{ env.MODELS_DIR }}/big_driving_vision.onnx"; do
[ -f "$f" ] && VISION_ONNX="$f" && break
done
POLICY_ONNX=""
for f in "${{ env.MODELS_DIR }}/driving_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_policy.onnx"; do
[ -f "$f" ] && POLICY_ONNX="$f" && break
done
OFF_POLICY_ONNX=""
for f in "${{ env.MODELS_DIR }}/driving_off_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_off_policy.onnx"; do
[ -f "$f" ] && OFF_POLICY_ONNX="$f" && break
done
ON_POLICY_ONNX=""
for f in "${{ env.MODELS_DIR }}/driving_on_policy.onnx" "${{ env.MODELS_DIR }}/big_driving_on_policy.onnx"; do
[ -f "$f" ] && ON_POLICY_ONNX="$f" && break
done
SUPERCOMBO_ONNX=""
for f in "${{ env.MODELS_DIR }}/supercombo.onnx" "${{ env.MODELS_DIR }}/driving_supercombo.onnx" "${{ env.MODELS_DIR }}/big_supercombo.onnx" "${{ env.MODELS_DIR }}/big_driving_supercombo.onnx"; do
[ -f "$f" ] && SUPERCOMBO_ONNX="$f" && break
done
MODEL_TYPE="" ONNX_ARGS="" OUTPUT_NAME=""
if [ -f "$VISION_ONNX" ]; then
ONNX_ARGS="--vision-onnx $VISION_ONNX"
if [ -f "$ON_POLICY_ONNX" ] && [ -f "$OFF_POLICY_ONNX" ]; then
MODEL_TYPE=vision_multi_policy
ONNX_ARGS="$ONNX_ARGS --off-policy-onnx $OFF_POLICY_ONNX --on-policy-onnx $ON_POLICY_ONNX"
elif [ -f "$OFF_POLICY_ONNX" ] && [ -f "$POLICY_ONNX" ]; then
MODEL_TYPE=vision_multi_policy
ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX --off-policy-onnx $OFF_POLICY_ONNX"
elif [ -f "$POLICY_ONNX" ]; then
MODEL_TYPE=vision_policy
ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX"
fi
elif [ -f "$SUPERCOMBO_ONNX" ]; then
MODEL_TYPE=supercombo
ONNX_ARGS="--supercombo-onnx $SUPERCOMBO_ONNX"
# Detect model type and build compile args
VISION_ONNX="${{ env.MODELS_DIR }}/driving_vision.onnx"
POLICY_ONNX="${{ env.MODELS_DIR }}/driving_policy.onnx"
OFF_POLICY_ONNX="${{ env.MODELS_DIR }}/driving_off_policy.onnx"
ON_POLICY_ONNX="${{ env.MODELS_DIR }}/driving_on_policy.onnx"
SUPERCOMBO_ONNX=""
for f in "${{ env.MODELS_DIR }}/supercombo.onnx" "${{ env.MODELS_DIR }}/driving_supercombo.onnx"; do
if [ -f "$f" ]; then
SUPERCOMBO_ONNX="$f"
break
fi
done
if [ -n "$MODEL_TYPE" ]; then
echo "Detected: $MODEL_TYPE -> $OUTPUT_PKL"
env ${TG_FLAGS} taskset -c 7 python3 "$COMPILE_MODELD" \
--model-type $MODEL_TYPE \
--model-size $MODEL_SIZE \
--camera-resolutions $CAMERA_RES \
$ONNX_ARGS \
--output "$OUTPUT_PKL"
MODEL_TYPE="" ONNX_ARGS="" OUTPUT_NAME=""
if [ -f "$VISION_ONNX" ]; then
ONNX_ARGS="--vision-onnx $VISION_ONNX"
if [ -f "$ON_POLICY_ONNX" ] && [ -f "$OFF_POLICY_ONNX" ]; then
MODEL_TYPE=vision_multi_policy
ONNX_ARGS="$ONNX_ARGS --off-policy-onnx $OFF_POLICY_ONNX --on-policy-onnx $ON_POLICY_ONNX"
elif [ -f "$OFF_POLICY_ONNX" ] && [ -f "$POLICY_ONNX" ]; then
MODEL_TYPE=vision_multi_policy
ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX --off-policy-onnx $OFF_POLICY_ONNX"
elif [ -f "$POLICY_ONNX" ]; then
MODEL_TYPE=vision_policy
ONNX_ARGS="$ONNX_ARGS --policy-onnx $POLICY_ONNX"
fi
elif [ -f "$SUPERCOMBO_ONNX" ]; then
MODEL_TYPE=supercombo
ONNX_ARGS="--supercombo-onnx $SUPERCOMBO_ONNX"
fi
if [ -n "$MODEL_TYPE" ]; then
echo "Detected: $MODEL_TYPE -> $OUTPUT_PKL"
env ${TG_FLAGS} python3 "$COMPILE_MODELD" \
--model-type $MODEL_TYPE \
--model-size $MODEL_SIZE \
--camera-resolutions $CAMERA_RES \
$ONNX_ARGS \
--output "$OUTPUT_PKL"
fi
- name: Prepare Output
@@ -301,7 +246,8 @@ jobs:
# Copy the model files
rsync -avm \
--include='*.dlc' \
--include='/${{ inputs.target_hardware == 'chestnut' && 'big_' || '' }}driving_tinygrad.pkl' \
--include='*.chunk*' \
--include='*.chunkmanifest' \
--exclude='*' \
--delete-excluded \
--chown=comma:comma \
@@ -312,7 +258,6 @@ jobs:
--output-dir "${{ env.OUTPUT_DIR }}" \
--custom-name "${{ env.MODEL_NAME }}" \
--upstream-branch "${{ inputs.upstream_branch }}" \
$([ -f "${{ env.MODELS_DIR }}/upstream_pkl.txt" ] && echo "--onnx-sha256 $(cut -d' ' -f3 "${{ env.MODELS_DIR }}/upstream_pkl.txt")") \
${{ inputs.is_20hz && '--is-20hz' || '' }}
- name: Write artifact name to file
@@ -324,7 +269,6 @@ jobs:
with:
name: model-${{ env.MODEL_NAME }}${{ inputs.artifact_suffix }}-${{ github.run_number }}
path: ${{ env.OUTPUT_DIR }}
compression-level: 0
- name: Upload artifact name file
uses: actions/upload-artifact@v4
@@ -36,11 +36,8 @@ jobs:
publish_concurrency_group: ${{ steps.strategy.outputs.publish_concurrency_group }}
is_stable_branch: ${{ steps.strategy.outputs.is_stable_branch }}
build: ${{ steps.strategy.outputs.build }}
include_big_model: ${{ steps.strategy.outputs.include_big_model }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Extract deploy strategy
id: strategy
run: |
@@ -81,9 +78,6 @@ jobs:
stable_version=$(cat openpilot/sunnypilot/common/version.h | grep SUNNYPILOT_VERSION | sed -e 's/[^0-9|.]//g');
echo "version=$([ "$is_stable_branch" = "true" ] && echo "$stable_version" || echo "$BUILD")" >> $GITHUB_OUTPUT
echo "extra_version_identifier=${environment}" >> $GITHUB_OUTPUT
include_big_model="$(echo "$CONFIG" | jq -r '.include_big_model // false')";
echo "include_big_model=$include_big_model" >> $GITHUB_OUTPUT
fi
echo "build=$BUILD" >> $GITHUB_OUTPUT
cat $GITHUB_OUTPUT
@@ -98,8 +92,6 @@ jobs:
}}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Wait for Tests
uses: ./.github/workflows/wait-for-action # Path to where you place the action
with:
@@ -123,7 +115,6 @@ jobs:
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 1
submodules: recursive
ref: ${{ env.SOURCE_BRANCH }}
repository: ${{ github.event.pull_request.head.repo.fork && github.event.pull_request.head.repo.full_name || github.repository }}
@@ -170,10 +161,7 @@ jobs:
scons -j1 cache_dir="$SCONS_CACHE" --minimal \
openpilot/selfdrive/locationd openpilot/sunnypilot/selfdrive/locationd
echo "Building rest of sunnypilot"
sudo rm -rf /tmp/* || true
mkdir -p "$BUILD_DIR/tmp"
export TMPDIR="$BUILD_DIR/tmp"
SKIP_TINYGRAD_COMPILE=1 /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
/usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
touch ${BUILD_DIR}/prebuilt
if [[ "${{ runner.debug }}" == "1" ]]; then
ls -la ${BUILD_DIR}
@@ -215,285 +203,22 @@ jobs:
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
prepare_chestnut:
needs: [ prepare_strategy ]
runs-on: ubuntu-24.04
if: ${{ needs.prepare_strategy.outputs.include_big_model == 'true' }}
concurrency:
group: prepare-chestnut
cancel-in-progress: false
outputs:
onnx_sha256: ${{ steps.resolve.outputs.onnx_sha256 }}
tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
env:
GH_REPO: ${{ github.repository }}
HF_REPO: sunnypilot/sunnypilot_models_v1
HF_DEFAULTS_PATH: models/defaults/big
steps:
- name: Resolve tinygrad ref via API
id: resolve
run: |
REF="${{ github.head_ref || github.ref_name }}"
BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl?ref=${REF}" --jq '.sha')
[ -n "$BLOB_SHA" ] || { echo "::error::Failed to resolve big_driving_tinygrad.pkl blob SHA"; exit 1; }
ONNX_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
echo "big PKL hash: $ONNX_HASH"
[ -n "$ONNX_HASH" ] || { echo "::error::Failed to extract big PKL hash"; exit 1; }
echo "onnx_sha256=$ONNX_HASH" >> "$GITHUB_OUTPUT"
TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
echo "tinygrad ref: $TINYGRAD_REF"
echo "tinygrad_ref=$TINYGRAD_REF" >> "$GITHUB_OUTPUT"
JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
check_defaults() {
DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" --arg ref "$TINYGRAD_REF" '
. as $root | [.bundles[] | select(.onnx_sha256 == $hash and (.tinygrad_ref == $ref or (.tinygrad_ref == null and $root.tinygrad_ref == $ref)))] | .[0] // empty
' 2>/dev/null)
[ -n "$BUNDLE" ] && [ "$BUNDLE" != "null" ]
}
if check_defaults; then
echo "HF defaults match repo tinygrad ref"
exit 0
fi
echo "No matching model on HF — dispatching build"
gh workflow run build-default-models.yaml --ref "$REF" -f target=big
sleep 10
BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
echo "Dispatched build run: $BUILD_RUN_ID"
echo "Waiting for build run to complete..."
for i in $(seq 1 90); do
sleep 30
STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
echo "Poll $i/90: status=$STATUS conclusion=$CONCLUSION"
if [ "$STATUS" = "completed" ]; then
if [ "$CONCLUSION" = "success" ]; then
echo "Build run succeeded, verifying HF..."
sleep 10
if check_defaults; then
echo "Big model verified on HF"
exit 0
fi
echo "::error::Build succeeded but model not found on HF"
exit 1
else
echo "::error::Build run failed with conclusion=$CONCLUSION"
exit 1
fi
fi
done
echo "::error::Build run did not complete within 45 minutes"
exit 1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Cancel run on failure
if: failure()
run: gh run cancel ${{ github.run_id }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
prepare_small_model:
needs: [ prepare_strategy ]
runs-on: ubuntu-24.04
concurrency:
group: prepare-small-model
cancel-in-progress: false
outputs:
driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
env:
GH_REPO: ${{ github.repository }}
HF_REPO: sunnypilot/sunnypilot_models_v1
HF_DEFAULTS_PATH: models/defaults/small
steps:
- name: Resolve tinygrad ref via API
id: resolve
run: |
REF="${{ github.head_ref || github.ref_name }}"
BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.sha')
DRIVING_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
echo "Driving ONNX hash: $DRIVING_HASH"
[ -n "$DRIVING_HASH" ] || { echo "::error::Failed to extract driving ONNX hash"; exit 1; }
echo "driving_onnx_sha256=$DRIVING_HASH" >> "$GITHUB_OUTPUT"
TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
echo "tinygrad ref: $TINYGRAD_REF"
echo "tinygrad_ref=$TINYGRAD_REF" >> "$GITHUB_OUTPUT"
JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
check_defaults() {
DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
DRIVING=$(echo "$DEFAULTS" | jq --arg hash "$DRIVING_HASH" --arg ref "$TINYGRAD_REF" '
. as $root | [.bundles[] | select(.onnx_sha256 == $hash and (.tinygrad_ref == $ref or (.tinygrad_ref == null and $root.tinygrad_ref == $ref)))] | .[0] // empty
' 2>/dev/null)
[ -n "$DRIVING" ] && [ "$DRIVING" != "null" ]
}
if check_defaults; then
echo "HF defaults match repo tinygrad ref"
exit 0
fi
echo "No matching model on HF — dispatching build"
gh workflow run build-default-models.yaml --ref "$REF" -f target=small
sleep 10
BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
echo "Dispatched build run: $BUILD_RUN_ID"
echo "Waiting for build run to complete..."
for i in $(seq 1 60); do
sleep 30
STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
if [ "$STATUS" = "completed" ]; then
if [ "$CONCLUSION" = "success" ]; then
echo "Build run succeeded, verifying HF..."
sleep 10
if check_defaults; then
echo "Small model verified on HF"
exit 0
fi
echo "::error::Build succeeded but model not found on HF"
exit 1
else
echo "::error::Build run failed with conclusion=$CONCLUSION"
exit 1
fi
fi
done
echo "::error::Small model build did not complete within 30 minutes"
exit 1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Cancel run on failure
if: failure()
run: gh run cancel ${{ github.run_id }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
prepare_dm_model:
needs: [ prepare_strategy ]
runs-on: ubuntu-24.04
concurrency:
group: prepare-dm-model
cancel-in-progress: false
outputs:
dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
env:
GH_REPO: ${{ github.repository }}
HF_REPO: sunnypilot/sunnypilot_models_v1
HF_DEFAULTS_PATH: models/defaults/dm
steps:
- name: Resolve tinygrad ref via API
id: resolve
run: |
REF="${{ github.head_ref || github.ref_name }}"
BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.sha')
DM_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
echo "DM ONNX hash: $DM_HASH"
[ -n "$DM_HASH" ] || { echo "::error::Failed to extract DM ONNX hash"; exit 1; }
echo "dm_onnx_sha256=$DM_HASH" >> "$GITHUB_OUTPUT"
TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
echo "tinygrad ref: $TINYGRAD_REF"
echo "tinygrad_ref=$TINYGRAD_REF" >> "$GITHUB_OUTPUT"
JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
check_defaults() {
DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
DM=$(echo "$DEFAULTS" | jq --arg hash "$DM_HASH" --arg ref "$TINYGRAD_REF" '
. as $root | [.bundles[] | select(.onnx_sha256 == $hash and (.tinygrad_ref == $ref or (.tinygrad_ref == null and $root.tinygrad_ref == $ref)))] | .[0] // empty
' 2>/dev/null)
[ -n "$DM" ] && [ "$DM" != "null" ]
}
if check_defaults; then
echo "HF defaults match DM tinygrad ref"
exit 0
fi
echo "No matching DM model on HF — dispatching build"
gh workflow run build-default-models.yaml --ref "$REF" -f target=dm
sleep 10
BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
echo "Dispatched build run: $BUILD_RUN_ID"
echo "Waiting for build run to complete..."
for i in $(seq 1 60); do
sleep 30
STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
if [ "$STATUS" = "completed" ]; then
if [ "$CONCLUSION" = "success" ]; then
echo "Build run succeeded, verifying HF..."
sleep 10
if check_defaults; then
echo "DM model verified on HF"
exit 0
fi
echo "::error::Build succeeded but DM model not found on HF"
exit 1
else
echo "::error::Build run failed with conclusion=$CONCLUSION"
exit 1
fi
fi
done
echo "::error::DM model build did not complete within 30 minutes"
exit 1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Cancel run on failure
if: failure()
run: gh run cancel ${{ github.run_id }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
publish:
concurrency:
# We do a bit of a hack here to avoid canceling the publishing job if a new commit comes in while we're publishing by adding the sha to the group name.
