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carnival-2025
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| db32fbea20 |
@@ -1,3 +0,0 @@
|
||||
.Xauthority
|
||||
.env
|
||||
.host/
|
||||
@@ -1,18 +0,0 @@
|
||||
FROM ghcr.io/commaai/openpilot-base:latest
|
||||
|
||||
RUN apt update && apt install -y vim net-tools usbutils htop ripgrep tmux wget mesa-utils xvfb libxtst6 libxv1 libglu1-mesa gdb bash-completion
|
||||
RUN python3 -m ensurepip --upgrade
|
||||
RUN pip3 install ipython jupyter jupyterlab
|
||||
|
||||
RUN cd /tmp && \
|
||||
ARCH=$(arch | sed s/aarch64/arm64/ | sed s/x86_64/amd64/) && \
|
||||
curl -L -o virtualgl.deb "https://github.com/VirtualGL/virtualgl/releases/download/3.1.1/virtualgl_3.1.1_$ARCH.deb" && \
|
||||
dpkg -i virtualgl.deb
|
||||
|
||||
RUN usermod -aG video batman
|
||||
|
||||
USER batman
|
||||
|
||||
RUN cd $HOME && \
|
||||
curl -O https://raw.githubusercontent.com/commaai/agnos-builder/master/userspace/home/.tmux.conf && \
|
||||
curl -O https://raw.githubusercontent.com/commaai/agnos-builder/master/userspace/home/.vimrc
|
||||
@@ -1,38 +0,0 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
TARGET_USER=batman
|
||||
source .devcontainer/.host/.env
|
||||
|
||||
# override display flag for mac hosts
|
||||
if [[ $HOST_OS == darwin ]]; then
|
||||
echo "Setting up DISPLAY override for macOS..."
|
||||
cat <<EOF >> /home/$TARGET_USER/.bashrc
|
||||
source .devcontainer/.host/.env
|
||||
if [ -n "\$HOST_DISPLAY" ]; then
|
||||
DISPLAY_NUM=\$(echo "\$HOST_DISPLAY" | awk -F: '{print \$NF}')
|
||||
export DISPLAY=host.docker.internal:\$DISPLAY_NUM
|
||||
fi
|
||||
EOF
|
||||
fi
|
||||
|
||||
# setup virtualgl for mac hosts
|
||||
if [[ $HOST_OS == darwin ]]; then
|
||||
echo "Setting up virtualgl for macOS..."
|
||||
cat <<EOF >> /home/$TARGET_USER/.bashrc
|
||||
if [ -n "\$HOST_DISPLAY" ]; then
|
||||
export VGL_PORT=10000
|
||||
export VGL_CLIENT=host.docker.internal
|
||||
export VGL_COMPRESS=rgb
|
||||
export VGL_DISPLAY=:99
|
||||
export VGL_FPS=60
|
||||
# prevent vglrun from running exec
|
||||
alias exec=:; source vglrun :; unalias exec
|
||||
fi
|
||||
EOF
|
||||
fi
|
||||
|
||||
# These lines are temporary, to remain backwards compatible with old devcontainers
|
||||
# that were running as root and therefore had their caches written as root
|
||||
sudo chown -R $TARGET_USER: /tmp/scons_cache
|
||||
sudo chown -R $TARGET_USER: /tmp/comma_download_cache
|
||||
sudo chown -R $TARGET_USER: /home/batman/.comma
|
||||
@@ -1,15 +0,0 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
source .devcontainer/.host/.env
|
||||
|
||||
# setup safe directories for submodules
|
||||
SUBMODULE_DIRS=$(git config --file .gitmodules --get-regexp path | awk '{ print $2 }')
|
||||
for DIR in $SUBMODULE_DIRS; do
|
||||
git config --global --add safe.directory "$PWD/$DIR"
|
||||
done
|
||||
|
||||
# virtual display for virtualgl
|
||||
if [[ "$HOST_OS" == "darwin" ]] && [[ -n "$HOST_DISPLAY" ]]; then
|
||||
echo "Starting virtual display at :99 ..."
|
||||
tmux new-session -d -s fakedisplay Xvfb :99 -screen 0 1920x1080x24
|
||||
fi
|
||||
@@ -1,53 +0,0 @@
|
||||
{
|
||||
"name": "openpilot devcontainer",
|
||||
"build": {
|
||||
"dockerfile": "Dockerfile"
|
||||
},
|
||||
"postCreateCommand": ".devcontainer/container_post_create.sh",
|
||||
"postStartCommand": ".devcontainer/container_post_start.sh",
|
||||
"initializeCommand": [".devcontainer/host_setup"],
|
||||
"privileged": true,
|
||||
"containerEnv": {
|
||||
"DISPLAY": "${localEnv:DISPLAY}",
|
||||
"PYTHONPATH": "${containerWorkspaceFolder}",
|
||||
"TERM": "xterm-256color",
|
||||
"force_color_prompt": "1"
|
||||
},
|
||||
"runArgs": [
|
||||
"--volume=/dev:/dev",
|
||||
"--volume=/tmp/.X11-unix:/tmp/.X11-unix",
|
||||
"--volume=${localWorkspaceFolder}/.devcontainer/.host/.Xauthority:/home/batman/.Xauthority",
|
||||
"--volume=${localEnv:HOME}/.comma:/home/batman/.comma",
|
||||
"--volume=${localEnv:HOME}/.azure:/home/batman/.azure",
|
||||
"--volume=/tmp/comma_download_cache:/tmp/comma_download_cache",
|
||||
"--shm-size=1G",
|
||||
"--add-host=host.docker.internal:host-gateway", // required to use host.docker.internal on linux
|
||||
"--publish=0.0.0.0:8070-8079:8070-8079" // body ZMQ services
|
||||
],
|
||||
"features": {
|
||||
"ghcr.io/devcontainers/features/common-utils:2": {
|
||||
"installZsh": false,
|
||||
"installOhMyZsh": false,
|
||||
"upgradePackages": false,
|
||||
"username": "batman"
|
||||
},
|
||||
"ghcr.io/devcontainers-contrib/features/gh-cli:1": {},
|
||||
"ghcr.io/devcontainers/features/azure-cli:1": {}
|
||||
},
|
||||
"containerUser": "batman",
|
||||
"remoteUser": "batman",
|
||||
"customizations": {
|
||||
"vscode": {
|
||||
"extensions": [
|
||||
"ms-python.python",
|
||||
"ms-vscode.cpptools",
|
||||
"ms-toolsai.jupyter",
|
||||
"guyskk.language-cython",
|
||||
"lharri73.dbc"
|
||||
]
|
||||
}
|
||||
},
|
||||
"mounts": [
|
||||
"type=volume,source=scons_cache,target=/tmp/scons_cache"
|
||||
]
|
||||
}
|
||||
@@ -1,47 +0,0 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
# pull base image
|
||||
if [[ -z $USE_LOCAL_IMAGE ]]; then
|
||||
echo "Updating openpilot_base image if needed..."
|
||||
docker pull ghcr.io/commaai/openpilot-base:latest
|
||||
fi
|
||||
|
||||
# setup .host dir
|
||||
mkdir -p .devcontainer/.host
|
||||
|
||||
# setup links to Xauthority
|
||||
XAUTHORITY_LINK=".devcontainer/.host/.Xauthority"
|
||||
rm -f $XAUTHORITY_LINK
|
||||
if [[ -z $XAUTHORITY ]]; then
|
||||
echo "XAUTHORITY not set. Fallback to ~/.Xauthority ..."
|
||||
if ! [[ -f $HOME/.Xauthority ]]; then
|
||||
echo "~/.XAuthority file does not exist. GUI tools may not work properly."
|
||||
touch $XAUTHORITY_LINK # dummy file to satisfy container volume mount
|
||||
else
|
||||
ln -sf $HOME/.Xauthority $XAUTHORITY_LINK
|
||||
fi
|
||||
else
|
||||
ln -sf $XAUTHORITY $XAUTHORITY_LINK
|
||||
fi
|
||||
|
||||
# setup host env file
|
||||
HOST_INFO_FILE=".devcontainer/.host/.env"
|
||||
SYSTEM=$(uname -s | tr '[:upper:]' '[:lower:]')
|
||||
echo "HOST_OS=\"$SYSTEM\"" > $HOST_INFO_FILE
|
||||
echo "HOST_DISPLAY=\"$DISPLAY\"" >> $HOST_INFO_FILE
|
||||
|
||||
# run virtualgl if macos
|
||||
if [[ $SYSTEM == "darwin" ]]; then
|
||||
echo
|
||||
if [[ -f /opt/VirtualGL/bin/vglclient ]]; then
|
||||
echo "Starting VirtualGL client at port 10000..."