# This means that if multiple commits come in while we're publishing, they will be queued up and publish one after the other.
# Otherwise, if a job is waiting to be published due to environment wait time, it would be canceled by a new commit and restart the wait time.
group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}
cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
if: ${{
always() && !cancelled() &&
needs.build.result == 'success' &&
needs.prepare_strategy.result == 'success' &&
needs.prepare_small_model.result == 'success' &&
needs.prepare_dm_model.result == 'success' &&
(!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) &&
(needs.prepare_strategy.outputs.include_big_model != 'true' || needs.prepare_chestnut.result == 'success')
}}
needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
if: ${{ (always() && !cancelled() && !failure()) && needs.build.result == 'success' && needs.prepare_strategy.result == 'success' && (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) }}
needs: [ build, prepare_strategy ]
runs-on: ubuntu-24.04
environment: ${{ needs.prepare_strategy.outputs.environment }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Download prebuilt artifact
- name: Download build artifacts
uses: actions/download-artifact@v4
with:
name: prebuilt
@@ -503,18 +228,6 @@ jobs:
mkdir -p ${{ env.OUTPUT_DIR }}
tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
- name: Download models from HF
uses: ./.github/workflows/download-hf-model
with:
hf_repo: sunnypilot/sunnypilot_models_v1
dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
tinygrad_ref: ${{ needs.prepare_dm_model.outputs.tinygrad_ref }}
models: |
[
{"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
{"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"}
]
- name: Configure Git
run: |
git config --global user.email "github-actions[bot]@users.noreply.github.com"
@@ -542,78 +255,11 @@ jobs:
git tag -f -a ${TAG} -m "${{ needs.prepare_strategy.outputs.environment }} @ ${{ needs.prepare_strategy.outputs.version }} of build ${{ needs.prepare_strategy.outputs.build }}."
git push -f origin ${TAG}
publish_chestnut:
concurrency:
group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}-chestnut
cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
if: ${{
always() && !cancelled() &&
needs.build.result == 'success' &&
needs.prepare_strategy.result == 'success' &&
needs.prepare_small_model.result == 'success' &&
needs.prepare_dm_model.result == 'success' &&
needs.prepare_chestnut.result == 'success' &&
(!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt'))
}}
needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
runs-on: ubuntu-24.04
environment: ${{ needs.prepare_strategy.outputs.environment }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Download prebuilt artifact
uses: actions/download-artifact@v4
with:
name: prebuilt
- name: Untar prebuilt
run: |
mkdir -p ${{ env.OUTPUT_DIR }}
tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
- name: Download models from HF
uses: ./.github/workflows/download-hf-model
with:
hf_repo: sunnypilot/sunnypilot_models_v1
dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
tinygrad_ref: ${{ needs.prepare_dm_model.outputs.tinygrad_ref }}
models: |
[
{"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
{"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"},
{"hf_path": "models/defaults/big", "onnx_hash": "${{ needs.prepare_chestnut.outputs.onnx_sha256 }}", "canonical": "big_driving_tinygrad.pkl"}
]
- name: Configure Git
run: |
git config --global user.email "github-actions[bot]@users.noreply.github.com"
git config --global user.name "github-actions[bot]"
- name: Publish chestnut branch
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
${{ env.CI_DIR }}/publish.sh \
"${{ github.workspace }}" \
"${{ env.OUTPUT_DIR }}" \
"$CHESTNUT_BRANCH" \
"${{ needs.prepare_strategy.outputs.version }}" \
"https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
"${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
notify:
needs:
- prepare_strategy
- build
- publish
- publish_chestnut
- prepare_chestnut
- prepare_small_model
- prepare_dm_model
runs-on: ubuntu-24.04
if: ${{ (always() && !cancelled() && !failure())
&& needs.publish.result == 'success'
@@ -621,8 +267,6 @@ jobs:
&& (fromJSON(vars.DEV_FEEDBACK_NOTIFICATION_BRANCHES_V2)[github.head_ref || github.ref_name] != null) }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Prepare notification message
id: message
@@ -635,7 +279,6 @@ jobs:
export commit_short_sha="${commit_short_sha:0:7}"
export extra_version_identifier="${{ needs.prepare_strategy.outputs.extra_version_identifier || github.run_number }}"
export PUBLIC_REPO_URL="${{ env.PUBLIC_REPO_URL }}"
export chestnut_branch="${{ needs.prepare_chestnut.result == 'success' && format('{0}-chestnut', needs.prepare_strategy.outputs.new_branch) || '' }}"
MESSAGE=$(cat << 'EOF' | envsubst
${{ vars.DISCOURSE_GENERAL_UPDATE_NOTICE }}
+78
View File
@@ -0,0 +1,78 @@
name: Debug Discourse Posting
on:
push:
jobs:
test-discourse-post:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Post test message to Discourse
uses: ./.github/workflows/post-to-discourse
with:
discourse-url: ${{ vars.DISCOURSE_URL }}
api-key: ${{ secrets.DISCOURSE_API_KEY }}
api-username: ${{ secrets.DISCOURSE_API_USERNAME }}
topic-id: ${{ vars.DISCOURSE_UPDATES_TOPIC_ID }}
message: |
## 🧪 Test Post from GitHub Actions
**This is a test post to verify Discourse integration**
- **Workflow**: ${{ github.workflow }}
- **Run Number**: #${{ github.run_number }}
- **Branch**: `${{ github.ref_name }}`
- **Commit**: ${{ github.sha }}
- **Actor**: @${{ github.actor }}
- **Timestamp**: ${{ github.event.head_commit.timestamp }}
---
### Fake Build Info (for testing)
- **Version**: 0.9.8-test
- **Build**: #42
- **Branch**: release-test
[View workflow run](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }})
*This is an automated test message. Drive safe! 🚗💨*
- name: Create topic on Discourse
uses: ./.github/workflows/post-to-discourse
with:
discourse-url: ${{ vars.DISCOURSE_URL }}
api-key: ${{ secrets.DISCOURSE_API_KEY }}
api-username: ${{ secrets.DISCOURSE_API_USERNAME }}
#topic-id: ${{ vars.DISCOURSE_UPDATES_TOPIC_ID }}
category-id: 4
title: "This is a test of a new topic instead of a reply"
message: |
## 🧪 Test Post from GitHub Actions
**This is a test post to verify Discourse integration**
- **Workflow**: ${{ github.workflow }}
- **Run Number**: #${{ github.run_number }}
- **Branch**: `${{ github.ref_name }}`
- **Commit**: ${{ github.sha }}
- **Actor**: @${{ github.actor }}
- **Timestamp**: ${{ github.event.head_commit.timestamp }}
---
### Fake Build Info (for testing)
- **Version**: 0.9.8-test
- **Build**: #42
- **Branch**: release-test
[View workflow run](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }})
*This is an automated test message. Drive safe! 🚗💨*
- name: Display results
if: always()
run: |
echo "::notice::Discourse post test completed"
echo "Check your Discourse topic to verify the post appeared correctly"
-69
View File
@@ -1,69 +0,0 @@
name: Test Models Compatibility With Tinygrad Changes
on:
pull_request:
paths:
- 'tinygrad_repo'
workflow_dispatch:
jobs:
generate-matrix:
runs-on: ubuntu-latest
outputs:
models: ${{ steps.set-matrix.outputs.models }}
steps:
- uses: actions/checkout@v4
- name: Fetch and Parse json
id: set-matrix
run: |
python3 -c '
import json, urllib.request, os, re
with open("openpilot/sunnypilot/models/fetcher.py", "r") as f:
urls = re.findall(r"MODEL_URL(?:_CHESTNUT)?\s*=\s*[\"'"'"']([^\"'"'"']+)[\"'"'"']", f.read())
artifacts = []
for url in urls:
data = json.loads(urllib.request.urlopen(url).read())
for bundle in data.get("bundles", []):
for model in bundle.get("models", []):
if "artifact" in model:
artifacts.append(model["artifact"])
with open(os.environ["GITHUB_OUTPUT"], "a") as f:
f.write(f"models={json.dumps(artifacts)}\n")
'
test-model:
name: Test ${{ matrix.artifact.file_name }}
needs: generate-matrix
runs-on: ubuntu-latest
container: ghcr.io/commaai/openpilot-base:latest
strategy:
fail-fast: false
matrix:
artifact: ${{ fromJson(needs.generate-matrix.outputs.models) }}
steps:
- uses: actions/checkout@v4
with:
submodules: true
- name: Download model
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
MODEL_URL: ${{ matrix.artifact.download_uri.url }}
MODEL_FILE: ${{ matrix.artifact.file_name }}
shell: bash
run: |
mkdir -p /tmp/models
AUTH=()
if [ -n "$HF_TOKEN" ]; then AUTH=(-H "Authorization: Bearer $HF_TOKEN"); fi
curl --retry 3 --retry-all-errors -s -S -f -L "${AUTH[@]}" -o "/tmp/models/$MODEL_FILE" "$MODEL_URL"
- name: Run Model Compatibility Test
env:
MODEL_BASE_NAME: ${{ matrix.artifact.file_name }}
MODEL_DIR: "/tmp/models"
run: |
export PYTHONPATH="$GITHUB_WORKSPACE/tinygrad_repo:$GITHUB_WORKSPACE:$PYTHONPATH"
python3 -m pip uninstall -y tinygrad || uv pip uninstall -y tinygrad --system || true
python3 -m pytest openpilot/sunnypilot/modeld_v2/tests/test_models.py
+1 -1
View File
@@ -22,7 +22,7 @@ env:
PYTHONPATH: ${{ github.workspace }}
GIT_CONFIG_COUNT: 1
GIT_CONFIG_KEY_0: lfs.fetchexclude
GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
GIT_CONFIG_VALUE_0: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
jobs:
build_release:
-2
View File
@@ -50,8 +50,6 @@ st[0-9A-Za-z][0-9A-Za-z][0-9A-Za-z][0-9A-Za-z][0-9A-Za-z][0-9A-Za-z]
*.stats
*.pkl
*.pkl*
!openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
!openpilot/sunnypilot/modeld_v2/models/*.pkl
config.json
compile_commands.json
compare_runtime*.html
-1
View File
@@ -19,4 +19,3 @@
[submodule "sunnypilot/neural_network_data"]
path = openpilot/sunnypilot/neural_network_data
url = https://github.com/sunnypilot/neural-network-data.git
+2 -3
View File
@@ -1,5 +1,4 @@
[lfs]
url = https://huggingface.co/sunnypilot/sunnypilot-lfs.git/info/lfs
pushurl = https://huggingface.co/sunnypilot/sunnypilot-lfs.git/info/lfs
url = https://gitlab.com/sunnypilot/public/sunnypilot-new-lfs.git/info/lfs
pushurl = ssh://git@gitlab.com/sunnypilot/public/sunnypilot-new-lfs.git
locksverify = false
Vendored
+4 -62
View File
@@ -12,17 +12,16 @@ def retryWithDelay(int maxRetries, int delay, Closure body) {
def device(String ip, String step_label, String cmd) {
withCredentials([file(credentialsId: 'id_rsa', variable: 'key_file')]) {
def ssh_cmd = """
ssh -o ControlMaster=no -o ControlPath=none -o ConnectTimeout=5 -o ServerAliveInterval=5 -o ServerAliveCountMax=12 -o BatchMode=yes -o StrictHostKeyChecking=no -i ${key_file} 'comma@${ip}' exec setpriv --pdeathsig HUP /usr/bin/bash <<'END'
ssh -o ControlMaster=auto -o ControlPath=/tmp/ssh_control_%C -o ControlPersist=yes -o ConnectTimeout=5 -o ServerAliveInterval=5 -o ServerAliveCountMax=2 -o BatchMode=yes -o StrictHostKeyChecking=no -i ${key_file} 'comma@${ip}' exec /usr/bin/bash <<'END'
set -e
export TERM=xterm-256color
trap 'kill 0' HUP # stop this process group on SSH disconnect
shopt -s huponexit # kill all child processes when the shell exits
export CI=1
export PYTHONWARNINGS=error
export PYTHONFAULTHANDLER=1
export COMMA_CACHE=/data/tmp/comma_download_cache
#export LOGPRINT=debug # this has gotten too spammy...
export TEST_DIR=${env.TEST_DIR}
@@ -70,8 +69,7 @@ export LD_LIBRARY_PATH="\$(python -c 'import ffmpeg; print(ffmpeg.LIB_DIR)'):/us
ln -snf ${env.TEST_DIR} /data/pythonpath
cd ${env.TEST_DIR} || true
time ( ${cmd} ) &
wait \$!