|
||||
VGL_LOG_FILE=".devcontainer/.host/.vgl/vglclient.log"
|
||||
mkdir -p "$(dirname $VGL_LOG_FILE)"
|
||||
/opt/VirtualGL/bin/vglclient -l "$VGL_LOG_FILE" -display "$DISPLAY" -port 10000 -detach
|
||||
else
|
||||
echo "VirtualGL not found. GUI tools may not work properly. Some GUI tools require OpenGL to work properly. To use them with XQuartz on mac, VirtualGL needs to be installed. To install it run:"
|
||||
echo
|
||||
echo " brew install --cask virtualgl"
|
||||
echo
|
||||
fi
|
||||
fi
|
||||
@@ -1,10 +0,0 @@
|
||||
:: pull base image
|
||||
IF NOT DEFINED USE_LOCAL_IMAGE ^
|
||||
echo "Updating openpilot_base image if needed..." && ^
|
||||
docker pull ghcr.io/commaai/openpilot-base:latest
|
||||
|
||||
:: setup .host dir
|
||||
mkdir .devcontainer\.host
|
||||
|
||||
:: setup host env file
|
||||
echo "" > .devcontainer\.host\.env
|
||||
@@ -8,7 +8,7 @@ assignees: ''
|
||||
|
||||
**Checklist**
|
||||
|
||||
- [ ] added entry to CAR in selfdrive/car/*/values.py and ran `selfdrive/opcar/docs.py` to generate new docs
|
||||
- [ ] added entry to CAR in selfdrive/car/*/values.py and ran `selfdrive/car/docs.py` to generate new docs
|
||||
- [ ] test route added to [routes.py](https://github.com/commaai/openpilot/blob/master/selfdrive/car/tests/routes.py)
|
||||
- [ ] route with openpilot:
|
||||
- [ ] route with stock system:
|
||||
|
||||
@@ -44,7 +44,7 @@ Explain how you tested this bug fix.
|
||||
|
||||
**Checklist**
|
||||
|
||||
- [ ] added entry to CAR in selfdrive/car/*/values.py and ran `selfdrive/opcar/docs.py` to generate new docs
|
||||
- [ ] added entry to CAR in selfdrive/car/*/values.py and ran `selfdrive/car/docs.py` to generate new docs
|
||||
- [ ] test route added to [routes.py](https://github.com/commaai/openpilot/blob/master/selfdrive/car/tests/routes.py)
|
||||
- [ ] route with openpilot:
|
||||
- [ ] route with stock system:
|
||||
|
||||
@@ -14,17 +14,25 @@ inputs:
|
||||
description: 'whether to save the cache'
|
||||
default: 'false'
|
||||
required: false
|
||||
outputs:
|
||||
cache-hit:
|
||||
description: 'cache hit occurred'
|
||||
value: ${{ (contains(runner.name, 'nsc') && steps.ns-cache.outputs.cache-hit) ||
|
||||
(!contains(runner.name, 'nsc') && inputs.save != 'false' && steps.gha-cache.outputs.cache-hit) ||
|
||||
(!contains(runner.name, 'nsc') && inputs.save == 'false' && steps.gha-cache-ro.outputs.cache-hit) }}
|
||||
|
||||
runs:
|
||||
using: "composite"
|
||||
steps:
|
||||
- name: setup namespace cache
|
||||
id: ns-cache
|
||||
if: ${{ contains(runner.name, 'nsc') }}
|
||||
uses: namespacelabs/nscloud-cache-action@v1
|
||||
with:
|
||||
path: ${{ inputs.path }}
|
||||
|
||||
- name: setup github cache
|
||||
id: gha-cache
|
||||
if: ${{ !contains(runner.name, 'nsc') && inputs.save != 'false' }}
|
||||
uses: 'actions/cache@v4'
|
||||
with:
|
||||
@@ -33,6 +41,7 @@ runs:
|
||||
restore-keys: ${{ inputs.restore-keys }}
|
||||
|
||||
- name: setup github cache
|
||||
id: gha-cache-ro
|
||||
if: ${{ !contains(runner.name, 'nsc') && inputs.save == 'false' }}
|
||||
uses: 'actions/cache/restore@v4'
|
||||
with:
|
||||
|
||||
@@ -15,7 +15,3 @@ jobs:
|
||||
uses: commaai/openpilot/.github/workflows/selfdrive_tests.yaml@master
|
||||
with:
|
||||
run_number: ${{ inputs.run_number }}
|
||||
tools_tests:
|
||||
uses: commaai/openpilot/.github/workflows/tools_tests.yaml@master
|
||||
with:
|
||||
run_number: ${{ inputs.run_number }}
|
||||
|
||||
@@ -18,9 +18,10 @@ concurrency:
|
||||
jobs:
|
||||
docs:
|
||||
name: build docs
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 1
|
||||
runs-on: ubuntu-24.04
|
||||
steps:
|
||||
- uses: commaai/timeout@v1
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
|
||||
@@ -28,7 +28,7 @@ jobs:
|
||||
git add .
|
||||
- name: update car docs
|
||||
run: |
|
||||
scons -j$(nproc) --minimal opendbc
|
||||
scons -j$(nproc) --minimal opendbc_repo
|
||||
PYTHONPATH=. python selfdrive/car/docs.py
|
||||
git add docs/CARS.md
|
||||
- name: Create Pull Request
|
||||
|
||||
@@ -32,9 +32,9 @@ env:
|
||||
jobs:
|
||||
build_release:
|
||||
name: build release
|
||||
runs-on: ${{ ((github.repository == 'commaai/openpilot') &&
|
||||
((github.event_name != 'pull_request') ||
|
||||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-latest' }}
|
||||
runs-on:
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
|
||||
env:
|
||||
STRIPPED_DIR: /tmp/releasepilot
|
||||
steps:
|
||||
@@ -75,15 +75,9 @@ jobs:
|
||||
${{ env.RUN }} "scripts/lint/lint.sh --skip check_added_large_files"
|
||||
|
||||
build:
|
||||
strategy:
|
||||
matrix:
|
||||
arch: ${{ fromJson(
|
||||
((github.repository == 'commaai/openpilot') &&
|
||||
((github.event_name != 'pull_request') ||
|
||||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && '["x86_64", "aarch64"]' || '["x86_64"]' ) }}
|
||||
runs-on: ${{ ((matrix.arch == 'aarch64') && 'namespace-profile-arm64-2x8') ||
|
||||
((matrix.arch == 'x86_64') && ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16') ||
|
||||
'ubuntu-latest'}}
|
||||
runs-on:
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
@@ -92,17 +86,14 @@ jobs:
|
||||
if: github.ref == 'refs/heads/master' && github.event_name != 'pull_request' && github.repository == 'commaai/openpilot'
|
||||
run: |
|
||||
echo "PUSH_IMAGE=true" >> "$GITHUB_ENV"
|
||||
echo "TARGET_ARCHITECTURE=${{ matrix.arch }}" >> "$GITHUB_ENV"
|
||||
$DOCKER_LOGIN
|
||||
- uses: ./.github/workflows/setup-with-retry
|
||||
with:
|
||||
docker_hub_pat: ${{ secrets.DOCKER_HUB_PAT }}
|
||||
- uses: ./.github/workflows/compile-openpilot
|
||||
timeout-minutes: ${{ ((steps.restore-scons-cache.outputs.cache-hit == 'true') && 15 || 30) }} # allow more time when we missed the scons cache
|
||||
timeout-minutes: 30
|
||||
|
||||
build_mac:
|
||||
name: build macOS
|
||||
runs-on: namespace-profile-macos-8x14
|
||||
runs-on: ${{ github.repository == 'commaai/openpilot' && 'namespace-profile-macos-8x14' || 'macos-latest' }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
@@ -125,28 +116,11 @@ jobs:
|
||||
- name: Building openpilot
|
||||
run: . .venv/bin/activate && scons -j$(nproc)
|
||||
|
||||
docker_push_multiarch:
|
||||
name: docker push multiarch tag
|
||||
runs-on: ubuntu-latest
|
||||
if: github.ref == 'refs/heads/master' && github.event_name != 'pull_request' && github.repository == 'commaai/openpilot'
|
||||
needs: [build]
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: false
|
||||
- name: Setup docker
|
||||
run: |
|
||||
$DOCKER_LOGIN
|
||||
- name: Merge x64 and arm64 tags
|
||||
run: |
|
||||
export PUSH_IMAGE=true
|
||||
scripts/retry.sh selfdrive/test/docker_tag_multiarch.sh base x86_64 aarch64
|
||||
|
||||
static_analysis:
|
||||
name: static analysis
|
||||
runs-on: ${{ ((github.repository == 'commaai/openpilot') &&
|
||||
((github.event_name != 'pull_request') ||
|
||||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
runs-on:
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
|
||||
env:
|
||||
PYTHONWARNINGS: default
|
||||
steps:
|
||||
@@ -160,24 +134,16 @@ jobs:
|
||||
|
||||
unit_tests:
|
||||
name: unit tests
|
||||
runs-on: ${{ ((github.repository == 'commaai/openpilot') &&
|
||||
((github.event_name != 'pull_request') ||
|
||||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-latest' }}
|
||||
runs-on:
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- uses: ./.github/workflows/setup-with-retry
|
||||
with:
|
||||
docker_hub_pat: ${{ secrets.DOCKER_HUB_PAT }}
|
||||
- name: Build openpilot
|
||||
timeout-minutes: ${{ ((steps.restore-scons-cache.outputs.cache-hit == 'true') && 10 || 30) }} # allow more time when we missed the scons cache
|
||||
run: ${{ env.RUN }} "scons -j$(nproc)"
|
||||
- name: Setup cache
|
||||
uses: ./.github/workflows/auto-cache
|
||||
with:
|
||||
path: .ci_cache/comma_download_cache
|
||||
key: unit_tests_${{ hashFiles('.github/workflows/selfdrive_tests.yaml') }}
|
||||
- name: Run unit tests
|
||||
timeout-minutes: ${{ contains(runner.name, 'nsc') && 1 || 20 }}
|
||||
run: |
|
||||
@@ -195,27 +161,25 @@ jobs:
|
||||
|
||||
process_replay:
|
||||
name: process replay
|
||||
runs-on: ${{ ((github.repository == 'commaai/openpilot') &&
|
||||
((github.event_name != 'pull_request') ||
|
||||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-latest' }}
|
||||
runs-on:
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- uses: ./.github/workflows/setup-with-retry
|
||||
with:
|
||||
docker_hub_pat: ${{ secrets.DOCKER_HUB_PAT }}
|
||||
- name: Cache test routes
|
||||
id: dependency-cache
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: .ci_cache/comma_download_cache
|
||||
key: proc-replay-${{ hashFiles('.github/workflows/selfdrive_tests.yaml', 'selfdrive/test/process_replay/ref_commit', 'selfdrive/test/process_replay/test_regen.py') }}
|
||||
key: proc-replay-${{ hashFiles('selfdrive/test/process_replay/ref_commit', 'selfdrive/test/process_replay/test_processes.py') }}
|
||||
- name: Build openpilot
|
||||
run: |
|
||||
${{ env.RUN }} "scons -j$(nproc)"
|
||||
- name: Run replay
|
||||
timeout-minutes: ${{ contains(runner.name, 'nsc') && 1 || 20 }}
|
||||
timeout-minutes: ${{ contains(runner.name, 'nsc') && (steps.dependency-cache.outputs.cache-hit == 'true') && 1 || 20 }}
|
||||
run: |
|
||||
${{ env.RUN }} "coverage run selfdrive/test/process_replay/test_processes.py -j$(nproc) && \
|
||||
chmod -R 777 /tmp/comma_download_cache && \
|
||||
@@ -250,9 +214,9 @@ jobs:
|
||||
|
||||
test_cars:
|
||||
name: cars
|
||||
runs-on: ${{ ((github.repository == 'commaai/openpilot') &&
|
||||
((github.event_name != 'pull_request') ||
|
||||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-latest' }}
|
||||
runs-on:
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
@@ -263,17 +227,17 @@ jobs:
|
||||
submodules: true
|
||||
- uses: ./.github/workflows/setup-with-retry
|
||||
- name: Cache test routes
|
||||
id: dependency-cache
|
||||
uses: ./.github/workflows/auto-cache
|
||||
id: routes-cache
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: .ci_cache/comma_download_cache
|
||||
key: car_models-${{ hashFiles('selfdrive/car/tests/test_models.py', 'selfdrive/car/tests/routes.py') }}-${{ matrix.job }}
|
||||
key: car_models-${{ hashFiles('selfdrive/car/tests/test_models.py', 'opendbc/car/tests/routes.py') }}-${{ matrix.job }}
|
||||
- name: Build openpilot
|
||||
run: ${{ env.RUN }} "scons -j$(nproc)"
|
||||
- name: Test car models
|
||||
timeout-minutes: ${{ contains(runner.name, 'nsc') && 1 || 20 }}
|
||||
timeout-minutes: ${{ contains(runner.name, 'nsc') && (steps.routes-cache.outputs.cache-hit == 'true') && 1 || 20 }}
|
||||
run: |
|
||||
${{ env.RUN }} "FILEREADER_CACHE=1 MAX_EXAMPLES=1 $PYTEST selfdrive/car/tests/test_models.py && \
|
||||
${{ env.RUN }} "MAX_EXAMPLES=1 $PYTEST selfdrive/car/tests/test_models.py && \
|
||||
chmod -R 777 /tmp/comma_download_cache"
|
||||
env:
|
||||
NUM_JOBS: 4
|
||||
@@ -342,9 +306,10 @@ jobs:
|
||||
|
||||
simulator_driving:
|
||||
name: simulator driving
|
||||
runs-on: ${{ ((github.repository == 'commaai/openpilot') &&
|
||||
((github.event_name != 'pull_request') ||
|
||||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
runs-on:
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
|
||||
if: (github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
@@ -363,9 +328,9 @@ jobs:
|
||||
create_ui_report:
|
||||
# This job name needs to be the same as UI_JOB_NAME in ui_preview.yaml
|
||||
name: Create UI Report
|
||||
runs-on: ${{ ((github.repository == 'commaai/openpilot') &&
|
||||
((github.event_name != 'pull_request') ||
|
||||
(github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
runs-on:
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
|
||||
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
|
||||
@@ -17,7 +17,6 @@ runs:
|
||||
uses: ./.github/workflows/setup
|
||||
continue-on-error: true
|
||||
with:
|
||||
docker_hub_pat: ${{ inputs.docker_hub_pat }}
|
||||
is_retried: true
|
||||
- if: steps.setup1.outcome == 'failure'
|
||||
shell: bash
|
||||
@@ -27,7 +26,6 @@ runs:
|
||||
uses: ./.github/workflows/setup
|
||||
continue-on-error: true
|
||||
with:
|
||||
docker_hub_pat: ${{ inputs.docker_hub_pat }}
|
||||
is_retried: true
|
||||
- if: steps.setup2.outcome == 'failure'
|
||||
shell: bash
|
||||
@@ -36,5 +34,4 @@ runs:
|
||||
if: steps.setup2.outcome == 'failure'
|
||||
uses: ./.github/workflows/setup
|
||||
with:
|
||||
docker_hub_pat: ${{ inputs.docker_hub_pat }}
|
||||
is_retried: true
|
||||
|
||||
@@ -1,10 +1,6 @@
|
||||
name: 'openpilot env setup'
|
||||
|
||||
inputs:
|
||||
docker_hub_pat:
|
||||
description: 'Auth token for Docker Hub, required for BuildJet jobs'
|
||||
required: true
|
||||
default: ''
|
||||
is_retried:
|
||||
description: 'A mock param that asserts that we use the setup-with-retry instead of this action directly'
|
||||
required: false
|
||||
@@ -24,11 +20,9 @@ runs:
|
||||
name: No retries!