time ${cmd}
END"""
sh script: ssh_cmd, label: step_label
@@ -161,14 +159,6 @@ def step(String name, String cmd, Map args = [:]) {
return [name, cmd, args]
}
def chestnutStage(String name = "chestnut") {
deviceStage(name, "mici-chestnut-ci", ["UNSAFE=1", "CHESTNUT=1"], [
step("build", "./openpilot/selfdrive/test/chestnut.sh"),
step("model replay", "openpilot/selfdrive/test/process_replay/model_replay.py --chestnut"),
step("onroad tests", "./openpilot/selfdrive/test/test_onroad.py TestChestnutOnroad", [timeout: 120]),
])
}
node {
env.CI = "1"
env.PYTHONWARNINGS = "error"
@@ -179,37 +169,7 @@ node {
env.GIT_BRANCH = checkout(scm).GIT_BRANCH
env.GIT_COMMIT = checkout(scm).GIT_COMMIT
if (env.JOB_BASE_NAME == 'chestnut-stresstest') {
sh 'git fetch --no-tags origin nightly-chestnut'
env.GIT_COMMIT = sh(script: 'git show FETCH_HEAD:git_src_commit', returnStdout: true).trim()
if (!(env.GIT_COMMIT ==~ /[0-9a-f]{40}/)) {
error("invalid nightly-chestnut source commit")
}
def results = []
try {
timeout(time: 12, unit: 'HOURS') {
for (int run = 1; run <= 100; run++) {
results << "run ${run}: INCOMPLETE"
try {
chestnutStage("chestnut ${run}/100")
results[run - 1] = "run ${run}: PASS"
} catch (hudson.AbortException e) {
results[run - 1] = "run ${run}: FAIL"
echo e.toString()
}
}
}
} finally {
writeFile file: 'chestnut_stress_report.txt', text: "commit: ${env.GIT_COMMIT}\ncompleted: ${results.count { !it.endsWith('INCOMPLETE') }}/100\n" + results.join('\n') + '\n'
archiveArtifacts artifacts: 'chestnut_stress_report.txt'
}
if (results.any { !it.endsWith('PASS') }) {
error("chestnut stress test failed")
}
return
}
def excludeBranches = ['__nightly', '__nightly-chestnut', 'devel', 'devel-staging',
def excludeBranches = ['__nightly', 'devel', 'devel-staging',
'release-tizi', 'release-tizi-staging', 'release-mici', 'release-mici-staging', 'testing-closet*', 'hotfix-*']
def excludeRegex = excludeBranches.join('|').replaceAll('\\*', '.*')
@@ -241,21 +201,6 @@ node {
)
}
if (env.BRANCH_NAME == '__nightly-chestnut') {
parallel (
'nightly-chestnut': {
deviceStage("build nightly-chestnut", "mici-chestnut-ci", ["CHESTNUT=1"], [
step("build nightly-chestnut", "SCONSFLAGS=-j4 INCLUDE_BIG_MODEL=1 RELEASE_BRANCH=nightly-chestnut $SOURCE_DIR/tools/release/build_release.sh TestChestnutOnroad"),
])
},
'nightly-chestnut-dev': {
deviceStage("build nightly-chestnut-dev", "mici-chestnut-ci", ["CHESTNUT=1"], [
step("build nightly-chestnut-dev", "SCONSFLAGS=-j4 INCLUDE_BIG_MODEL=1 PANDA_DEBUG_BUILD=1 RELEASE_BRANCH=nightly-chestnut-dev $SOURCE_DIR/tools/release/build_release.sh TestChestnutOnroad"),
])
},
)
}
if (!env.BRANCH_NAME.matches(excludeRegex)) {
parallel (
'onroad tests': {
@@ -307,9 +252,6 @@ node {
step("test amp", "./openpilot/common/hardware/comma/tests/test_amplifier.py"),
])
},
'chestnut': {
chestnutStage()
},
)
}
+1 -11
View File
@@ -1,14 +1,4 @@
Version 0.11.3 (2026-XX-XX)
========================
* Autospeed
* On supported cars, openpilot will intelligently decide what speed to drive based on the scene, including:
* stopping at red lights, and going at green lights
* slowing down for curves
* adjusting speed based on surrounding traffic
* This behavior was previously available with openpilot's "Experimental mode", but is now out of beta and always enabled
* With openpilot deciding which speed to drive, the car's cruise speed is treated as a maximum speed openpilot will not exceed
Version 0.11.2 (2026-10-14)
Version 0.11.2 (2026-08-12)
=======================
* New driving model
* Big model with 880M parameters
+13 -2
View File
@@ -20,7 +20,7 @@ SetOption('num_jobs', max(1, int(os.cpu_count()/(1 if "CI" in os.environ else 2)
AddOption('--ccflags', action='store', type='string', default='', help='pass arbitrary flags over the command line')
AddOption('--verbose', action='store_true', default=False, help='show full build commands')
release = not os.path.exists(File('#.gitmodules').abspath) # file absent on release branch, see release_files.py
release = not os.path.exists(File('#.gitattributes').abspath) # file absent on release branch, see release_files.py
AddOption('--minimal',
action='store_false',
dest='extras',
@@ -87,6 +87,7 @@ acados_include_dirs = [
# vendored in commaai/dependencies.
allowed_system_libs = {
"EGL", "GLESv2", "GL",
"Qt5Charts", "Qt5Core", "Qt5Gui", "Qt5Widgets",
"dl", "drm", "gbm", "m", "pthread",
}
@@ -120,7 +121,6 @@ def _libflags(target, source, env, for_signature):
env = Environment(
ENV={
"PATH": os.environ['PATH'],
"TMPDIR": os.environ.get('TMPDIR', '/tmp'),
"PYTHONPATH": os.pathsep.join(submodule_python_paths),
"ACADOS_SOURCE_DIR": acados.DIR,
"ACADOS_PYTHON_INTERFACE_PATH": acados.TEMPLATE_DIR,
@@ -316,6 +316,8 @@ def count_scons_nodes(nodes):
if node in seen:
continue
seen.add(node)
if hasattr(node, 'has_builder') and node.has_builder():
build_product_nodes.add(node)
executor = node.get_executor()
if executor is not None:
stack += executor.get_all_prerequisites() + executor.get_all_children()
@@ -324,6 +326,7 @@ def count_scons_nodes(nodes):
progress_interval = 5
progress_count = 0
build_product_nodes = set()
progress_total = max(1, count_scons_nodes(env.arg2nodes(BUILD_TARGETS or [Dir('.')], env.fs.Entry)))
def progress_function(node):
@@ -339,3 +342,11 @@ def progress_function(node):
Progress(progress_function, interval=progress_interval)
AddPostAction(BUILD_TARGETS or [Dir('.')], prune_cache_dir)
def check_build_product_size(target, source, env):
limit = 50 * 1024 * 1024 # GitHub max size
for t in target:
if hasattr(t, 'isfile') and t.isfile() and (size := os.path.getsize(t.abspath)) > limit:
raise SCons.Errors.UserError(f"{t} is {size / (1024 * 1024):.1f} MiB, exceeding the {limit / (1024 * 1024):.1f} MiB limit")
if not GetOption('extras'):
AddPostAction(list(build_product_nodes), Action(check_build_product_size, None))
+7 -7
View File
@@ -34,7 +34,7 @@ A supported vehicle is one that just works when you install a comma device. All
|Chrysler|Pacifica Hybrid 2019-25|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Chrysler Pacifica Hybrid 2019-25">Buy Here</a></sub></details>|||
|comma|body|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|None|<a href="https://youtu.be/VT-i3yRsX2s?t=2736" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
|CUPRA[<sup>12</sup>](#footnotes)|Ateca 2018-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=CUPRA Ateca 2018-23">Buy Here</a></sub></details>|||
|CUPRA|Born 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=CUPRA Born 2021-23">Buy Here</a></sub></details>|||
|CUPRA[<sup>12</sup>](#footnotes)|Born 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=CUPRA Born 2021-23">Buy Here</a></sub></details>|||
|Dodge|Durango 2020-21|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Dodge Durango 2020-21">Buy Here</a></sub></details>|||
|Ford|Bronco Sport 2021-24|Co-Pilot360 Assist+|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Ford Q3 connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Ford Bronco Sport 2021-24">Buy Here</a></sub></details>|||
|Ford|Escape 2020-22|Co-Pilot360 Assist+|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Ford Q3 connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Ford Escape 2020-22">Buy Here</a></sub></details>|||
@@ -99,7 +99,7 @@ A supported vehicle is one that just works when you install a comma device. All
|Honda|Fit 2018-20|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Fit 2018-20">Buy Here</a></sub></details>|||
|Honda|Freed 2020|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Freed 2020">Buy Here</a></sub></details>|||
|Honda|HR-V 2019-22|Honda Sensing|openpilot|26 mph|12 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Nidec connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2019-22">Buy Here</a></sub></details>|||
|Honda|HR-V 2023-27|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2023-27">Buy Here</a></sub></details>|||
|Honda|HR-V 2023-25|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch B connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda HR-V 2023-25">Buy Here</a></sub></details>|||
|Honda|Insight 2019-22|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|3 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Insight 2019-22">Buy Here</a></sub></details>|||
|Honda|Inspire 2018|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|3 mph|[![star](assets/icon-star-empty.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda Inspire 2018">Buy Here</a></sub></details>|||
|Honda|N-Box 2018|All|openpilot available[<sup>1,5</sup>](#footnotes)|0 mph|11 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 Honda Bosch A connector<br>- 1 OBD-C cable (2 ft)<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Honda N-Box 2018">Buy Here</a></sub></details>|||
@@ -268,8 +268,8 @@ A supported vehicle is one that just works when you install a comma device. All
|Škoda[<sup>12</sup>](#footnotes)|Superb 2015-22[<sup>15</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Škoda Superb 2015-22">Buy Here</a></sub></details>|||
|Tesla[<sup>10</sup>](#footnotes)|Model 3 (with HW3) 2019-23[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model 3 (with HW3) 2019-23">Buy Here</a></sub></details>|||
|Tesla[<sup>10</sup>](#footnotes)|Model 3 (with HW4) 2024-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model 3 (with HW4) 2024-25">Buy Here</a></sub></details>|||
|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW3) 2020-24[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW3) 2020-24">Buy Here</a></sub></details>|||
|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW4) 2023-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW4) 2023-25">Buy Here</a></sub></details>|||
|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW3) 2020-23[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla A connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW3) 2020-23">Buy Here</a></sub></details>|||
|Tesla[<sup>10</sup>](#footnotes)|Model Y (with HW4) 2024-25[<sup>9</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Tesla B connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Tesla Model Y (with HW4) 2024-25">Buy Here</a></sub></details>|||
|Toyota|Alphard 2019-20|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Alphard 2019-20">Buy Here</a></sub></details>|||
|Toyota|Alphard Hybrid 2021|All|openpilot|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Alphard Hybrid 2021">Buy Here</a></sub></details>|||
|Toyota|Avalon 2016|Toyota Safety Sense P|Stock|19 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-empty.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 Toyota A connector<br>- 1 comma four<br>- 1 comma power v3<br>- 1 harness box<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Toyota Avalon 2016">Buy Here</a></sub></details>|||
@@ -335,8 +335,8 @@ A supported vehicle is one that just works when you install a comma device. All
|Volkswagen[<sup>12</sup>](#footnotes)|Golf R 2015-19|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Golf R 2015-19">Buy Here</a></sub></details>|||
|Volkswagen[<sup>12</sup>](#footnotes)|Golf SportsVan 2015-20|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Golf SportsVan 2015-20">Buy Here</a></sub></details>|||
|Volkswagen[<sup>12</sup>](#footnotes)|Grand California 2019-24|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|31 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Grand California 2019-24">Buy Here</a></sub></details>|<a href="https://youtu.be/4100gLeabmo" target="_blank"><img height="18px" src="assets/icon-youtube.svg" /></a>||
|Volkswagen|ID.4 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2021-23">Buy Here</a></sub></details>|||
|Volkswagen|ID.4 2024-25|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW MEB connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2024-25">Buy Here</a></sub></details>|||
|Volkswagen[<sup>12</sup>](#footnotes)|ID.4 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2021-23">Buy Here</a></sub></details>|||
|Volkswagen[<sup>12</sup>](#footnotes)|ID.4 2024-25|Adaptive Cruise Control (ACC) & Lane Assist|openpilot[<sup>16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen ID.4 2024-25">Buy Here</a></sub></details>|||
|Volkswagen[<sup>12</sup>](#footnotes)|Jetta 2019-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Jetta 2019-23">Buy Here</a></sub></details>|||
|Volkswagen[<sup>12</sup>](#footnotes)|Jetta GLI 2021-23|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Jetta GLI 2021-23">Buy Here</a></sub></details>|||
|Volkswagen|Passat 2015-22[<sup>14</sup>](#footnotes)|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,16</sup>](#footnotes)|0 mph|0 mph|[![star](assets/icon-star-full.svg)](##)|[![star](assets/icon-star-full.svg)](##)|<details><summary>Parts</summary><sub>- 1 OBD-C cable (2 ft)<br>- 1 VW J533 connector<br>- 1 comma four<br>- 1 harness box<br>- 1 long OBD-C cable (9.5 ft)<br>- 1 mount<br><a href="https://comma.ai/shop/comma-3x?harness=Volkswagen Passat 2015-22">Buy Here</a></sub></details>|||
@@ -363,7 +363,7 @@ A supported vehicle is one that just works when you install a comma device. All
<sup>6</sup>See more setup details for <a href="https://github.com/commaai/openpilot/wiki/nissan" target="_blank">Nissan</a>. <br />
<sup>7</sup>In the non-US market, openpilot requires the car to come equipped with EyeSight with Lane Keep Assistance. <br />
<sup>8</sup>Enabling longitudinal control (alpha) will disable all EyeSight functionality, including AEB, LDW, and RAB. <br />
<sup>9</sup>Model years 2023 and 2024 can have either hardware type, depending on build date and factory. To check which hardware type your vehicle has, look for <b>Autopilot computer</b> under <b>Software -> Additional Vehicle Information</b> on your vehicle's touchscreen. See <a href="https://www.notateslaapp.com/news/2173/how-to-check-if-your-tesla-has-hardware-4-ai4-or-hardware-3">this page</a> for more information. <br />
<sup>9</sup>Some 2023 model years have HW4. To check which hardware type your vehicle has, look for <b>Autopilot computer</b> under <b>Software -> Additional Vehicle Information</b> on your vehicle's touchscreen. See <a href="https://www.notateslaapp.com/news/2173/how-to-check-if-your-tesla-has-hardware-4-ai4-or-hardware-3">this page</a> for more information. <br />
<sup>10</sup>See more setup details for <a href="https://github.com/commaai/openpilot/wiki/tesla" target="_blank">Tesla</a>. <br />
<sup>11</sup>openpilot operates above 28mph for Camry 4CYL L, 4CYL LE and 4CYL SE which don't have Full-Speed Range Dynamic Radar Cruise Control. <br />
<sup>12</sup>The J533 harness plugs in at the CAN gateway under the dashboard, just above the steering column. More information can be found at <a href="https://docs.howtocomma.com/docs/j533-harness-install" target="_blank">this guide</a>. <br />
+2 -2
View File
@@ -5,10 +5,10 @@ The site is updated on pushes to master by this [workflow](../.github/workflows/
**1. Build the site**
``` bash
op docs --build
python docs/serve.py --build
```
**2. Run the site locally** (rebuilds on change)
``` bash
op docs
python docs/serve.py
```
+10 -14
View File
@@ -18,21 +18,19 @@ function agnos_init {
sudo chmod 660 /dev/adsprpc-smd /dev/ion /dev/kgsl-3d0
# Check if AGNOS update is required
if [ "$(< /VERSION)" != "$AGNOS_VERSION" ]; then
if [ $(< /VERSION) != "$AGNOS_VERSION" ]; then
AGNOS_PY="$DIR/openpilot/common/hardware/comma/agnos.py"
MANIFEST="$DIR/openpilot/system/hardware/comma/agnos.json"
if "$AGNOS_PY" --verify "$MANIFEST"; then
if $AGNOS_PY --verify $MANIFEST; then
sudo reboot
fi
while true; do
"$DIR/openpilot/common/hardware/comma/updater" "$AGNOS_PY" "$MANIFEST"
done
$DIR/openpilot/common/hardware/comma/updater $AGNOS_PY $MANIFEST
fi
}
function launch {
# Remove orphaned git lock if it exists on boot
[ -f "$DIR/.git/index.lock" ] && rm -f "$DIR/.git/index.lock"
[ -f "$DIR/.git/index.lock" ] && rm -f $DIR/.git/index.lock
# Check to see if there's a valid overlay-based update available. Conditions
# are as follows:
@@ -44,7 +42,7 @@ function launch {
# that completed successfully and synced to disk.
if [ -f "${DIR}/.overlay_init" ]; then
find "${DIR}/.git" -newer "${DIR}/.overlay_init" | grep -q '.' 2> /dev/null
find ${DIR}/.git -newer ${DIR}/.overlay_init | grep -q '.' 2> /dev/null
if [ $? -eq 0 ]; then
echo "${DIR} has been modified, skipping overlay update installation"
else
@@ -53,11 +51,9 @@ function launch {
echo "Valid overlay update found, installing"
LAUNCHER_LOCATION="${BASH_SOURCE[0]}"
mv "$DIR" /data/safe_staging/old_openpilot
mv "${STAGING_ROOT}/finalized" "$DIR"
cd "$DIR"
# releases before the openpilot/ move can't swap AGNOS on newer AGNOS, use ours
[ ! -L system/hardware/tici/agnos.json ] && /data/safe_staging/old_openpilot/openpilot/common/hardware/comma/agnos.py --verify system/hardware/tici/agnos.json && sudo reboot
mv $DIR /data/safe_staging/old_openpilot
mv "${STAGING_ROOT}/finalized" $DIR
cd $DIR
echo "Restarting launch script ${LAUNCHER_LOCATION}"
unset AGNOS_VERSION
@@ -71,7 +67,7 @@ function launch {
fi
# handle pythonpath
ln -sfn "$(pwd)" /data/pythonpath
ln -sfn $(pwd) /data/pythonpath
export PYTHONPATH="$PWD"