|
||||
run: |
|
||||
if [ "${{ github.run_attempt }}" -gt 1 ]; then
|
||||
echo -e "\033[31m"
|
||||
echo "##################################################"
|
||||
echo " Retries not allowed! Fix the flaky test! "
|
||||
echo "##################################################"
|
||||
echo -e "\033[0m"
|
||||
echo -e "\033[0;31m##################################################"
|
||||
echo -e "\033[0;31m Retries not allowed! Fix the flaky test! "
|
||||
echo -e "\033[0;31m##################################################\033[0m"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
@@ -36,19 +30,6 @@ runs:
|
||||
- shell: bash
|
||||
run: git lfs pull
|
||||
|
||||
# on BuildJet runners, must be logged into DockerHub to avoid rate limiting
|
||||
# https://buildjet.com/for-github-actions/docs/guides/docker
|
||||
- shell: bash
|
||||
if: ${{ contains(runner.name, 'buildjet') && inputs.docker_hub_pat == '' }}
|
||||
run: |
|
||||
echo "Need to set the Docker Hub PAT secret as an input to this action"
|
||||
exit 1
|
||||
- name: Login to Docker Hub
|
||||
if: contains(runner.name, 'buildjet')
|
||||
shell: bash
|
||||
run: |
|
||||
docker login -u adeebshihadeh -p ${{ inputs.docker_hub_pat }}
|
||||
|
||||
# build cache
|
||||
- id: date
|
||||
shell: bash
|
||||
|
||||
@@ -1,54 +0,0 @@
|
||||
name: tools
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- master
|
||||
pull_request:
|
||||
workflow_call:
|
||||
inputs:
|
||||
run_number:
|
||||
default: '1'
|
||||
required: true
|
||||
type: string
|
||||
concurrency:
|
||||
group: tools-tests-ci-run-${{ inputs.run_number }}-${{ github.event_name == 'push' && github.ref == 'refs/heads/master' && github.run_id || github.head_ref || github.ref }}-${{ github.workflow }}-${{ github.event_name }}
|
||||
cancel-in-progress: true
|
||||
|
||||
env:
|
||||
BASE_IMAGE: openpilot-base
|
||||
DOCKER_LOGIN: docker login ghcr.io -u ${{ github.actor }} -p ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
BUILD: selfdrive/test/docker_build.sh base
|
||||
|
||||
RUN: docker run --shm-size 2G -v $GITHUB_WORKSPACE:/tmp/openpilot -w /tmp/openpilot -e FILEREADER_CACHE=1 -e PYTHONPATH=/tmp/openpilot -e NUM_JOBS -e JOB_ID -e GITHUB_ACTION -e GITHUB_REF -e GITHUB_HEAD_REF -e GITHUB_SHA -e GITHUB_REPOSITORY -e GITHUB_RUN_ID -v $GITHUB_WORKSPACE/.ci_cache/scons_cache:/tmp/scons_cache -v $GITHUB_WORKSPACE/.ci_cache/comma_download_cache:/tmp/comma_download_cache -v $GITHUB_WORKSPACE/.ci_cache/openpilot_cache:/tmp/openpilot_cache $BASE_IMAGE /bin/bash -c
|
||||
|
||||
|
||||
jobs:
|
||||
devcontainer:
|
||||
name: devcontainer
|
||||
runs-on: ubuntu-latest
|
||||
if: false # we can re-enable once this is faster
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- uses: ./.github/workflows/setup-with-retry
|
||||
- name: Use local image for testing devcontainer with latest base image
|
||||
run: |
|
||||
echo "USE_LOCAL_IMAGE=true" >> "$GITHUB_ENV"
|
||||
- name: Setup Dev Container CLI
|
||||
run: npm install -g @devcontainers/cli
|
||||
- name: Build dev container image
|
||||
run: ./scripts/retry.sh devcontainer build --workspace-folder .
|
||||
- name: Run dev container
|
||||
run: |
|
||||
mkdir -p /tmp/devcontainer_scons_cache/
|
||||
cp -r $GITHUB_WORKSPACE/.ci_cache/scons_cache/. /tmp/devcontainer_scons_cache/
|
||||
devcontainer up --workspace-folder .
|
||||
- name: Test environment
|
||||
run: |
|
||||
devcontainer exec --workspace-folder . scons -j$(nproc) cereal/ common/
|
||||
devcontainer exec --workspace-folder . pip3 install pip-install-test
|
||||
devcontainer exec --workspace-folder . touch /home/batman/.comma/auth.json
|
||||
devcontainer exec --workspace-folder . sudo touch /root/test.txt
|
||||
@@ -1,9 +1,9 @@
|
||||
FROM ghcr.io/commaai/openpilot-base:latest
|
||||
|
||||
ENV PYTHONUNBUFFERED 1
|
||||
ENV PYTHONUNBUFFERED=1
|
||||
|
||||
ENV OPENPILOT_PATH /home/batman/openpilot
|
||||
ENV PYTHONPATH ${OPENPILOT_PATH}:${PYTHONPATH}
|
||||
ENV OPENPILOT_PATH=/home/batman/openpilot
|
||||
ENV PYTHONPATH=${OPENPILOT_PATH}:${PYTHONPATH}
|
||||
|
||||
RUN mkdir -p ${OPENPILOT_PATH}
|
||||
WORKDIR ${OPENPILOT_PATH}
|
||||
|
||||
+12
-15
@@ -1,16 +1,16 @@
|
||||
FROM ubuntu:24.04
|
||||
|
||||
ENV PYTHONUNBUFFERED 1
|
||||
ENV PYTHONUNBUFFERED=1
|
||||
|
||||
ENV DEBIAN_FRONTEND=noninteractive
|
||||
RUN apt-get update && \
|
||||
apt-get install -y --no-install-recommends sudo tzdata locales ssh pulseaudio xvfb x11-xserver-utils gnome-screenshot && \
|
||||
apt-get install -y --no-install-recommends sudo tzdata locales ssh pulseaudio xvfb x11-xserver-utils gnome-screenshot python3-tk python3-dev && \
|
||||
rm -rf /var/lib/apt/lists/*
|
||||
|
||||
RUN sed -i -e 's/# en_US.UTF-8 UTF-8/en_US.UTF-8 UTF-8/' /etc/locale.gen && locale-gen
|
||||
ENV LANG en_US.UTF-8
|
||||
ENV LANGUAGE en_US:en
|
||||
ENV LC_ALL en_US.UTF-8
|
||||
ENV LANG=en_US.UTF-8
|
||||
ENV LANGUAGE=en_US:en
|
||||
ENV LC_ALL=en_US.UTF-8
|
||||
|
||||
COPY tools/install_ubuntu_dependencies.sh /tmp/tools/
|
||||
RUN /tmp/tools/install_ubuntu_dependencies.sh && \
|
||||
@@ -55,9 +55,9 @@ RUN mkdir -p /tmp/opencl-driver-intel && \
|
||||
cd / && \
|
||||
rm -rf /tmp/opencl-driver-intel
|
||||
|
||||
ENV NVIDIA_VISIBLE_DEVICES all
|
||||
ENV NVIDIA_DRIVER_CAPABILITIES graphics,utility,compute
|
||||
ENV QTWEBENGINE_DISABLE_SANDBOX 1
|
||||
ENV NVIDIA_VISIBLE_DEVICES=all
|
||||
ENV NVIDIA_DRIVER_CAPABILITIES=graphics,utility,compute
|
||||
ENV QTWEBENGINE_DISABLE_SANDBOX=1
|
||||
|
||||
RUN dbus-uuidgen > /etc/machine-id
|
||||
|
||||
@@ -68,17 +68,14 @@ RUN usermod -aG sudo $USER
|
||||
RUN echo '%sudo ALL=(ALL) NOPASSWD:ALL' >> /etc/sudoers
|
||||
USER $USER
|
||||
|
||||
COPY --chown=$USER pyproject.toml uv.lock /tmp/
|
||||
COPY --chown=$USER tools/install_python_dependencies.sh /tmp/tools/
|
||||
COPY --chown=$USER pyproject.toml uv.lock /home/$USER
|
||||
COPY --chown=$USER tools/install_python_dependencies.sh /home/$USER/tools/
|
||||
|
||||
ENV VIRTUAL_ENV=/home/$USER/.venv
|
||||
ENV PATH="$VIRTUAL_ENV/bin:$PATH"
|
||||
RUN cd /tmp && \
|
||||
RUN cd /home/$USER && \
|
||||
tools/install_python_dependencies.sh && \
|
||||
mkdir -p $VIRTUAL_ENV && \
|
||||
cp -r /tmp/.venv/* $VIRTUAL_ENV && \
|
||||
rm -rf /tmp/* && \
|
||||
rm -rf /home/$USER/.cache
|
||||
rm -rf tools/ pyproject.toml uv.lock .cache
|
||||
|
||||
USER root
|
||||
RUN sudo git config --global --add safe.directory /tmp/openpilot
|
||||
|
||||
Vendored
+13
-4
@@ -79,6 +79,10 @@ def deviceStage(String stageName, String deviceType, List extra_env, def steps)
|
||||
return
|
||||
}
|
||||
|
||||
if (isReplay()) {
|
||||
error("REPLAYING TESTS IS NOT ALLOWED. FIX THEM INSTEAD.")
|
||||
}
|
||||
|
||||
def extra = extra_env.collect { "export ${it}" }.join('\n');
|
||||
def branch = env.BRANCH_NAME ?: 'master';
|
||||
def gitDiff = sh returnStdout: true, script: 'curl -s -H "Authorization: Bearer ${GITHUB_COMMENTS_TOKEN}" https://api.github.com/repos/commaai/openpilot/compare/master...${GIT_BRANCH} | jq .files[].filename || echo "/"', label: 'Getting changes'
|
||||
@@ -123,6 +127,11 @@ def hasPathChanged(String gitDiff, List<String> paths) {
|
||||
return false
|
||||
}
|
||||
|
||||
def isReplay() {
|
||||
def replayClass = "org.jenkinsci.plugins.workflow.cps.replay.ReplayCause"
|
||||
return currentBuild.rawBuild.getCauses().any{ cause -> cause.toString().contains(replayClass) }
|
||||
}
|
||||
|
||||
def setupCredentials() {
|
||||
withCredentials([
|
||||
string(credentialsId: 'azure_token', variable: 'AZURE_TOKEN'),
|
||||
@@ -207,8 +216,8 @@ node {
|
||||
step("build", "cd system/manager && ./build.py"),
|
||||
step("test pandad", "pytest selfdrive/pandad/tests/test_pandad.py", [diffPaths: ["panda", "selfdrive/pandad/"]]),
|
||||
step("test power draw", "pytest -s system/hardware/tici/tests/test_power_draw.py"),
|
||||
step("test encoder", "LD_LIBRARY_PATH=/usr/local/lib pytest system/loggerd/tests/test_encoder.py"),
|
||||
step("test pigeond", "pytest system/ubloxd/tests/test_pigeond.py"),
|
||||
step("test encoder", "LD_LIBRARY_PATH=/usr/local/lib pytest system/loggerd/tests/test_encoder.py", [diffPaths: ["system/loggerd/"]]),
|
||||
step("test pigeond", "pytest system/ubloxd/tests/test_pigeond.py", [diffPaths: ["system/ubloxd/"]]),
|
||||
step("test manager", "pytest system/manager/test/test_manager.py"),
|
||||
])
|
||||
},
|
||||
@@ -243,7 +252,7 @@ node {
|
||||
'replay': {
|
||||
deviceStage("model-replay", "tici-replay", ["UNSAFE=1"], [
|
||||
step("build", "cd system/manager && ./build.py", [diffPaths: ["selfdrive/modeld/", "tinygrad_repo", "selfdrive/test/process_replay/model_replay.py"]]),
|
||||
step("model replay", "selfdrive/test/process_replay/model_replay.py", [diffPaths: ["selfdrive/modeld/"]]),
|
||||
step("model replay", "selfdrive/test/process_replay/model_replay.py", [diffPaths: ["selfdrive/modeld/", "tinygrad_repo", "selfdrive/test/process_replay/model_replay.py"]]),
|
||||
])
|
||||
},
|
||||
'tizi': {
|
||||
@@ -253,7 +262,7 @@ node {
|
||||
step("test pandad spi", "pytest selfdrive/pandad/tests/test_pandad_spi.py"),
|
||||
step("test pandad", "pytest selfdrive/pandad/tests/test_pandad.py", [diffPaths: ["panda", "selfdrive/pandad/"]]),
|
||||
step("test amp", "pytest system/hardware/tici/tests/test_amplifier.py"),
|
||||
step("test qcomgpsd", "pytest system/qcomgpsd/tests/test_qcomgpsd.py"),
|
||||
step("test qcomgpsd", "pytest system/qcomgpsd/tests/test_qcomgpsd.py", [diffPaths: ["system/qcomgpsd/"]]),
|
||||
])
|
||||
},
|
||||
|
||||
|
||||
@@ -38,7 +38,8 @@ Quick start: `bash <(curl -fsSL openpilot.comma.ai)`
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
To start using openpilot in a car
|
||||
|
||||
Using openpilot in a car
|
||||
------
|
||||
|
||||
To use openpilot in a car, you need four things:
|
||||
@@ -49,6 +50,14 @@ To use openpilot in a car, you need four things:
|
||||
|
||||
We have detailed instructions for [how to install the harness and device in a car](https://comma.ai/setup). Note that it's possible to run openpilot on [other hardware](https://blog.comma.ai/self-driving-car-for-free/), although it's not plug-and-play.
|
||||
|
||||
### Branches
|
||||
| branch | URL | description |
|
||||
|------------------|----------------------------------------|-------------------------------------------------------------------------------------|
|
||||
| `release3` | openpilot.comma.ai | This is openpilot's release branch. |
|
||||
| `release3-staging` | openpilot-test.comma.ai | This is the staging branch for releases. Use it to get new releases slightly early. |
|
||||
| `nightly` | openpilot-nightly.comma.ai | This is the bleeding edge development branch. Do not expect this to be stable. |
|
||||
| `nightly-dev` | installer.comma.ai/commaai/nightly-dev | Same as nightly, but includes experimental development features for some cars. |
|
||||
|
||||
To start developing openpilot
|
||||
------
|
||||
|
||||
|
||||
+2
-1
@@ -349,7 +349,7 @@ Export('common', 'gpucommon')
|
||||
env_swaglog = env.Clone()
|
||||
env_swaglog['CXXFLAGS'].append('-DSWAGLOG="\\"common/swaglog.h\\""')
|
||||
SConscript(['msgq_repo/SConscript'], exports={'env': env_swaglog})
|
||||
SConscript(['opendbc/can/SConscript'], exports={'env': env_swaglog})
|
||||
SConscript(['opendbc_repo/SConscript'], exports={'env': env_swaglog})
|
||||
|
||||
SConscript(['cereal/SConscript'])
|
||||
|
||||
@@ -366,6 +366,7 @@ SConscript(['rednose/SConscript'])
|
||||
|
||||
# Build system services
|
||||
SConscript([
|
||||
'system/ui/SConscript',
|
||||
'system/proclogd/SConscript',
|
||||
'system/ubloxd/SConscript',
|
||||
'system/loggerd/SConscript',
|
||||
|
||||
@@ -486,6 +486,9 @@ struct DeviceState @0xa4d8b5af2aa492eb {
|
||||
nvmeTempC @35 :List(Float32);
|
||||
modemTempC @36 :List(Float32);
|
||||
pmicTempC @39 :List(Float32);
|
||||
intakeTempC @46 :Float32;
|
||||
exhaustTempC @47 :Float32;
|
||||
caseTempC @48 :Float32;
|
||||
maxTempC @44 :Float32; # max of other temps, used to control fan
|
||||
thermalZones @38 :List(ThermalZone);
|
||||
thermalStatus @14 :ThermalStatus;
|
||||
@@ -2437,6 +2440,14 @@ struct Microphone {
|
||||
filteredSoundPressureWeightedDb @2 :Float32;
|
||||
}
|
||||
|
||||
struct Touch {
|