# submodule package symlinks for PYTHONPATH imports on device.
@@ -92,7 +88,7 @@ function launch {
# start manager
cd openpilot/system/manager
if [ ! -f "$DIR/prebuilt" ]; then
if [ ! -f $DIR/prebuilt ]; then
./build.py
fi
./manager.py
+1 -1
View File
@@ -16,7 +16,7 @@ export VECLIB_MAXIMUM_THREADS=1
export QCOM_PRIORITY=12
if [ -z "$AGNOS_VERSION" ]; then
export AGNOS_VERSION="19.9"
export AGNOS_VERSION="19.6"
fi
export STAGING_ROOT="/data/safe_staging"
+3 -8
View File
@@ -131,7 +131,6 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
downloaded @2;
cached @3;
failed @4;
verifying @5;
}
struct DownloadProgress {
@@ -196,6 +195,7 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
}
struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
dec @0 :DynamicExperimentalControl;
longitudinalPlanSource @1 :LongitudinalPlanSource;
smartCruiseControl @2 :SmartCruiseControl;
speedLimit @3 :SpeedLimit;
@@ -204,11 +204,7 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
events @6 :List(OnroadEventSP.Event);
e2eAlerts @7 :E2eAlerts;
deprecated :group {
dec @0 :DynamicExperimentalControlDEPRECATED;
}
struct DynamicExperimentalControlDEPRECATED {
struct DynamicExperimentalControl {
state @0 :DynamicExperimentalControlState;
enabled @1 :Bool;
active @2 :Bool;
@@ -345,7 +341,7 @@ struct OnroadEventSP @0xda96579883444c35 {
silentParkBrake @11;
controlsMismatchLateral @12;
hyundaiRadarTracksConfirmed @13;
experimentalModeSwitchedDEPRECATED @14;
experimentalModeSwitched @14;
wrongCarModeAlertOnly @15;
pedalPressedAlertOnly @16;
laneTurnLeft @17;
@@ -356,7 +352,6 @@ struct OnroadEventSP @0xda96579883444c35 {
speedLimitPending @22;
e2eChime @23;
laneChangeRoadEdge @24;
bigModelReady @25;
}
}
+16 -24
View File
@@ -128,7 +128,6 @@ struct OnroadEvent @0xc4fa6047f024e718 {
personalityChanged @91;
aeb @92;
userBookmark @95;
userBookmarkNotPaired @104;
excessiveActuation @96;
bigModelLoading @100;
bigModelFailed @102;
@@ -167,7 +166,12 @@ struct InitData {
gitSrcCommit @23 :Text;
gitSrcCommitDate @24 :Text;
androidProperties @16 :Map(Text, Text);
pandaInfo @8 :PandaInfo;
dirty @9 :Bool;
passive @12 :Bool;
params @17 :Map(Text, Data);
commands @19 :Map(Text, Data);
@@ -185,17 +189,6 @@ struct InitData {
mici @7; # comma four
}
deprecated :group {
gctx @1 :Text;
androidBuildInfo @5 :Deprecated.AndroidBuildInfo;
androidSensors @6 :List(Deprecated.AndroidSensor);
chffrAndroidExtra @7 :ChffrAndroidExtra;
pandaInfo @8 :PandaInfo;
passive @12 :Bool;
iosBuildInfo @14 :Deprecated.IosBuildInfo;
androidProperties @16 :Map(Text, Text);
}
struct PandaInfo {
hasPanda @0 :Bool;
dongleId @1 :Text;
@@ -206,6 +199,14 @@ struct InitData {
struct ChffrAndroidExtra {
allCameraCharacteristics @0 :Map(Text, Text);
}
deprecated :group {
gctx @1 :Text;
androidBuildInfo @5 :Deprecated.AndroidBuildInfo;
androidSensors @6 :List(Deprecated.AndroidSensor);
chffrAndroidExtra @7 :ChffrAndroidExtra;
iosBuildInfo @14 :Deprecated.IosBuildInfo;
}
}
struct FrameData {
@@ -571,9 +572,6 @@ struct PandaState @0xa7649e2575e4591e {
controlsAllowedLateral @38 :Bool;
controlsAllowedLongitudinal @39 :Bool;
nmiReset @40 :Bool;
hardfaultReset @41 :Bool;
enum FaultStatus {
none @0;
faultTemp @1;
@@ -696,7 +694,6 @@ struct PeripheralState {
struct UsbState {
devices @0 :List(Device);
connected @1 :Bool;
struct Device {
busnum @0 :UInt8;
@@ -728,7 +725,6 @@ struct ChestnutState {
pcieLtssm @7 :UInt8;
supplyVoltage @8 :UInt16; # mV
supplyCurrent @9 :Int16; # mA
supplyFault @10 :Bool;
}
struct RadarState @0x9a185389d6fdd05f {
@@ -822,6 +818,7 @@ struct SelfdriveState {
alertHudVisual @12 :Car.CarControl.HUDControl.VisualAlert;
# configurable driving settings
experimentalMode @10 :Bool;
personality @11 :LongitudinalPersonality;
enum AudibleAlert {
@@ -865,7 +862,6 @@ struct SelfdriveState {
deprecated :group {
alertSound @8 :Car.CarControl.HUDControl.AudibleAlert;
experimentalMode @10 :Bool;
}
}
@@ -1008,7 +1004,6 @@ struct DrivingModelData {
frameIdExtra @1 :UInt32;
frameDropPerc @6 :Float32;
modelExecutionTime @7 :Float32;
big @8 :Bool;
action @2 :ModelDataV2.Action;
@@ -1240,7 +1235,6 @@ struct LongitudinalPlan @0xe00b5b3eba12876c {
shouldStop @37: Bool;
allowThrottle @38: Bool;
allowBrake @39: Bool;
accelBoost @40 :Float32;
solverExecutionTime @35 :Float32;
@@ -2238,7 +2232,6 @@ struct DriverMonitoringState {
pose @0: Bool;
eye @1: Bool;
phone @2: Bool;
sleep @3: Bool;
}
struct Pose {
@@ -2599,7 +2592,6 @@ struct Event {
clocks @35 :Clocks;
deviceState @6 :DeviceState;
chestnutState @152 :ChestnutState;
chestnutGpuState @153 :ChestnutState;
logMessage @18 :Text;
errorLogMessage @85 :Text;
@@ -2710,8 +2702,8 @@ struct Event {
driverMonitoringStateDEPRECATED @71 :DriverMonitoringStateDEPRECATED;
gpsNMEADEPRECATED @3 :GPSNMEAData;
uploaderStateDEPRECATED @79 :UploaderState;
navInstruction @82 :NavInstruction;
navRoute @83 :NavRoute;
navInstructionDEPRECATED @82 :NavInstruction;
navRouteDEPRECATED @83 :NavRoute;
navThumbnailDEPRECATED @84 :Thumbnail;
gnssMeasurementsDEPRECATED @91 :GnssMeasurements;
mapRenderStateDEPRECATED @105: MapRenderState;
+1 -4
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@@ -25,8 +25,7 @@ _services: dict[str, tuple] = {
"accelerometer": (True, 104., 104),
"temperatureSensor": (True, 2., 200),
"deviceState": (True, 2., 1),
"chestnutState": (True, 10., 1),
"chestnutGpuState": (False, 10.),
"chestnutState": (True, 10., 10),
"touch": (True, 20., 1),
"can": (True, 100., 2053, QueueSize.BIG), # decimation gives ~3 msgs in a full segment
"controlsState": (True, 100., 10, QueueSize.MEDIUM),
@@ -52,8 +51,6 @@ _services: dict[str, tuple] = {
"procLog": (True, 0.5, 15, QueueSize.BIG),
"gpsLocationExternal": (True, 10., 10),
"gpsLocation": (True, 1., 1),
"navInstruction": (True, 1., 10),
"navRoute": (True, 0.),
"ubloxGnss": (True, 10.),
"qcomGnss": (True, 2.),
"clocks": (True, 0.1, 1),
+1 -1
View File
@@ -1,4 +1,4 @@
from openpilot.common.api.comma_connect import API_HOST as API_HOST, CommaConnectApi
from openpilot.common.api.comma_connect import CommaConnectApi
class Api:
-4
View File
@@ -16,10 +16,6 @@ class CV:
DEG_TO_RAD = np.pi / 180.
RAD_TO_DEG = 1. / DEG_TO_RAD
# Length
METER_TO_FOOT = 3.28084
METER_TO_MILE = 1. / 1609.344
# Mass
LB_TO_KG = 0.453592
+1 -10
View File
@@ -1,8 +1,6 @@
from abc import ABC, abstractmethod
from dataclasses import dataclass
WEBBING_ICCID_PREFIX = "8985235"
class LPAError(RuntimeError):
pass
@@ -21,14 +19,7 @@ class Profile:
@property
def is_comma(self) -> bool:
return self.provider == 'Webbing' and self.iccid.startswith(WEBBING_ICCID_PREFIX)
@property
def display_name(self) -> str:
if self.is_comma:
return "comma prime"
name = self.nickname or self.provider or "<unnamed>"
return f"{name} (...{self.iccid[-4:]})"
return self.provider == 'Webbing' and self.iccid.startswith('8985235')
class LPABase(ABC):
+1 -1
View File
@@ -613,7 +613,7 @@ def parse_lpa_activation_code(activation_code: str) -> tuple[str, str]:
if not activation_code.startswith("LPA:"):
raise ValueError("Invalid activation code format")
parts = activation_code[4:].split("$")
if len(parts) != 3 or not all(parts):
if len(parts) != 3:
raise ValueError("Invalid activation code format")
return parts[1], parts[2]
+82
View File
@@ -0,0 +1,82 @@
#!/usr/bin/env python3
import io
import sys
import math
import os
from pathlib import Path
CHUNK_SIZE = 45 * 1024 * 1024 # 45MB, under GitHub's 50MB limit
def get_chunk_name(name, idx, num_chunks):
return f"{name}.chunk{idx+1:02d}of{num_chunks:02d}"
def get_manifest_path(name):
return f"{name}.chunkmanifest"
def _chunk_paths(path, num_chunks):
return [get_manifest_path(path)] + [get_chunk_name(path, i, num_chunks) for i in range(num_chunks)]
def get_chunk_targets(path, file_size):
num_chunks = math.ceil(file_size / CHUNK_SIZE)
return _chunk_paths(path, num_chunks)
def chunk_file(path, targets):
manifest_path, *chunk_paths = targets
actual_num_chunks = max(1, math.ceil(os.path.getsize(path) / CHUNK_SIZE))
assert len(chunk_paths) >= actual_num_chunks, f"Allowed {len(chunk_paths)} chunks but needs at least {actual_num_chunks}, for path {path}"
with open(path, 'rb') as f:
for chunk_path in chunk_paths:
with open(chunk_path, 'wb') as out:
out.write(f.read(CHUNK_SIZE))
Path(manifest_path).write_text(str(len(chunk_paths)))
os.remove(path)
def get_existing_chunks(path):
if os.path.isfile(path):
return [path]
if os.path.isfile(manifest := get_manifest_path(path)):
num_chunks = int(Path(manifest).read_text().strip())
return _chunk_paths(path, num_chunks)
raise FileNotFoundError(path)
class ChunkStream(io.RawIOBase):
def __init__(self, paths):
self._paths = iter(paths)
self._f = None
def readable(self):
return True
def readinto(self, b):
n = 0
view = memoryview(b)
while n < len(b):
if self._f is None:
p = next(self._paths, None)
if p is None:
break
self._f = open(p, 'rb')
count = self._f.readinto(view[n:])
if not count:
self._f.close()
self._f = None
continue
n += count
return n
def open_file_chunked(path):
manifest_path = get_manifest_path(path)
if os.path.isfile(manifest_path):
num_chunks = int(Path(manifest_path).read_text().strip())
paths = [get_chunk_name(path, i, num_chunks) for i in range(num_chunks)]
elif os.path.isfile(path):
paths = [path]
else:
raise FileNotFoundError(path)
return io.BufferedReader(ChunkStream(paths))
if __name__ == "__main__":
path = sys.argv[1]
chunk_paths = get_chunk_targets(path, os.path.getsize(path))
chunk_file(path, chunk_paths)
+10
View File
@@ -27,6 +27,16 @@ def gpio_read(pin: int) -> bool | None:
return val
def gpio_export(pin: int) -> None:
if os.path.isdir(f"/sys/class/gpio/gpio{pin}"):
return
try:
with open("/sys/class/gpio/export", 'w') as f:
f.write(str(pin))
except Exception:
print(f"Failed to export gpio {pin}")
@cache
def get_irq_action(irq: int) -> list[str]:
try:
-3
View File
@@ -145,9 +145,6 @@ class HardwareBase(ABC):
def get_modem_temperatures(self):
return []
def get_modem_state(self) -> dict:
return {}
def initialize_hardware(self):
pass
+12 -12
View File
@@ -56,29 +56,29 @@
},
{
"name": "boot",
"url": "https://commadist.azureedge.net/agnosupdate/boot-b9c9b9261fca0cef9e6d9b198fa4b563767e6342afc7a61ab137b2b519260615.img.xz",
"hash": "b9c9b9261fca0cef9e6d9b198fa4b563767e6342afc7a61ab137b2b519260615",
"hash_raw": "b9c9b9261fca0cef9e6d9b198fa4b563767e6342afc7a61ab137b2b519260615",
"size": 46962688,
"url": "https://commadist.azureedge.net/agnosupdate/boot-b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd.img.xz",
"hash": "b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd",
"hash_raw": "b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd",
"size": 46897152,
"sparse": false,
"full_check": true,
"has_ab": true,
"ondevice_hash": "3ef4769bb1cc73bfc31f96f073b46af42dcc0bad4ab2dde32d11929745d0cd28"
"ondevice_hash": "6650e4c46df99ae6dfd6ee895a34b8a2a3cc490a8ce18e16cc3c451c3f822b6e"
},
{
"name": "system",
"url": "https://commadist.azureedge.net/agnosupdate/system-80d9373348ddff2a5d1f534fab3420383939c96f3eba60baab6b15339fc602c7.img.xz",
"hash": "9aebca09b9d142718e71efbfe44b723010eec6e70067c043c63186067291739d",
"hash_raw": "80d9373348ddff2a5d1f534fab3420383939c96f3eba60baab6b15339fc602c7",
"url": "https://commadist.azureedge.net/agnosupdate/system-5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3.img.xz",
"hash": "b134fd04e9da27fa1d359ea0f2742c216fa21a08b5c47e9be22ab3b0563d9b9b",
"hash_raw": "5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3",
"size": 4718592000,
"sparse": true,
"full_check": false,
"has_ab": true,
"ondevice_hash": "270b76c5c5568828e3883390b83ea445425a104dd42119d68f06093ce6b6fcef",
"ondevice_hash": "91242772af771ae96fe2eebc105f2b80a7e1dbaaf6003c2574b62d51b806f468",
"alt": {
"hash": "80d9373348ddff2a5d1f534fab3420383939c96f3eba60baab6b15339fc602c7",
"url": "https://commadist.azureedge.net/agnosupdate/system-80d9373348ddff2a5d1f534fab3420383939c96f3eba60baab6b15339fc602c7.img",
"hash": "5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3",
"url": "https://commadist.azureedge.net/agnosupdate/system-5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3.img",
"size": 4718592000
}
}
]
]
@@ -8,7 +8,6 @@ from functools import cached_property, lru_cache
from pathlib import Path
from openpilot.cereal import log
from openpilot.common.esim.base import WEBBING_ICCID_PREFIX
from openpilot.common.utils import sudo_read, sudo_write
from openpilot.common.gpio import gpio_set, gpio_init, get_irqs_for_action
from openpilot.common.esim.base import LPABase
@@ -208,8 +207,6 @@ class HardwareComma(HardwareBase):