||||
sec @0 :Int64;
|
||||
usec @1 :Int64;
|
||||
type @2 :UInt8;
|
||||
code @3 :Int32;
|
||||
value @4 :Int32;
|
||||
}
|
||||
|
||||
struct Event {
|
||||
logMonoTime @0 :UInt64; # nanoseconds
|
||||
valid @67 :Bool = true;
|
||||
@@ -2517,6 +2528,9 @@ struct Event {
|
||||
logMessage @18 :Text;
|
||||
errorLogMessage @85 :Text;
|
||||
|
||||
# touch frame
|
||||
touch @135 :List(Touch);
|
||||
|
||||
# navigation
|
||||
navInstruction @82 :NavInstruction;
|
||||
navRoute @83 :NavRoute;
|
||||
|
||||
@@ -17,5 +17,5 @@ class TestServices:
|
||||
|
||||
def test_generated_header(self):
|
||||
with tempfile.NamedTemporaryFile(suffix=".h") as f:
|
||||
ret = os.system(f"python3 {services.__file__} > {f.name} && clang++ {f.name}")
|
||||
ret = os.system(f"python3 {services.__file__} > {f.name} && clang++ {f.name} -std=c++11")
|
||||
assert ret == 0, "generated services header is not valid C"
|
||||
|
||||
@@ -22,6 +22,7 @@ _services: dict[str, tuple] = {
|
||||
"temperatureSensor2": (True, 2., 200),
|
||||
"gpsNMEA": (True, 9.),
|
||||
"deviceState": (True, 2., 1),
|
||||
"touch": (True, 20., 1),
|
||||
"can": (True, 100., 2053), # decimation gives ~3 msgs in a full segment
|
||||
"controlsState": (True, 100., 10),
|
||||
"selfdriveState": (True, 100., 10),
|
||||
|
||||
@@ -112,7 +112,6 @@ std::unordered_map<std::string, uint32_t> keys = {
|
||||
{"DisablePowerDown", PERSISTENT},
|
||||
{"DisableUpdates", PERSISTENT},
|
||||
{"DisengageOnAccelerator", PERSISTENT},
|
||||
{"DmModelInitialized", CLEAR_ON_ONROAD_TRANSITION},
|
||||
{"DongleId", PERSISTENT},
|
||||
{"DoReboot", CLEAR_ON_MANAGER_START},
|
||||
{"DoShutdown", CLEAR_ON_MANAGER_START},
|
||||
|
||||
+1
-1
@@ -13,7 +13,7 @@ public:
|
||||
if (prefix.empty()) {
|
||||
prefix = util::random_string(15);
|
||||
}
|
||||
msgq_path = "/dev/shm/" + prefix;
|
||||
msgq_path = Path::shm_path() + "/" + prefix;
|
||||
bool ret = util::create_directories(msgq_path, 0777);
|
||||
assert(ret);
|
||||
setenv("OPENPILOT_PREFIX", prefix.c_str(), 1);
|
||||
|
||||
+1
-1
@@ -11,7 +11,7 @@ from openpilot.system.hardware.hw import DEFAULT_DOWNLOAD_CACHE_ROOT
|
||||
class OpenpilotPrefix:
|
||||
def __init__(self, prefix: str = None, clean_dirs_on_exit: bool = True, shared_download_cache: bool = False):
|
||||
self.prefix = prefix if prefix else str(uuid.uuid4().hex[0:15])
|
||||
self.msgq_path = os.path.join('/dev/shm', self.prefix)
|
||||
self.msgq_path = os.path.join(Paths.shm_path(), self.prefix)
|
||||
self.clean_dirs_on_exit = clean_dirs_on_exit
|
||||
self.shared_download_cache = shared_download_cache
|
||||
|
||||
|
||||
+6
-2
@@ -48,13 +48,13 @@ class Ratekeeper:
|
||||
def __init__(self, rate: float, print_delay_threshold: float | None = 0.0) -> None:
|
||||
"""Rate in Hz for ratekeeping. print_delay_threshold must be nonnegative."""
|
||||
self._interval = 1. / rate
|
||||
self._next_frame_time = time.monotonic() + self._interval
|
||||
self._print_delay_threshold = print_delay_threshold
|
||||
self._frame = 0
|
||||
self._remaining = 0.0
|
||||
self._process_name = getproctitle()
|
||||
self._dts = deque([self._interval], maxlen=100)
|
||||
self._last_monitor_time = time.monotonic()
|
||||
self._last_monitor_time = -1.
|
||||
self._next_frame_time = -1.
|
||||
|
||||
@property
|
||||
def frame(self) -> int:
|
||||
@@ -79,6 +79,10 @@ class Ratekeeper:
|
||||
|
||||
# Monitors the cumulative lag, but does not enforce a rate
|
||||
def monitor_time(self) -> bool:
|
||||
if self._last_monitor_time < 0:
|
||||
self._next_frame_time = time.monotonic() + self._interval
|
||||
self._last_monitor_time = time.monotonic()
|
||||
|
||||
prev = self._last_monitor_time
|
||||
self._last_monitor_time = time.monotonic()
|
||||
self._dts.append(self._last_monitor_time - prev)
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import numpy as np
|
||||
|
||||
from openpilot.common.transformations.orientation import rot_from_euler
|
||||
from openpilot.common.transformations.camera import get_view_frame_from_calib_frame, view_frame_from_device_frame
|
||||
from openpilot.common.transformations.camera import get_view_frame_from_calib_frame, view_frame_from_device_frame, _ar_ox_fisheye
|
||||
|
||||
# segnet
|
||||
SEGNET_SIZE = (512, 384)
|
||||
@@ -39,6 +39,13 @@ sbigmodel_intrinsics = np.array([
|
||||
[0.0, sbigmodel_fl, 0.5 * (256 + MEDMODEL_CY)],
|
||||
[0.0, 0.0, 1.0]])
|
||||
|
||||
DM_INPUT_SIZE = (1440, 960)
|
||||
dmonitoringmodel_fl = _ar_ox_fisheye.focal_length
|
||||
dmonitoringmodel_intrinsics = np.array([
|
||||
[dmonitoringmodel_fl, 0.0, DM_INPUT_SIZE[0]/2],
|
||||
[0.0, dmonitoringmodel_fl, DM_INPUT_SIZE[1]/2 - (_ar_ox_fisheye.height - DM_INPUT_SIZE[1])/2],
|
||||
[0.0, 0.0, 1.0]])
|
||||
|
||||
bigmodel_frame_from_calib_frame = np.dot(bigmodel_intrinsics,
|
||||
get_view_frame_from_calib_frame(0, 0, 0, 0))
|
||||
|
||||
|
||||
+2
-1
@@ -2,8 +2,9 @@
|
||||
|
||||
#include "common/watchdog.h"
|
||||
#include "common/util.h"
|
||||
#include "system/hardware/hw.h"
|
||||
|
||||
const std::string watchdog_fn_prefix = "/dev/shm/wd_"; // + <pid>
|
||||
const std::string watchdog_fn_prefix = Path::shm_path() + "/wd_"; // + <pid>
|
||||
|
||||
bool watchdog_kick(uint64_t ts) {
|
||||
static std::string fn = watchdog_fn_prefix + std::to_string(getpid());
|
||||
|
||||
+7
-6
@@ -4,7 +4,7 @@
|
||||
|
||||
A supported vehicle is one that just works when you install a comma device. All supported cars provide a better experience than any stock system. Supported vehicles reference the US market unless otherwise specified.