def get_network_metered(self, network_type) -> bool:
if network_type in (NetworkType.cell2G, NetworkType.cell3G, NetworkType.cell4G, NetworkType.cell5G):
if self.get_modem_state().get("iccid", "").startswith(WEBBING_ICCID_PREFIX):
return True
from openpilot.common.params import Params
return Params().get_bool("GsmMetered")
try:
+2 -4
View File
@@ -5,7 +5,6 @@ import logging
import os
import select
import signal
import string
import struct
import subprocess
import tempfile
@@ -17,8 +16,6 @@ from ipaddress import IPv4Address, AddressValueError
from enum import Enum
from openpilot.common.esim.base import WEBBING_ICCID_PREFIX
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s.%(msecs)03d %(levelname)-7s modem: %(message)s",
@@ -46,6 +43,7 @@ NETWORK_TYPE = {0: "gsm", 1: "gsm", 3: "gsm", 8: "gsm",
11: "nr", 12: "nr", 13: "nr"}
DIAL_CID = 1
WEBBING_ICCID_PREFIX = "8985235"
PPPD_CMD = [
"sudo", "pppd", PPP_PORT, "460800", "noauth", "nodetach", "noipdefault", "usepeerdns",
@@ -356,7 +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")
+2 -2
View File
@@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f92c0a9b41613e063b6a1cd086729f5555d9df6482249e171ed1e276272cad7d
size 24709520
oid sha256:3a94ab8395f20d20a9d5a2a2bacca0694f072df8421cf13adca6250d28065bdc
size 24709205
+2 -13
View File
@@ -1,20 +1,14 @@
import os
from pathlib import Path
CHESTNUT_FW_VERSION = "8516b768"
CHESTNUT_FW_VERSION = "ed4e39b7"
CHESTNUT_USB_IDS = ((0xADD1, 0x0001), (0x3801, 0x0001))
CHESTNUT_ROM_USB_IDS = ((0x174C, 0x2464), (0x174C, 0x2463))
CHESTNUT_USB_PRODUCT = f"custom {CHESTNUT_FW_VERSION}-CLEAN"
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))
@@ -36,10 +30,6 @@ def read_int(path: Path, base: int = 10) -> int:
return 0
def cable_connected() -> bool:
return read_int(TYPEC_CC_ORIENTATION_PATH) != 0
def usb_devices() -> list[Path]:
try:
devices = (d for d in USB_DEVICES_PATH.glob("*") if (d / "idVendor").exists())
@@ -91,8 +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
device_state.usbState.connected = cable_connected()
+11 -27
View File
@@ -28,7 +28,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"ControlsReady", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
{"CurrentBootlog", {PERSISTENT, STRING}},
{"CurrentRoute", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
{"DisableDriverCameraIR", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
{"DisableLogging", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
{"DisablePowerDown", {PERSISTENT | BACKUP, BOOL}},
{"DisableUpdates", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -40,6 +39,8 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"DriverTooDistracted", {CLEAR_ON_MANAGER_START | CLEAR_ON_IGNITION_ON, BOOL}},
{"DriverLockoutCount", {CLEAR_ON_MANAGER_START | CLEAR_ON_IGNITION_ON, INT, "0"}},
{"AlphaLongitudinalEnabled", {PERSISTENT | DEVELOPMENT_ONLY | BACKUP, BOOL}},
{"ExperimentalMode", {PERSISTENT | BACKUP, BOOL}},
{"ExperimentalModeConfirmed", {PERSISTENT | BACKUP, BOOL}},
{"FirmwareQueryDone", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
{"ForcePowerDown", {PERSISTENT, BOOL}},
{"GitBranch", {PERSISTENT, STRING}},
@@ -58,7 +59,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"IsDriverViewEnabled", {CLEAR_ON_MANAGER_START, BOOL}},
{"IsEngaged", {PERSISTENT, BOOL}},
{"IsLdwEnabled", {PERSISTENT | BACKUP, BOOL}},
{"IsLiveStreaming", {CLEAR_ON_MANAGER_START | CLEAR_ON_IGNITION_ON, BOOL}},
{"IsLiveStreaming", {CLEAR_ON_MANAGER_START, BOOL}},
{"IsMetric", {PERSISTENT | BACKUP, BOOL}},
{"IsOffroad", {CLEAR_ON_MANAGER_START, BOOL}},
{"IsRhdDetected", {PERSISTENT, BOOL}},
@@ -67,7 +68,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"JoystickDebugMode", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, BOOL}},
{"LanguageSetting", {PERSISTENT | BACKUP, STRING, "en"}},
{"LastAthenaPingTime", {CLEAR_ON_MANAGER_START, INT}},
{"LastGPSPosition", {PERSISTENT, BYTES}},
{"LastGPSPosition", {PERSISTENT, STRING}},
{"LastManagerExitReason", {CLEAR_ON_MANAGER_START, STRING}},
{"LastOffroadStatusPacket", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, JSON}},
{"LastAgnosPowerMonitorShutdown", {CLEAR_ON_MANAGER_START, STRING}},
@@ -91,12 +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}},
@@ -135,17 +130,8 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"UpdaterLastFetchTime", {PERSISTENT, TIME}},
{"UptimeOffroad", {PERSISTENT, FLOAT, "0.0"}},
{"UptimeOnroad", {PERSISTENT, FLOAT, "0.0"}},
{"ChestnutActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
{"ChestnutLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
{"ChestnutRetry", {CLEAR_ON_MANAGER_START | CLEAR_ON_IGNITION_ON, BOOL}},
{"InitialCruiseSpeedKph", {PERSISTENT, INT, "40"}},
{"NavDestination", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, JSON}},
{"NavigationEnabled", {PERSISTENT, BOOL, "0"}},
{"Offroad_ChestnutModelError", {CLEAR_ON_MANAGER_START, JSON}},
{"Offroad_Pairing", {CLEAR_ON_MANAGER_START, JSON}},
{"Offroad_UploadsIgnored", {CLEAR_ON_MANAGER_START, JSON}},
{"PairingEmail", {PERSISTENT, STRING}},
{"PairingProvider", {PERSISTENT, STRING}},
{"UsbGpuActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
{"UsbGpuLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
{"Version", {PERSISTENT, STRING}},
// --- sunnypilot params --- //
@@ -209,16 +195,14 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
// Model Manager params
{"ModelManager_ActiveBundle", {PERSISTENT, JSON}},
{"ModelManager_ActiveBundleUSBGPU", {PERSISTENT, JSON}}, //TODO-SP: kept for migration, remove on next sync?
{"ModelManager_ActiveBundleChestnut", {PERSISTENT, JSON}},
{"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, JSON}},
{"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, STRING}},
{"ModelManager_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
{"ModelManager_DownloadRef", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
{"ModelManager_DownloadIndex", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, INT}},
{"ModelManager_Favs", {PERSISTENT | BACKUP, STRING}},
{"ModelManager_LastSyncTime", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
{"ModelManager_LastSyncTime_Chestnut", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
{"ModelManager_LastSyncTime_USBGPU", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
{"ModelManager_ModelsCache", {PERSISTENT | BACKUP, JSON}},
{"ModelManager_ModelsCache_Chestnut", {PERSISTENT | BACKUP, JSON}},
{"ModelManager_ModelsCache_USBGPU", {PERSISTENT | BACKUP, JSON}},
// Neural Network Lateral Control
{"NeuralNetworkLateralControl", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -247,6 +231,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"ToyotaEnforceStockLongitudinal", {PERSISTENT | BACKUP, BOOL, "0"}},
{"ToyotaStopAndGoHack", {PERSISTENT | BACKUP, BOOL, "0"}},
{"DynamicExperimentalControl", {PERSISTENT | BACKUP, BOOL, "0"}},
{"BlindSpot", {PERSISTENT | BACKUP, BOOL, "0"}},
// sunnypilot model params
@@ -260,7 +245,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
// mapd
{"MapAdvisorySpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, FLOAT}},
{"Mapd_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
{"MapdVersion", {PERSISTENT, STRING}},
{"MapSpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, FLOAT, "0.0"}},
{"NextMapSpeedLimit", {CLEAR_ON_ONROAD_TRANSITION, JSON}},
+4 -4
View File
@@ -27,14 +27,14 @@ public:
auto param_path = Params().getParamPath();
if (util::file_exists(param_path)) {
std::string real_path = util::readlink(param_path);
util::check_system(util::string_format("rm -rf %s", real_path.c_str()));
util::check_system(util::string_format("rm %s -rf", real_path.c_str()));
unlink(param_path.c_str());
}
if (getenv("COMMA_CACHE") == nullptr) {
util::check_system(util::string_format("rm -rf %s", Path::download_cache_root().c_str()));
util::check_system(util::string_format("rm %s -rf", Path::download_cache_root().c_str()));
}
util::check_system(util::string_format("rm -rf %s", Path::comma_home().c_str()));
util::check_system(util::string_format("rm -rf %s", msgq_path.c_str()));
util::check_system(util::string_format("rm %s -rf", Path::comma_home().c_str()));
util::check_system(util::string_format("rm %s -rf", msgq_path.c_str()));
unsetenv("OPENPILOT_PREFIX");
}
+35 -556
View File
@@ -1,47 +1,16 @@
"""QR code encoding, decoding, and UI textures."""
import functools
import itertools
"""Small QR encoder for the UI's byte-mode, error-correction-level-L codes."""
import numpy as np
import pyray as rl
# (ec codewords per block, block count) for levels L, M, Q, H, versions 1-40
_EC = [
((7, 1), (10, 1), (13, 1), (17, 1)), ((10, 1), (16, 1), (22, 1), (28, 1)), ((15, 1), (26, 1), (18, 2), (22, 2)),
((20, 1), (18, 2), (26, 2), (16, 4)), ((26, 1), (24, 2), (18, 4), (22, 4)), ((18, 2), (16, 4), (24, 4), (28, 4)),
((20, 2), (18, 4), (18, 6), (26, 5)), ((24, 2), (22, 4), (22, 6), (26, 6)), ((30, 2), (22, 5), (20, 8), (24, 8)),
((18, 4), (26, 5), (24, 8), (28, 8)), ((20, 4), (30, 5), (28, 8), (24, 11)), ((24, 4), (22, 8), (26, 10), (28, 11)),
((26, 4), (22, 9), (24, 12), (22, 16)), ((30, 4), (24, 9), (20, 16), (24, 16)), ((22, 6), (24, 10), (30, 12), (24, 18)),
((24, 6), (28, 10), (24, 17), (30, 16)), ((28, 6), (28, 11), (28, 16), (28, 19)), ((30, 6), (26, 13), (28, 18), (28, 21)),
((28, 7), (26, 14), (26, 21), (26, 25)), ((28, 8), (26, 16), (30, 20), (28, 25)), ((28, 8), (26, 17), (28, 23), (30, 25)),
((28, 9), (28, 17), (30, 23), (24, 34)), ((30, 9), (28, 18), (30, 25), (30, 30)), ((30, 10), (28, 20), (30, 27), (30, 32)),
((26, 12), (28, 21), (30, 29), (30, 35)), ((28, 12), (28, 23), (28, 34), (30, 37)), ((30, 12), (28, 25), (30, 34), (30, 40)),
((30, 13), (28, 26), (30, 35), (30, 42)), ((30, 14), (28, 28), (30, 38), (30, 45)), ((30, 15), (28, 29), (30, 40), (30, 48)),
((30, 16), (28, 31), (30, 43), (30, 51)), ((30, 17), (28, 33), (30, 45), (30, 54)), ((30, 18), (28, 35), (30, 48), (30, 57)),
((30, 19), (28, 37), (30, 51), (30, 60)), ((30, 19), (28, 38), (30, 53), (30, 63)), ((30, 20), (28, 40), (30, 56), (30, 66)),
((30, 21), (28, 43), (30, 59), (30, 70)), ((30, 22), (28, 45), (30, 62), (30, 74)), ((30, 24), (28, 47), (30, 65), (30, 77)),
((30, 25), (28, 49), (30, 68), (30, 81)),
]
# Indexes are QR versions. These are the only two Reed-Solomon parameters needed
# for error-correction level L.
_ECC_LEN = (0, 7, 10, 15, 20, 26, 18, 20, 24, 30, 18, 20, 24, 26, 30, 22, 24, 28, 30, 28, 28)
_NUM_BLOCKS = (0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 4, 4, 4, 4, 4, 6, 6, 6, 6, 7, 8)
# GF(256) with the QR polynomial x^8 + x^4 + x^3 + x^2 + 1: powers of alpha and their logs
_EXP = [1]
for _ in range(254):
_EXP.append(_EXP[-1] << 1 ^ (0x11D if _EXP[-1] & 0x80 else 0))
_LOG = {v: i for i, v in enumerate(_EXP)}
def _bch_format(data: int) -> int:
v = data << 10
for shift in range(14, 9, -1):
if v >> shift & 1:
v ^= 0x537 << (shift - 10)
return (data << 10 | v) ^ 0x5412
# 15-bit format info indexed by (level bits << 3 | mask). Level bits: L=01, M=00, Q=11, H=10.
_FORMATS = [_bch_format(d) for d in range(32)]
# 15 format-info bits for level L (01) with mask 0: ((0x08 << 10) | bch_remainder) ^ 0x5412
_FORMAT_BITS = 0b111011111000100
def _raw_modules(version: int) -> int:
@@ -52,24 +21,8 @@ def _raw_modules(version: int) -> int:
return result - (36 if version >= 7 else 0)
def _block_lengths(version: int, level: int) -> list[int]:
"""Data codewords per Reed-Solomon block. The last blocks may be one longer."""
ec, nblocks = _EC[version - 1][level]
total = _raw_modules(version) // 8 - ec * nblocks
return [total // nblocks + (i >= nblocks - total % nblocks) for i in range(nblocks)]
def _interleaved(version: int, level: int) -> list[tuple[int, int]]:
"""(block, index within block) of each transmitted codeword: data column-major, then ECC column-major."""
ec, nblocks = _EC[version - 1][level]
lens = _block_lengths(version, level)
data = [(b, i) for i in range(max(lens)) for b in range(nblocks) if i < lens[b]]
ecc = [(b, lens[b] + i) for i in range(ec) for b in range(nblocks)]
return data + ecc
def _capacity(version: int) -> int:
return sum(_block_lengths(version, 0))
return _raw_modules(version) // 8 - _ECC_LEN[version] * _NUM_BLOCKS[version]
def _append_bits(bits: list[int], value: int, length: int) -> None:
@@ -96,18 +49,37 @@ def _data_codewords(data: bytes, version: int) -> bytes:
def _codewords(data: bytes, version: int) -> bytes:
"""Split data codewords into Reed-Solomon blocks and interleave data + ECC."""
data = _data_codewords(data, version)
divisor = _divisor(_EC[version - 1][0][0])
blocks = []
num_blocks = _NUM_BLOCKS[version]
ecc_len = _ECC_LEN[version]
raw_codewords = _raw_modules(version) // 8
short_len = raw_codewords // num_blocks
num_short = num_blocks - raw_codewords % num_blocks
divisor = _divisor(ecc_len)
blocks: list[tuple[bytes, bytes]] = []
offset = 0
for length in _block_lengths(version, 0):
for i in range(num_blocks):
length = short_len - ecc_len + (0 if i < num_short else 1)
block = data[offset:offset + length]
blocks.append(block + _remainder(block, divisor))
blocks.append((block, _remainder(block, divisor)))
offset += length
return bytes(blocks[b][i] for b, i in _interleaved(version, 0))
result = bytearray()
for i in range(short_len - ecc_len + 1):
for block, _ in blocks:
result.extend(block[i:i + 1])
for i in range(ecc_len):
for _, ecc in blocks:
result.append(ecc[i])
return bytes(result)
def _multiply(x: int, y: int) -> int:
return _EXP[(_LOG[x] + _LOG[y]) % 255] if x and y else 0
result = 0
for _ in range(8):
result = (result << 1) ^ (0x11D if result & 0x80 else 0)
if y & 0x80:
result ^= x
y <<= 1
return result
def _divisor(degree: int) -> bytes:
@@ -136,7 +108,7 @@ def _alignment_positions(version: int) -> list[int]:
if version == 1:
return []
count = version // 7 + 2
step = (version * 8 + count * 3 + 5) // (count * 4 - 4) * 2
step = ((version * 4 + count * 2 + 1) // (count * 2 - 2)) * 2
return [6] + [version * 4 + 10 - step * i for i in range(count - 1)][::-1]
@@ -199,7 +171,7 @@ class _Qr:
def _format(self) -> None:
for i in range(15):
bit = ((_FORMATS[1 << 3 | 0] >> i) & 1) != 0 # level L, mask 0
bit = ((_FORMAT_BITS >> i) & 1) != 0
y_pos = i if i < 6 else i + 1 if i < 8 else self.size - 15 + i
self._set_function(8, y_pos, bit)
x_pos = self.size - 1 - i if i < 8 else 15 - i if i < 9 else 14 - i
@@ -244,496 +216,3 @@ def make_texture(data: str, inverted: bool = False) -> rl.Texture:
rl_image.mipmaps = 1
rl_image.format = rl.PixelFormat.PIXELFORMAT_UNCOMPRESSED_R8G8B8A8
return rl.load_texture_from_image(rl_image)
# ---- Symbol structure for decoding ----
class QRError(Exception):
pass
_LEVELS = (1, 0, 3, 2) # format info level bits -> column in _EC
_MASKS = [
lambda i, j: (i + j) % 2 == 0,
lambda i, j: i % 2 == 0,
lambda i, j: j % 3 == 0,
lambda i, j: (i + j) % 3 == 0,
lambda i, j: (i // 2 + j // 3) % 2 == 0,
lambda i, j: (i * j) % 2 + (i * j) % 3 == 0,
lambda i, j: ((i * j) % 2 + (i * j) % 3) % 2 == 0,
lambda i, j: ((i + j) % 2 + (i * j) % 3) % 2 == 0,
]
_ALIGNMENT = np.ones((5, 5), dtype=bool)
_ALIGNMENT[1:4, 1:4] = False
_ALIGNMENT[2, 2] = True
def _gf_inv(a: int) -> int:
return _EXP[-_LOG[a] % 255]
@functools.lru_cache
def _data_coords(version: int) -> tuple[np.ndarray, np.ndarray]:
"""(rows, cols) of the data and error correction modules in placement order: two-column zigzag from the right."""
dim = version * 4 + 17
func = np.zeros((dim, dim), dtype=bool) # finder, timing, alignment, format, and version modules
func[:9, :9] = func[:9, dim - 8:] = func[dim - 8:, :9] = True
func[6, :] = func[:, 6] = True
positions = _alignment_positions(version)
for r, c in itertools.product(positions, positions):
if (r, c) not in ((6, 6), (6, dim - 7), (dim - 7, 6)):
func[r - 2:r + 3, c - 2:c + 3] = True
if version >= 7:
func[:6, dim - 11:dim - 8] = func[dim - 11:dim - 8, :6] = True
ys = np.arange(dim)
rows, cols = [], []
# the vertical timing column is skipped, so the pairs left of it start at odd columns
for i, right in enumerate(col if col > 6 else col - 1 for col in range(dim - 1, 0, -2)):
r = np.repeat(ys[::-1] if i % 2 == 0 else ys, 2)
c = np.tile((right, right - 1), dim)
keep = ~func[r, c]
rows.append(r[keep])
cols.append(c[keep])
return np.concatenate(rows), np.concatenate(cols)
# ---- Matrix decoding ----
def _poly_eval(p: list[int], x: int) -> int:
# p is highest degree first
y = 0
for c in p:
y = _multiply(y, x) ^ c
return y
_EXP_TABLE = np.array(_EXP)
_LOG_TABLE = np.array([_LOG.get(v, 0) for v in range(256)])
def _syndromes(msg: list[int], nsym: int) -> list[int]:
"""syn[i] = msg(alpha^i), msg highest degree first."""
m = np.array(msg)
exponents = np.arange(nsym)[:, None] * (len(msg) - 1 - np.arange(len(msg)))
return np.bitwise_xor.reduce(_EXP_TABLE[(_LOG_TABLE[m] + exponents) % 255] * (m != 0), axis=1).tolist()
def _rs_correct(msg: list[int], nsym: int) -> list[int]:
"""Corrects up to nsym // 2 errors in a Reed-Solomon codeword, in place."""
n = len(msg)
syn = _syndromes(msg, nsym)
if not any(syn):
return msg
# Berlekamp-Massey, sigma is lowest degree first
sigma, prev, L, m, b = [1], [1], 0, 1, 1
for r in range(nsym):
d = syn[r]
for i in range(1, L + 1):
d ^= _multiply(sigma[i], syn[r - i])
if d == 0:
m += 1
continue
coef = _multiply(d, _gf_inv(b))
shifted = [0] * m + prev
saved = sigma[:]
sigma = sigma + [0] * max(0, len(shifted) - len(sigma))
for i, c in enumerate(shifted):
sigma[i] ^= _multiply(coef, c)
if 2 * L <= r:
L, prev, b, m = r + 1 - L, saved, d, 1
else:
m += 1
sigma = sigma[:L + 1]
if 2 * L > nsym:
raise QRError("too many errors")
# Chien search: codeword position p has locator alpha^(n-1-p)
positions = [p for p in range(n) if _poly_eval(sigma[::-1], _EXP[(p - n + 1) % 255]) == 0]
if len(positions) != L:
raise QRError("error locator mismatch")
# solve syn[i] = sum_k e_k * X_k^i for the magnitudes e_k
xlog = [(n - 1 - p) % 255 for p in positions]
A = [[_EXP[(xlog[k] * i) % 255] for k in range(L)] + [syn[i]] for i in range(L)]
for col in range(L):
piv = next((r for r in range(col, L) if A[r][col]), None)
if piv is None:
raise QRError("singular")
A[col], A[piv] = A[piv], A[col]
inv = _gf_inv(A[col][col])
A[col] = [_multiply(inv, v) for v in A[col]]
for r in range(L):
if r != col and A[r][col]:
f = A[r][col]
A[r] = [a ^ _multiply(f, c) for a, c in zip(A[r], A[col], strict=True)]
for k, p in enumerate(positions):
msg[p] ^= A[k][L]
if any(_syndromes(msg, nsym)):
raise QRError("uncorrectable")
return msg
def _read_format(m: np.ndarray) -> int:
"""Returns the closest format info (level bits << 3 | mask) from either copy."""
dim = m.shape[0]
copies = ([(8, i) for i in range(6)] + [(8, 7), (8, 8), (7, 8)] + [(5 - i, 8) for i in range(6)],
[(dim - 1 - i, 8) for i in range(7)] + [(8, dim - 8 + i) for i in range(8)]) # (row, col), msb first
candidates = []
for coords in copies:
bits = int("".join(str(int(m[r, c])) for r, c in coords), 2)
candidates += [((bits ^ f).bit_count(), i) for i, f in enumerate(_FORMATS)]
distance, fmt = min(candidates)
if distance > 3:
raise QRError("bad format info")
return fmt
_ALNUM = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ $%*+-./:"
_ECI_ENCODINGS = {
0: "cp437", 2: "cp437", 1: "iso8859-1", 3: "iso8859-1",
**{i + 2: f"iso8859-{i}" for i in range(2, 17) if i != 12},
20: "shift_jis", 21: "cp1250", 22: "cp1251", 23: "cp1252", 24: "cp1256",
25: "utf-16-be", 26: "utf-8", 27: "ascii", 170: "ascii", 28: "big5", 29: "gb18030", 30: "euc_kr",
}
class _Bits:
def __init__(self, data: list[int]):
self._value = int.from_bytes(bytes(data), "big")
self.remaining = len(data) * 8
def read(self, n: int) -> int:
if n > self.remaining:
raise QRError("bitstream underflow")
self.remaining -= n
return self._value >> self.remaining & (1 << n) - 1
def read_below(self, n: int, limit: int) -> int:
v = self.read(n)
if v >= limit:
raise QRError("value out of range")
return v
def _parse_data(data: list[int], version: int) -> str:
bits = _Bits(data)
out: list[str] = []
encoding = None
band = 0 if version <= 9 else 1 if version <= 26 else 2
while bits.remaining >= 4:
mode = bits.read(4)
if mode == 0:
break
if mode == 7: # ECI character set assignment
first = bits.read(8)
extra = 0 if first < 0x80 else 8 if first < 0xC0 else 16 if first < 0xE0 else -1 # 1, 2, or 3 byte assignment
if extra < 0:
raise QRError("bad ECI assignment")
assignment = (first & 0x7F >> extra // 8) << extra | bits.read(extra)
encoding = _ECI_ENCODINGS.get(assignment)
if encoding is None:
raise QRError(f"unsupported ECI assignment {assignment}")
elif mode == 1:
n = bits.read((10, 12, 14)[band])
while n > 0:
k = min(n, 3) # 3 digits in 10 bits, the last 2 or 1 in 7 or 4
out.append(f"{bits.read_below((4, 7, 10)[k - 1], 10 ** k):0{k}d}")
n -= k
elif mode == 2:
n = bits.read((9, 11, 13)[band])
while n > 0:
k = min(n, 2) # 2 characters in 11 bits, a last one in 6
v = bits.read_below((6, 11)[k - 1], 45 ** k)
out.append(_ALNUM[v // 45] * (k - 1) + _ALNUM[v % 45])
n -= k
elif mode == 4:
n = bits.read((8, 16, 16)[band])
segment = bytes(bits.read(8) for _ in range(n))
try:
out.append(segment.decode(encoding or "utf-8"))
except UnicodeDecodeError as e:
if encoding is not None:
raise QRError("invalid ECI byte segment") from e
out.append(segment.decode("latin-1"))
elif mode == 8:
n = bits.read((8, 10, 12)[band])
for _ in range(n):
v = bits.read(13)
c = (v // 0xC0) << 8 | v % 0xC0
c += 0x8140 if c < 0x1F00 else 0xC140
try:
out.append(c.to_bytes(2, "big").decode("shift_jis"))
except UnicodeDecodeError as e:
raise QRError("invalid Kanji character") from e
else:
raise QRError(f"unsupported mode {mode}")
return "".join(out)
def decode_matrix(m: np.ndarray) -> str:
"""Decodes a square boolean module matrix (True = dark) without a quiet zone."""
dim = m.shape[0]
if m.shape != (dim, dim) or dim % 4 != 1 or not 21 <= dim <= 177:
raise QRError("bad matrix size")
version = (dim - 17) // 4
fmt = _read_format(m)
level = _LEVELS[fmt >> 3]
rows, cols = _data_coords(version)
bits = m[rows, cols] ^ _MASKS[fmt & 7](rows, cols)
codewords = np.packbits(bits[:len(bits) // 8 * 8]).tolist()
ec, _ = _EC[version - 1][level]
lens = _block_lengths(version, level)
blocks = [[0] * (n + ec) for n in lens]
for (b, i), codeword in zip(_interleaved(version, level), codewords, strict=True):
blocks[b][i] = codeword
data: list[int] = []
for block, n in zip(blocks, lens, strict=True):
data += _rs_correct(block, ec)[:n]
return _parse_data(data, version)
# ---- Image decoding ----
def _box_sums(a: np.ndarray, radii: tuple[int, ...]) -> list[np.ndarray]:
"""Sums over (2r + 1)^2 neighborhoods of the last two axes, edge padded, from one integral image."""
P = max(radii)
lead = [(0, 0)] * (a.ndim - 2)
cs = np.pad(np.cumsum(np.cumsum(np.pad(a, lead + [(P, P), (P, P)], mode="edge"), -2), -1), lead + [(1, 0), (1, 0)])
H, W = a.shape[-2:]
out = []
for r in radii:
lo, hi = P - r, P + r + 1
out.append(cs[..., hi:hi + H, hi:hi + W] - cs[..., lo:lo + H, hi:hi + W] - cs[..., hi:hi + H, lo:lo + W] + cs[..., lo:lo + H, lo:lo + W])
return out
def _binarize(gray: np.ndarray) -> np.ndarray:
"""Adaptive threshold: each pixel against the mean of the surrounding tiles that have contrast."""
h, w = gray.shape
if h < 21 or w < 21:
raise QRError("image too small")
B = max(8, min(h, w) // 128 * 2)
H, W = -(-h // B), -(-w // B)
padded = np.pad(gray, ((0, H * B - h), (0, W * B - w)), mode="edge")
# block statistics from a subsample are plenty
sub = np.ascontiguousarray(padded[::2, ::2].reshape(H, B // 2, W, B // 2).transpose(0, 2, 1, 3)).reshape(H, W, -1)
blocks = sub.sum(axis=2, dtype=np.uint32) / sub.shape[2]
known = sub.max(axis=2) - sub.min(axis=2) >= 32
# Flat tiles cannot estimate their own threshold: use the tiles with contrast nearby, then
# further out, then the global midrange. A flat tile is then all dark or all light.
est = np.full((H, W), (blocks.min() + blocks.max()) / 2)
filled = np.zeros((H, W), dtype=bool)
for total, count in _box_sums(np.stack((known * blocks, known.astype(float))), (2, 6)):
fill = ~filled & (count > 0)
est[fill] = total[fill] / count[fill]
filled |= fill
thr = np.where(known, np.minimum(est, 254) + 1, np.where(blocks <= est, 255, 0)).astype(np.uint8)
return (padded.reshape(H, B, W, B) < thr[:, None, :, None]).reshape(H * B, W * B)[:h, :w]
class _Runs:
"""Run-length table of a padded, flattened binary image with a per-pixel run index."""
def __init__(self, padded: np.ndarray):
self.flat = padded.ravel()
self.lines, self.stride = padded.shape
change = self.flat[1:] != self.flat[:-1]
self.starts = np.concatenate(([0], np.flatnonzero(change) + 1))
self.lengths = np.diff(np.append(self.starts, self.flat.size)).astype(np.int32)
def run_at(self, line: np.ndarray, pos: np.ndarray) -> np.ndarray:
"""Index of the run containing the pixel at `pos` along `line`."""
return np.searchsorted(self.starts, line * self.stride + pos + 1, side="right") - 1
@staticmethod
def _match(lengths: list[np.ndarray], ratios: tuple[int, ...]) -> tuple[np.ndarray, np.ndarray]:
"""Checks windows of runs against the ratios, given the length of each run. Returns (ok, module size)."""