|
||||
|
||||
# 289 Supported Cars
|
||||
# 290 Supported Cars
|
||||
|
||||
|Make|Model|Supported Package|ACC|No ACC accel below|No ALC below|Steering Torque|Resume from stop|<a href="##"><img width=2000></a>Hardware Needed<br> |Video|
|
||||
|---|---|---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
|
||||
@@ -103,7 +103,7 @@ A supported vehicle is one that just works when you install a comma device. All
|
||||
|Hyundai|Ioniq Plug-in Hybrid 2020-22|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai H connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Ioniq Plug-in Hybrid 2020-22">Buy Here</a></sub></details>||
|
||||
|Hyundai|Kona 2020|Smart Cruise Control (SCC)|openpilot available[<sup>1</sup>](#footnotes)|6 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai B connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Kona 2020">Buy Here</a></sub></details>||
|
||||
|Hyundai|Kona Electric 2018-21|Smart Cruise Control (SCC)|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai G connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Kona Electric 2018-21">Buy Here</a></sub></details>||
|
||||
|Hyundai|Kona Electric 2022-23|Smart Cruise Control (SCC)|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai O connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Kona Electric 2022-23">Buy Here</a></sub></details>||
|
||||
|Hyundai|Kona Electric 2022-23|Smart Cruise Control (SCC)|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai O connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Kona Electric 2022-23">Buy Here</a></sub></details>||
|
||||
|Hyundai|Kona Electric (with HDA II, Korea only) 2023[<sup>5</sup>](#footnotes)|Smart Cruise Control (SCC)|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai R connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Kona Electric (with HDA II, Korea only) 2023">Buy Here</a></sub></details>|<a href="https://www.youtube.com/watch?v=U2fOCmcQ8hw" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|Hyundai|Kona Hybrid 2020|Smart Cruise Control (SCC)|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai I connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Kona Hybrid 2020">Buy Here</a></sub></details>||
|
||||
|Hyundai|Palisade 2020-22|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai H connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Palisade 2020-22">Buy Here</a></sub></details>|<a href="https://youtu.be/TAnDqjF4fDY?t=456" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
@@ -125,8 +125,9 @@ A supported vehicle is one that just works when you install a comma device. All
|
||||
|Hyundai|Veloster 2019-20|Smart Cruise Control (SCC)|Stock|5 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai E connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Hyundai&model=Veloster 2019-20">Buy Here</a></sub></details>||
|
||||
|Jeep|Grand Cherokee 2016-18|Adaptive Cruise Control (ACC)|Stock|0 mph|9 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Jeep&model=Grand Cherokee 2016-18">Buy Here</a></sub></details>|<a href="https://www.youtube.com/watch?v=eLR9o2JkuRk" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|Jeep|Grand Cherokee 2019-21|Adaptive Cruise Control (ACC)|Stock|0 mph|39 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 FCA connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Jeep&model=Grand Cherokee 2019-21">Buy Here</a></sub></details>|<a href="https://www.youtube.com/watch?v=jBe4lWnRSu4" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|Kia|Carnival 2022-24[<sup>5</sup>](#footnotes)|Smart Cruise Control (SCC)|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai A connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Kia&model=Carnival 2022-24">Buy Here</a></sub></details>||
|
||||
|Kia|Carnival (China only) 2023[<sup>5</sup>](#footnotes)|Smart Cruise Control (SCC)|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai K connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Kia&model=Carnival (China only) 2023">Buy Here</a></sub></details>||
|
||||
|Kia|Carnival 2022-24[<sup>5</sup>](#footnotes)|All|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai A connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Kia&model=Carnival 2022-24">Buy Here</a></sub></details>||
|
||||
|Kia|Carnival (China only) 2023[<sup>5</sup>](#footnotes)|All|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai K connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Kia&model=Carnival (China only) 2023">Buy Here</a></sub></details>||
|
||||
|Kia|Carnival (with HDA II) 2025[<sup>5</sup>](#footnotes)|Highway Driving Assist II|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai Q connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Kia&model=Carnival (with HDA II) 2025">Buy Here</a></sub></details>||
|
||||
|Kia|Ceed 2019|Smart Cruise Control (SCC)|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai E connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Kia&model=Ceed 2019">Buy Here</a></sub></details>||
|
||||
|Kia|EV6 (Southeast Asia only) 2022-24[<sup>5</sup>](#footnotes)|All|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai P connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Kia&model=EV6 (Southeast Asia only) 2022-24">Buy Here</a></sub></details>||
|
||||
|Kia|EV6 (with HDA II) 2022-24[<sup>5</sup>](#footnotes)|Highway Driving Assist II|openpilot available[<sup>1</sup>](#footnotes)|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Hyundai P connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Kia&model=EV6 (with HDA II) 2022-24">Buy Here</a></sub></details>||
|
||||
@@ -167,7 +168,7 @@ A supported vehicle is one that just works when you install a comma device. All
|
||||
|Lexus|ES 2017-18|All|openpilot available[<sup>2</sup>](#footnotes)|19 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 RJ45 cable (7 ft)<br>- 1 Toyota A connector<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lexus&model=ES 2017-18">Buy Here</a></sub></details>||
|
||||
|Lexus|ES 2019-24|All|openpilot|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 RJ45 cable (7 ft)<br>- 1 Toyota A connector<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lexus&model=ES 2019-24">Buy Here</a></sub></details>||
|
||||
|Lexus|ES Hybrid 2017-18|All|openpilot available[<sup>2</sup>](#footnotes)|19 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 RJ45 cable (7 ft)<br>- 1 Toyota A connector<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lexus&model=ES Hybrid 2017-18">Buy Here</a></sub></details>||
|
||||
|Lexus|ES Hybrid 2019-24|All|openpilot|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 RJ45 cable (7 ft)<br>- 1 Toyota A connector<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lexus&model=ES Hybrid 2019-24">Buy Here</a></sub></details>|<a href="https://youtu.be/BZ29osRVJeg?t=12" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|Lexus|ES Hybrid 2019-25|All|openpilot|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 RJ45 cable (7 ft)<br>- 1 Toyota A connector<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lexus&model=ES Hybrid 2019-25">Buy Here</a></sub></details>|<a href="https://youtu.be/BZ29osRVJeg?t=12" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|Lexus|GS F 2016|All|Stock|19 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 RJ45 cable (7 ft)<br>- 1 Toyota A connector<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lexus&model=GS F 2016">Buy Here</a></sub></details>||
|
||||
|Lexus|IS 2017-19|All|Stock|19 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 RJ45 cable (7 ft)<br>- 1 Toyota A connector<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lexus&model=IS 2017-19">Buy Here</a></sub></details>||
|
||||
|Lexus|IS 2022-23|All|openpilot|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 RJ45 cable (7 ft)<br>- 1 Toyota A connector<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lexus&model=IS 2022-23">Buy Here</a></sub></details>||
|
||||
@@ -188,7 +189,7 @@ A supported vehicle is one that just works when you install a comma device. All
|
||||
|Lincoln|Aviator Plug-in Hybrid 2020-24|Co-Pilot360 Plus|openpilot|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Ford Q3 connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Lincoln&model=Aviator Plug-in Hybrid 2020-24">Buy Here</a></sub></details>||
|
||||