S = sum(ratios)
total = sum(lengths[1:], start=lengths[0])
ok = total >= 2 * S # modules need to be at least 2 px
for L, r in zip(lengths, ratios, strict=True):
ok &= np.abs(2 * S * L - 2 * r * total) <= r * total # integer form of |L - r * total / S| <= r * total / (2 * S)
return ok, total / S
def scan(self, ratios: tuple[int, ...]) -> np.ndarray:
"""Returns the indices of all dark runs starting a window of runs matching the ratios."""
n = len(ratios)
N = len(self.lengths) - n + 1
if N <= 0:
return np.zeros(0, dtype=int)
ok, _ = self._match([self.lengths[k:N + k] for k in range(n)], ratios)
ok &= self.flat[self.starts[:N]]
first = np.flatnonzero(ok)
return first[self.starts[first] // self.stride == self.starts[first + n - 1] // self.stride]
def check(self, first: np.ndarray, ratios: tuple[int, ...]) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""Checks the run windows starting at run index `first`. Returns (ok, center position along the line, module size)."""
n, half = len(ratios), len(ratios) // 2
ok = (first >= 0) & (first + n <= len(self.starts))
idx = np.clip(first[:, None] + np.arange(n), 0, len(self.starts) - 1)
matched, module = self._match([self.lengths[idx[:, k]] for k in range(n)], ratios)
ok &= matched & self.flat[self.starts[idx[:, 0]]]
ok &= self.starts[idx[:, 0]] // self.stride == self.starts[idx[:, -1]] // self.stride
center = self.starts[idx[:, half]] % self.stride - 1 + self.lengths[idx[:, half]] / 2
return ok, center, module
def _find_patterns(binary: np.ndarray, ratios: tuple[int, ...]) -> list[tuple[float, float, float]]:
"""Finds dark/light run patterns with the given module ratios. Returns (x, y, module size)."""
half = len(ratios) // 2
step = 2 # the center rows of a 2 px finder pattern still get scanned twice
rows_t = _Runs(np.pad(binary[::step], ((0, 0), (1, 1))))
first = rows_t.scan(ratios)
if len(first) == 0:
return []
_, cx, hmod = rows_t.check(first, ratios)
row = rows_t.starts[first] // rows_t.stride * step
xi = cx.astype(int)
xs, col = np.unique(xi, return_inverse=True)
cols_t = _Runs(np.pad(binary[:, xs].T, ((0, 0), (1, 1))))
ok, cy, vmod = cols_t.check(cols_t.run_at(col, row) - half, ratios)
ok &= (0.5 <= vmod / hmod) & (vmod / hmod <= 2)
line = np.clip(np.rint(cy / step), 0, rows_t.lines - 1).astype(int)
ok2, cx2, hmod2 = rows_t.check(rows_t.run_at(line, xi) - half, ratios)
ok &= ok2 & (0.5 <= hmod2 / vmod) & (hmod2 / vmod <= 2)
found: list[list[float]] = [] # [x, y, module, count]
for x, y, module in zip(cx2[ok], cy[ok], (hmod2[ok] + vmod[ok]) / 2, strict=True):
for f in found:
if abs(f[0] - x) <= f[2] and abs(f[1] - y) <= f[2] and 0.5 <= f[2] / module <= 2:
c = f[3]
f[0], f[1], f[2], f[3] = (f[0] * c + x) / (c + 1), (f[1] * c + y) / (c + 1), (f[2] * c + module) / (c + 1), c + 1
break
else:
found.append([x, y, module, 1])
found.sort(key=lambda f: -f[3])
return [(f[0], f[1], f[2]) for f in found if f[3] >= 2]
def _pick_finders(patterns: list[tuple[float, float, float]]) -> tuple[np.ndarray, np.ndarray, np.ndarray, float]:
"""Returns (top-left, top-right, bottom-left) centers and the module size of the most square-looking triple."""
best = None
for a, b, c in itertools.combinations(patterns[:10], 3):
mods = sorted((a[2], b[2], c[2]))
if mods[2] / mods[0] > 1.5:
continue
pts = [np.array(p[:2]) for p in (a, b, c)]
d = [np.linalg.norm(pts[(i + 1) % 3] - pts[(i + 2) % 3]) for i in range(3)]
tl = int(np.argmax(d)) # opposite the hypotenuse
p1, p2 = pts[(tl + 1) % 3], pts[(tl + 2) % 3]
v1, v2 = p1 - pts[tl], p2 - pts[tl]
n1, n2 = np.linalg.norm(v1), np.linalg.norm(v2)
if n1 == 0 or n2 == 0:
continue
cos = abs(np.dot(v1, v2)) / (n1 * n2)
if cos > 0.35 or not 0.6 <= n1 / n2 <= 1.6:
continue
score = cos + abs(np.log(n1 / n2)) + np.log(mods[2] / mods[0])
if best is not None and score >= best[0]:
continue
if v1[0] * v2[1] - v1[1] * v2[0] < 0:
p1, p2 = p2, p1
best = (score, pts[tl], p1, p2, float(sum(mods) / 3))
if best is None:
raise QRError("no finder patterns")
return best[1:]
def _perspective(src: np.ndarray, dst: np.ndarray) -> np.ndarray:
"""Homography mapping the four src points onto the four dst points."""
A = [row for (x, y), (u, v) in zip(src, dst, strict=True)
for row in ([x, y, 1, 0, 0, 0, -u * x, -u * y], [0, 0, 0, x, y, 1, -v * x, -v * y])]
try:
h = np.linalg.solve(np.array(A, dtype=float), np.asarray(dst, dtype=float).ravel())
except np.linalg.LinAlgError as e:
raise QRError("degenerate geometry") from e
return np.append(h, 1).reshape(3, 3)
def _transform(H: np.ndarray, pts: np.ndarray) -> np.ndarray:
p = np.column_stack((pts, np.ones(len(pts)))) @ H.T
return p[:, :2] / p[:, 2:3]
def _match_alignment(binary: np.ndarray, est: np.ndarray, offs: np.ndarray, r: int, module: float) -> np.ndarray | None:
h, w = binary.shape
dy = np.arange(max(0, int(est[1]) - r), min(h, int(est[1]) + r)) - est[1]
dx = np.arange(max(0, int(est[0]) - r), min(w, int(est[0]) + r)) - est[0]
if len(dy) == 0 or len(dx) == 0:
return None
y = np.rint(est[1] + dy[:, None, None] + offs[None, None, :, 1]).astype(int)
x = np.rint(est[0] + dx[None, :, None] + offs[None, None, :, 0]).astype(int)
valid = ((y >= 0) & (y < h) & (x >= 0) & (x < w)).all(axis=2)
samples = binary[np.clip(y, 0, h - 1), np.clip(x, 0, w - 1)]
score = np.where(valid, (samples == _ALIGNMENT.ravel()).sum(axis=2), 0)
if score.max() < 23:
return None
hits = np.argwhere(score == score.max())
centers = np.column_stack((est[0] + dx[hits[:, 1]], est[1] + dy[hits[:, 0]]))
closest = centers[np.argmin(np.linalg.norm(centers - est, axis=1))]
return centers[np.linalg.norm(centers - closest, axis=1) <= module / 2].mean(axis=0)
def _locate_alignment(binary: np.ndarray, H: np.ndarray, center: float, module: float) -> np.ndarray | None:
"""Template matches the 5x5 alignment pattern around its position estimated from H."""
grid = np.mgrid[-2:3, -2:3].reshape(2, -1).T[:, ::-1] + center # (25, 2) module coords (x, y)
pts = _transform(H, grid)
# the affine estimate can be off in both position and local scale under perspective
for radius in (2, 4, 8, 16):
for scale in (1.0, 0.8, 1.25, 0.65, 1.5):
found = _match_alignment(binary, pts[12], (pts - pts[12]) * scale, int(module * radius), module)
if found is not None:
return found
return None
def _sample(binary: np.ndarray, tl: np.ndarray, tr: np.ndarray, bl: np.ndarray, module: float, dim: int, use_alignment: bool) -> np.ndarray:
src = np.array([(3.5, 3.5), (dim - 3.5, 3.5), (3.5, dim - 3.5), (dim - 3.5, dim - 3.5)])
dst = np.array([tl, tr, bl, tr + bl - tl])
H = _perspective(src, dst)
if use_alignment and dim > 21:
align = _locate_alignment(binary, H, dim - 6.5, module)
if align is not None:
src[3], dst[3] = (dim - 6.5, dim - 6.5), align
H = _perspective(src, dst)
rows, cols = np.mgrid[0:dim, 0:dim]
pts = _transform(H, np.column_stack((cols.ravel() + 0.5, rows.ravel() + 0.5)))
xy = np.rint(pts).astype(int)
h, w = binary.shape
if (xy < 0).any() or (xy[:, 0] >= w).any() or (xy[:, 1] >= h).any():
raise QRError("code extends outside image")
return binary[xy[:, 1], xy[:, 0]].reshape(dim, dim)
def decode(gray: np.ndarray) -> str | None:
"""Decodes the QR code in a 2D uint8 grayscale image. Modules need to be at least 2 px.
Returns None if nothing could be decoded."""
try:
binary = _binarize(gray)
tl, tr, bl, module = _pick_finders(_find_patterns(binary, (1, 1, 3, 1, 1)))
except QRError:
return None
d = (np.linalg.norm(tr - tl) + np.linalg.norm(bl - tl)) / 2
dim = int(round((d / module + 7 - 17) / 4)) * 4 + 17
dims = [cand for cand in (dim, dim - 4, dim + 4) if 21 <= cand <= 177]
for cand, use_alignment, transpose in itertools.product(dims, (True, False), (False, True)):
try:
m = _sample(binary, tl, tr, bl, module, cand, use_alignment)
return decode_matrix(m.T if transpose else m)
except QRError:
pass
return None
+2 -7
View File
@@ -91,13 +91,8 @@ class Ratekeeper:
self.avg_dt.add_value(self._last_monitor_time - prev)
lagged = False
now = time.monotonic()
remaining = self._next_frame_time - now
if remaining < -self._interval:
# more than a frame behind (e.g. a stall): resync instead of running catch-up frames back-to-back
self._next_frame_time = now + self._interval
else:
self._next_frame_time += self._interval
remaining = self._next_frame_time - time.monotonic()
self._next_frame_time += self._interval
if self._print_delay_threshold is not None and remaining < -self._print_delay_threshold:
print(f"{self._process_name} lagging by {-remaining * 1000:.2f} ms")
lagged = True
Binary file not shown.
Binary file not shown.
Binary file not shown.
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-178
View File
@@ -1,178 +0,0 @@
import hashlib
import math
from pathlib import Path
import numpy as np
from openpilot.common import qrcode as qr
from openpilot.common.test import OpenpilotTestCase
LPA = "LPA:1$rsp.truphone.com$QRF-BETTERROAMING-PMRDGIR2EARDEIT5"
# Matrices generated with python-qrcode 8.2, covering all versions and EC levels.
# Packed fixtures keep the decoder tests independent of our encoder.
FIXTURES = {}
for path in Path(__file__).with_name("fixtures").glob("qrcode_*.npz"):
with np.load(path) as fixtures:
FIXTURES.update({key: fixtures[key] for key in fixtures.files})
def fixture(key: str) -> np.ndarray:
bits = np.unpackbits(FIXTURES[key])
size = math.isqrt(len(bits))
return bits[:size * size].reshape(size, size).astype(bool)
def render(matrix: np.ndarray, box: int = 6, border: int = 4) -> np.ndarray:
img = np.repeat(np.repeat(np.pad(matrix, border), box, axis=0), box, axis=1)
return np.where(img, 0, 255).astype(np.uint8)
def make(data: str, version: int | None = None, level: int = 0, box: int = 6, border: int = 4):
matrix = fixture(hashlib.sha256(f"{version}:{level}:{data}".encode()).hexdigest())
return matrix, render(matrix, box, border)
def warp(img: np.ndarray, H: np.ndarray) -> np.ndarray:
"""Bilinear resampling through the output -> input homography H, white outside the image."""
h, w = img.shape
rows, cols = np.mgrid[0:h, 0:w]
pts = qr._transform(H, np.column_stack((cols.ravel() + 0.5, rows.ravel() + 0.5))) - 0.5
x0, y0 = np.floor(pts[:, 0]).astype(int), np.floor(pts[:, 1]).astype(int)
fx, fy = pts[:, 0] - x0, pts[:, 1] - y0
padded = np.pad(img.astype(float), 1, constant_values=255)
def at(y, x):
return padded[np.clip(y + 1, 0, h + 1), np.clip(x + 1, 0, w + 1)]
out = at(y0, x0) * (1 - fx) * (1 - fy) + at(y0, x0 + 1) * fx * (1 - fy) + at(y0 + 1, x0) * (1 - fx) * fy + at(y0 + 1, x0 + 1) * fx * fy
return np.clip(out, 0, 255).astype(np.uint8).reshape(h, w)
def rotate(img: np.ndarray, angle: float) -> np.ndarray:
h, w = img.shape
t = np.radians(angle)
R = np.array([[np.cos(t), -np.sin(t)], [np.sin(t), np.cos(t)]])
center = np.array([w / 2, h / 2])
corners = np.array([(0, 0), (w, 0), (w, h), (0, h)], dtype=float)
return warp(img, qr._perspective((corners - center) @ R.T + center, corners))
class TestQRCode(OpenpilotTestCase):
def test_alignment_positions(self):
assert qr._alignment_positions(7) == [6, 22, 38]
assert qr._alignment_positions(32) == [6, 34, 60, 86, 112, 138]
assert qr._alignment_positions(40) == [6, 30, 58, 86, 114, 142, 170]
def test_all_versions(self):
for version in range(1, 41):
for level in range(4):
with self.subTest(version=version, level=level):
data = "".join(chr(ord("a") + i % 26) for i in range(version))
matrix, img = make(data, version, level, box=3)
assert qr.decode_matrix(matrix) == data
assert qr.decode(img) == data
def test_modes(self):
for data in ["0123456789012345", "HELLO WORLD $1.50", LPA, "こんにちは", "ünïcødé", "mixed 123 ABC xyz"]:
with self.subTest(data=data):
matrix, img = make(data)
assert qr.decode_matrix(matrix) == data
assert qr.decode(img) == data
def test_error_correction(self):
matrix, _ = make(LPA, level=2)
rng = np.random.default_rng(0)
flipped = matrix.copy()
for r, c in rng.integers(9, matrix.shape[0] - 9, size=(40, 2)):
flipped[r, c] ^= True
assert qr.decode_matrix(flipped) == LPA
def test_large_modules(self):
for data in ["0123456789012345", "HELLO WORLD $1.50", LPA, "mixed 123 ABC xyz"]:
for box in [16, 20, 24, 32]:
for dark, light in [(0, 255), (60, 200), (140, 250)]:
with self.subTest(data=data, box=box, dark=dark):
_, img = make(data, box=box)
img = np.where(img == 0, dark, light).astype(np.uint8)
assert qr.decode(img) == data
def test_image_edges(self):
# a code touching the image edge must not lose the rows and columns left over from tiling
matrix, _ = make(LPA)
for size in (200, 203):
with self.subTest(size=size):
img = np.full((size, size), 255, dtype=np.uint8)
code = render(matrix, box=5, border=0)
img[size - code.shape[0]:, size - code.shape[1]:] = code
assert qr.decode(img) == LPA
def test_eci(self):
# qrcode_eci.npz: packed Segno 1.6.6 matrices, generated with mode='byte',
# eci=True, micro=False and the named encoding. Mixed also includes numeric,
# alphanumeric, and Kanji segments after changing the byte encoding twice.
cases = {
"iso8859-5": "Привет", "utf-16-be": "héllo", "utf-8": "こんにちは",
"shift_jis": "日本語", "cp1251": "Привет", "iso8859-1": "héllo",
"mixed": "hélloПривет日本語123ABC漢字",
}
for encoding, expected in cases.items():
with self.subTest(encoding=encoding):
matrix = fixture(encoding)
assert qr.decode_matrix(matrix) == expected
assert qr.decode(render(matrix)) == expected
def test_parse_data(self):
def parse(stream: str) -> str:
stream += '0' * (-len(stream) % 8)
return qr._parse_data([int(stream[i:i + 8], 2) for i in range(0, len(stream), 8)], 1)
def eci(assignment: str, payload: bytes = b'A') -> str:
return parse('0111' + assignment + '0100' + f'{len(payload):08b}' + ''.join(f'{b:08b}' for b in payload) + '0000')
# ASCII assignment 170 uses the two-byte ECI representation.
assert eci('1000000010101010') == 'A'
for assignment in ['00001110', '1000001111100111', '110000010000000000000000', '11100000']:
with self.subTest(assignment=assignment), self.assertRaises(qr.QRError):
eci(assignment)
with self.assertRaises(qr.QRError):
eci('00011010', b'\xff') # Invalid UTF-8 must not fall back to Latin-1.
# out-of-range numeric, alphanumeric, and Kanji values are format errors, not crashes
for stream in ['0001' + '0000000011' + '1111111111', '0001' + '0000000010' + '1111111',
'0010' + '000000010' + '11111111111', '0010' + '000000001' + '111111',
'1000' + '00000001' + '0000000111111']:
with self.subTest(stream=stream), self.assertRaises(qr.QRError):
parse(stream)
def test_rotation(self):
for angle in [0, 90, 180, 270, 25, 110]:
with self.subTest(angle=angle):
_, img = make(LPA, box=8, border=12)
assert qr.decode(rotate(img, angle)) == LPA
def test_mirrored(self):
_, img = make(LPA)
assert qr.decode(img[:, ::-1]) == LPA
def test_perspective_and_noise(self):
_, img = make(LPA, box=10, border=8)
h, w = img.shape
corners = np.array([(40, 60), (w - 20, 30), (w - 60, h - 40), (30, h - 90)])
arr = warp(img, qr._perspective(corners, np.array([(0, 0), (w, 0), (w, h), (0, h)]))).astype(float)
rng = np.random.default_rng(1)
arr = arr * 0.6 + 60 + rng.normal(0, 12, arr.shape) # low contrast + noise
# uneven lighting
arr += np.linspace(-40, 40, w)[None, :]
assert qr.decode(np.clip(arr, 0, 255).astype(np.uint8)) == LPA
def test_no_code(self):
rng = np.random.default_rng(2)
assert qr.decode(rng.integers(0, 256, size=(240, 320), dtype=np.uint8)) is None
assert qr.decode(np.full((240, 320), 200, dtype=np.uint8)) is None
def test_encoder_roundtrip(self):
for version in range(1, 21):
with self.subTest(version=version):
assert qr.decode_matrix(np.array(qr._Qr(version, b"hello").modules)) == "hello"
+15
View File
@@ -5,6 +5,7 @@ import contextlib
import subprocess
import time
import functools
from subprocess import Popen, PIPE, TimeoutExpired
import zstandard as zstd
LOG_COMPRESSION_LEVEL = 10 # little benefit up to level 15. level ~17 is a small step change
@@ -156,6 +157,20 @@ def run_cmd_default(cmd: list[str], default: str = "", cwd=None, env=None) -> st
return default
@contextlib.contextmanager
def managed_proc(cmd: list[str], env: dict[str, str]):
proc = Popen(cmd, env=env, stdout=PIPE, stderr=PIPE)
try:
yield proc
finally:
if proc.poll() is None:
proc.terminate()
try:
proc.wait(timeout=5)
except TimeoutExpired:
proc.kill()
def tabulate(tabular_data, headers=(), tablefmt="simple", floatfmt="g", stralign="left", numalign=None):
rows = [list(row) for row in tabular_data]
+1 -1
View File
@@ -1 +1 @@
#define COMMA_VERSION "0.11.3"
#define COMMA_VERSION "0.11.2"
-9
View File
@@ -16,15 +16,6 @@ MASTER_SP_BRANCHES = ['master']
RELEASE_BRANCHES = ['release-tizi-staging', 'release-mici-staging', 'release-tizi', 'release-mici', 'nightly']
TESTED_BRANCHES = RELEASE_BRANCHES + ['devel-staging', 'nightly-dev'] + RELEASE_SP_BRANCHES + TESTED_SP_BRANCHES
CHESTNUT_BRANCHES = {
"staging": "staging-chestnut",
"dev": "dev-chestnut",
"release-mici": "release-chestnut",
"release-tizi": "release-chestnut",
"release-mici-staging": "release-chestnut-staging",
"release-tizi-staging": "release-chestnut-staging",
}
SP_BRANCH_MIGRATIONS = {
("tici", "staging-c3-new"): "staging-tici",
("tici", "dev-c3-new"): "staging-tici",
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Binary file not shown.
+2 -2
View File
@@ -23,8 +23,8 @@ done
# sudo apt install inkscape
for svg in $(find "$DIR" -type f | grep svg$); do
bunx svgo "$svg" --multipass --pretty --indent 2
for svg in $(find $DIR -type f | grep svg$); do
bunx svgo $svg --multipass --pretty --indent 2
# convert to PNG
png="${svg%.svg}.png"
@@ -1,3 +0,0 @@
version https://git-lfs.github.com/spec/v1
oid sha256:5d02369e21d3c78a3a5ece7e78deedb82343bc3228a28db73da48b5c27860004
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version https://git-lfs.github.com/spec/v1
oid sha256:884e828e5c51d980d41b6e2400fcb4f4a926275018a00674d8239184e1eb96db
oid sha256:1bb440f424c989c06e203bfba0b32d39aede8f6c78a9b335e5e778460202b601
size 73026
+10 -3
View File
@@ -127,6 +127,9 @@ class Car:
set_alternative_experience(self.CP, self.CP_SP, self.params)
set_car_specific_params(self.CP, self.CP_SP, self.params)
# Dynamic Experimental Control
self.dynamic_experimental_control = self.params.get_bool("DynamicExperimentalControl")
openpilot_enabled_toggle = self.params.get_bool("OpenpilotEnabledToggle")
controller_available = self.CI.CC is not None and openpilot_enabled_toggle and not self.CP.dashcamOnly
self.CP.passive = not controller_available or self.CP.dashcamOnly
@@ -178,11 +181,14 @@ class Car:
self.v_cruise_helper = VCruiseHelper(self.CP, self.CP_SP)
self.is_metric = self.params.get_bool("IsMetric")
self.initial_cruise_speed = self.params.get("InitialCruiseSpeedKph", return_default=True)
self.experimental_mode = self.params.get_bool("ExperimentalMode")
# card is driven by can recv, expected at 100Hz
self.rk = Ratekeeper(100, print_delay_threshold=None)
# log fingerprint in sentry
sunnypilot_interfaces.log_fingerprint(self.CP)
def state_update(self) -> tuple[car.CarState, custom.CarStateSP, structs.RadarDataT | None]:
"""carState update loop, driven by can"""
@@ -211,7 +217,7 @@ class Car:
self.v_cruise_helper.update_v_cruise(CS, self.sm['carControl'].enabled, self.is_metric)
if self.sm['carControl'].enabled and not self.CC_prev.enabled:
# Use CarState w/ buttons from the step selfdrived enables on
self.v_cruise_helper.initialize_v_cruise(self.CS_prev, self.initial_cruise_speed)
self.v_cruise_helper.initialize_v_cruise(self.CS_prev, self.experimental_mode, self.dynamic_experimental_control)
# TODO: mirror the carState.cruiseState struct?
CS.vCruise = float(self.v_cruise_helper.v_cruise_kph)
@@ -296,9 +302,10 @@ class Car:
def params_thread(self, evt):
while not evt.is_set():
self.is_metric = self.params.get_bool("IsMetric")
self.initial_cruise_speed = self.params.get("InitialCruiseSpeedKph", return_default=True)
self.experimental_mode = self.params.get_bool("ExperimentalMode") and self.CP.openpilotLongitudinalControl
# sunnypilot
self.dynamic_experimental_control = self.params.get_bool("DynamicExperimentalControl")
self.v_cruise_helper.read_custom_set_speed_params()
time.sleep(0.1)
+6 -2
View File
@@ -13,6 +13,7 @@ V_CRUISE_MIN = 8
V_CRUISE_MAX = 145
V_CRUISE_UNSET = 255
V_CRUISE_INITIAL = 40
V_CRUISE_INITIAL_EXPERIMENTAL_MODE = 105
IMPERIAL_INCREMENT = round(CV.MPH_TO_KPH, 1) # round here to avoid rounding errors incrementing set speed
ButtonEvent = car.CarState.ButtonEvent
@@ -137,14 +138,17 @@ class VCruiseHelper(VCruiseHelperSP):
self.button_timers[b.type.raw] = 1 if b.pressed else 0
self.button_change_states[b.type.raw] = {"standstill": CS.cruiseState.standstill, "enabled": enabled}
def initialize_v_cruise(self, CS, initial_speed: int) -> None:
def initialize_v_cruise(self, CS, experimental_mode: bool, dynamic_experimental_control: bool) -> None:
# initializing is handled by the PCM
if self.CP.pcmCruise:
return
initial_experimental_mode = experimental_mode and not dynamic_experimental_control
initial = V_CRUISE_INITIAL_EXPERIMENTAL_MODE if initial_experimental_mode else V_CRUISE_INITIAL
if any(b.type in (ButtonType.accelCruise, ButtonType.resumeCruise) for b in CS.buttonEvents) and self.v_cruise_initialized:
self.v_cruise_kph = self.v_cruise_kph_last
else:
self.v_cruise_kph = int(round(np.clip(max(CS.vEgo * CV.MS_TO_KPH, initial_speed), V_CRUISE_INITIAL, V_CRUISE_MAX)))
self.v_cruise_kph = int(round(np.clip(CS.vEgo * CV.MS_TO_KPH, initial, V_CRUISE_MAX)))
self.v_cruise_cluster_kph = self.v_cruise_kph
@@ -14,7 +14,7 @@ ButtonEvent = car.CarState.ButtonEvent
ButtonType = car.CarState.ButtonEvent.Type
def run_cruise_simulation(cruise, personality, t_end=20.):
def run_cruise_simulation(cruise, e2e, personality, t_end=20.):
man = Maneuver(
'',
duration=t_end,
@@ -24,6 +24,7 @@ def run_cruise_simulation(cruise, personality, t_end=20.):
cruise_values=[cruise],
prob_lead_values=[0.0],
breakpoints=[0.],
e2e=e2e,
personality=personality,
)
valid, output = man.evaluate()
@@ -31,7 +32,8 @@ def run_cruise_simulation(cruise, personality, t_end=20.):
return output[-1, 3]
@parameterized_class(("personality", "speed"), itertools.product(
@parameterized_class(("e2e", "personality", "speed"), itertools.product(
[True, False], # e2e
log.LongitudinalPersonality.schema.enumerants, # personality
[5,35])) # speed
class TestCruiseSpeed(OpenpilotTestCase):
@@ -39,7 +41,7 @@ class TestCruiseSpeed(OpenpilotTestCase):
print(f'Testing {self.speed} m/s')
cruise_speed = float(self.speed)
simulation_steady_state = run_cruise_simulation(cruise_speed, self.personality)
simulation_steady_state = run_cruise_simulation(cruise_speed, self.e2e, self.personality)
self.assertAlmostEqual(simulation_steady_state, cruise_speed, delta=.01, msg=f'Did not reach {self.speed} m/s')
@@ -57,16 +59,16 @@ class TestVCruiseHelper(OpenpilotTestCase):
for _ in range(2):
self.v_cruise_helper.update_v_cruise(car.CarState(cruiseState={"available": False}), enabled=False, is_metric=False)
def enable(self, v_ego):
def enable(self, v_ego, experimental_mode, dynamic_experimental_control):
# Simulates user pressing set with a current speed
self.v_cruise_helper.initialize_v_cruise(car.CarState(vEgo=v_ego), V_CRUISE_INITIAL)
self.v_cruise_helper.initialize_v_cruise(car.CarState(vEgo=v_ego), experimental_mode, dynamic_experimental_control)
def test_adjust_speed(self):
"""
Asserts speed changes on falling edges of buttons.
"""
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS)
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
for btn in (ButtonType.accelCruise, ButtonType.decelCruise):
for pressed in (True, False):
@@ -90,7 +92,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
CS.buttonEvents = [ButtonEvent(type=ButtonType.decelCruise, pressed=pressed)]
self.v_cruise_helper.update_v_cruise(CS, enabled=enabled, is_metric=False)
if pressed:
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS)
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
# Expected diff on enabling. Speed should not change on falling edge of pressed
assert (not pressed) == (self.v_cruise_helper.v_cruise_kph == self.v_cruise_helper.v_cruise_kph_last)
@@ -100,7 +102,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
Asserts we don't increment set speed if user presses resume/accel to exit cruise standstill.
"""
self.enable(0)
self.enable(0, False, False)
for standstill in (True, False):
for pressed in (True, False):
@@ -120,7 +122,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
for v_ego in np.linspace(0, 100, 101):
self.reset_cruise_speed_state()
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS)
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
# first decrement speed, then perform gas pressed logic
expected_v_cruise_kph = self.v_cruise_helper.v_cruise_kph - IMPERIAL_INCREMENT
@@ -141,10 +143,12 @@ class TestVCruiseHelper(OpenpilotTestCase):
Asserts allowed cruise speeds on enabling with SET.
"""
for v_ego in np.linspace(0, 100, 101):
self.reset_cruise_speed_state()
assert not self.v_cruise_helper.v_cruise_initialized
for experimental_mode in (True, False):
for dynamic_experimental_control in (True, False):
for v_ego in np.linspace(0, 100, 101):
self.reset_cruise_speed_state()
assert not self.v_cruise_helper.v_cruise_initialized
self.enable(float(v_ego))
assert V_CRUISE_INITIAL <= self.v_cruise_helper.v_cruise_kph <= V_CRUISE_MAX
assert self.v_cruise_helper.v_cruise_initialized
self.enable(float(v_ego), experimental_mode, dynamic_experimental_control)
assert V_CRUISE_INITIAL <= self.v_cruise_helper.v_cruise_kph <= V_CRUISE_MAX
assert self.v_cruise_helper.v_cruise_initialized

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