|MAN|eTGE 2020-24|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,12</sup>](#footnotes)|0 mph|31 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 USB-C coupler<br>- 1 VW J533 connector<br>- 1 angled mount (8 degrees)<br>- 1 comma 3X<br>- 1 harness box<br>- 1 long OBD-C cable<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=MAN&model=eTGE 2020-24">Buy Here</a></sub></details>|<a href="https://youtu.be/4100gLeabmo" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|MAN|TGE 2017-24|Adaptive Cruise Control (ACC) & Lane Assist|openpilot available[<sup>1,12</sup>](#footnotes)|0 mph|31 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 USB-C coupler<br>- 1 VW J533 connector<br>- 1 angled mount (8 degrees)<br>- 1 comma 3X<br>- 1 harness box<br>- 1 long OBD-C cable<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=MAN&model=TGE 2017-24">Buy Here</a></sub></details>|<a href="https://youtu.be/4100gLeabmo" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|Mazda|CX-5 2022-24|All|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Mazda connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Mazda&model=CX-5 2022-24">Buy Here</a></sub></details>||
|
||||
|Mazda|CX-5 2022-25|All|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Mazda connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Mazda&model=CX-5 2022-25">Buy Here</a></sub></details>||
|
||||
|Mazda|CX-9 2021-23|All|Stock|0 mph|28 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Mazda connector<br>- 1 RJ45 cable (7 ft)<br>- 1 comma 3X<br>- 1 comma power v2<br>- 1 harness box<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Mazda&model=CX-9 2021-23">Buy Here</a></sub></details>|<a href="https://youtu.be/dA3duO4a0O4" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|Nissan|Altima 2019-20|ProPILOT Assist|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Nissan B connector<br>- 1 RJ45 cable (7 ft)<br>- 1 USB-C coupler<br>- 1 comma 3X<br>- 1 harness box<br>- 1 long OBD-C cable<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Nissan&model=Altima 2019-20">Buy Here</a></sub></details>||
|
||||
|Nissan|Leaf 2018-23|ProPILOT Assist|Stock|0 mph|0 mph|[](##)|[](##)|<details><summary>Parts</summary><sub>- 1 Nissan A connector<br>- 1 RJ45 cable (7 ft)<br>- 1 USB-C coupler<br>- 1 comma 3X<br>- 1 harness box<br>- 1 long OBD-C cable<br>- 1 mount<br>- 1 right angle OBD-C cable (1.5 ft)<br><a href="https://comma.ai/shop/comma-3x.html?make=Nissan&model=Leaf 2018-23">Buy Here</a></sub></details>|<a href="https://youtu.be/vaMbtAh_0cY" target="_blank"><img height="18px" src="assets/icon-youtube.svg"></img></a>|
|
||||
|
||||
@@ -0,0 +1,44 @@
|
||||
[data-tooltip] {
|
||||
position: relative;
|
||||
display: inline-block;
|
||||
border-bottom: 1px dotted black;
|
||||
}
|
||||
|
||||
[data-tooltip] .tooltip-content {
|
||||
width: max-content;
|
||||
max-width: 25em;
|
||||
position: absolute;
|
||||
top: 100%;
|
||||
left: 50%;
|
||||
transform: translateX(-50%);
|
||||
background-color: white;
|
||||
color: #404040;
|
||||
box-shadow: 0 4px 14px 0 rgba(0,0,0,.2), 0 0 0 1px rgba(0,0,0,.05);
|
||||
padding: 10px;
|
||||
font: 14px/1.5 Lato, proxima-nova, Helvetica Neue, Arial, sans-serif;
|
||||
text-decoration: none;
|
||||
opacity: 0;
|
||||
visibility: hidden;
|
||||
transition: opacity 0.1s, visibility 0s;
|
||||
z-index: 1000;
|
||||
pointer-events: none; /* Prevent accidental interaction */
|
||||
}
|
||||
|
||||
[data-tooltip]:hover .tooltip-content {
|
||||
opacity: 1;
|
||||
visibility: visible;
|
||||
pointer-events: auto; /* Allow interaction when visible */
|
||||
}
|
||||
|
||||
.tooltip-content .tooltip-glossary-link {
|
||||
display: inline-block;
|
||||
margin-top: 8px;
|
||||
font-size: 12px;
|
||||
color: #007bff;
|
||||
text-decoration: none;
|
||||
}
|
||||
|
||||
.tooltip-content .tooltip-glossary-link:hover {
|
||||
color: #0056b3;
|
||||
text-decoration: underline;
|
||||
}
|
||||
@@ -0,0 +1,68 @@
|
||||
import re
|
||||
import tomllib
|
||||
|
||||
def load_glossary(file_path="docs/glossary.toml"):
|
||||
with open(file_path, "rb") as f:
|
||||
glossary_data = tomllib.load(f)
|
||||
return glossary_data.get("glossary", {})
|
||||
|
||||
def generate_anchor_id(name):
|
||||
return name.replace(" ", "-").replace("_", "-").lower()
|
||||
|
||||
def format_markdown_term(name, definition):
|
||||
anchor_id = generate_anchor_id(name)
|
||||
markdown = f"* [**{name.replace('_', ' ').title()}**](#{anchor_id})"
|
||||
if definition.get("abbreviation"):
|
||||
markdown += f" *({definition['abbreviation']})*"
|
||||
if definition.get("description"):
|
||||
markdown += f": {definition['description']}\n"
|
||||
return markdown
|
||||
|
||||
def glossary_markdown(vocabulary):
|
||||
markdown = ""
|
||||
for category, terms in vocabulary.items():
|
||||
markdown += f"## {category.replace('_', ' ').title()}\n\n"
|
||||
for name, definition in terms.items():
|
||||
markdown += format_markdown_term(name, definition)
|
||||
return markdown
|
||||
|
||||
def format_tooltip_html(term_key, definition, html):
|
||||
display_term = term_key.replace("_", " ").title()
|
||||
clean_description = re.sub(r"\[(.+)]\(.+\)", r"\1", definition["description"])
|
||||
glossary_link = (
|
||||
f"<a href='/concepts/glossary#{term_key}' class='tooltip-glossary-link' title='View in glossary'>Glossary🔗</a>"
|
||||
)
|
||||
return re.sub(
|
||||
re.escape(display_term),
|
||||
lambda
|
||||
match: f"<span data-tooltip>{match.group(0)}<span class='tooltip-content'>{clean_description} {glossary_link}</span></span>",
|
||||
html,
|
||||
flags=re.IGNORECASE,
|
||||
)
|
||||
|
||||
def apply_tooltip(_term_key, _definition, pattern, html):
|
||||
return re.sub(
|
||||
pattern,
|
||||
lambda match: format_tooltip_html(_term_key, _definition, match.group(0)),
|
||||
html,
|
||||
flags=re.IGNORECASE,
|
||||
)
|
||||
|
||||
def tooltip_html(vocabulary, html):
|
||||
for _category, terms in vocabulary.items():
|
||||
for term_key, definition in terms.items():
|
||||
if definition.get("description"):
|
||||
pattern = rf"(?<!\w){re.escape(term_key.replace('_', ' ').title())}(?![^<]*<\/a>)(?!\([^)]*\))"
|
||||
html = apply_tooltip(term_key, definition, pattern, html)
|
||||
return html
|
||||
|
||||
# Page Hooks
|
||||
def on_page_markdown(markdown, **kwargs):
|
||||
glossary = load_glossary()
|
||||
return markdown.replace("{{GLOSSARY_DEFINITIONS}}", glossary_markdown(glossary))
|
||||
|
||||
def on_page_content(html, **kwargs):
|
||||
if kwargs.get("page").title == "Glossary":
|
||||
return html
|
||||
glossary = load_glossary()
|
||||
return tooltip_html(glossary, html)
|
||||
+1
-1
@@ -7,7 +7,7 @@ export OPENBLAS_NUM_THREADS=1
|
||||
export VECLIB_MAXIMUM_THREADS=1
|
||||
|
||||
if [ -z "$AGNOS_VERSION" ]; then
|
||||
export AGNOS_VERSION="11.2"
|
||||
export AGNOS_VERSION="11.4"
|
||||
fi
|
||||
|
||||
export STAGING_ROOT="/data/safe_staging"
|
||||
|
||||
@@ -8,6 +8,10 @@ strict: true
|
||||
docs_dir: docs
|
||||
site_dir: docs_site/
|
||||
|
||||
hooks:
|
||||
- docs/hooks/glossary.py
|
||||
extra_css:
|
||||
- css/tooltip.css
|
||||
theme:
|
||||
name: readthedocs
|
||||
navigation_depth: 3
|
||||
|
||||
+1
-1
Submodule msgq_repo updated: 3e17f865bb...5bb86f8bc7
+1
-1
Submodule opendbc_repo updated: 7cb3d4c021...9de5605ac4
+1
-1
Submodule panda updated: dec9223f97...5c1923fe0c
+6
-4
@@ -1,6 +1,6 @@
|
||||
[project]
|
||||
name = "openpilot"
|
||||
requires-python = ">= 3.11, <= 3.12"
|
||||
requires-python = ">= 3.11, < 3.13"
|
||||
license = {text = "MIT License"}
|
||||
version = "0.1.0"
|
||||
description = "an open source driver assistance system"
|
||||
@@ -31,6 +31,9 @@ dependencies = [
|
||||
# body / webrtcd
|
||||
"aiohttp",
|
||||
"aiortc",
|
||||
# aiortc does not put an upper bound on pyopenssl and is now incompatible
|
||||
# with the latest release
|
||||
"pyopenssl < 24.3.0",
|
||||
"pyaudio",
|
||||
|
||||
# panda
|
||||
@@ -39,8 +42,7 @@ dependencies = [
|
||||
|
||||
# modeld
|
||||
"onnx >= 1.14.0",
|
||||
"onnxruntime >=1.16.3; platform_system == 'Linux' and platform_machine == 'aarch64'",
|
||||
"onnxruntime-gpu >=1.16.3; platform_system == 'Linux' and platform_machine == 'x86_64'",
|
||||
"onnxruntime >=1.16.3",
|
||||
|
||||
# logging
|
||||
"pyzmq",
|
||||
@@ -98,7 +100,6 @@ dev = [
|
||||
"azure-identity",
|
||||
"azure-storage-blob",
|
||||
"dictdiffer",
|
||||
"flaky",
|
||||
"lru-dict",
|
||||
"matplotlib",
|
||||
"parameterized >=0.8, <0.9",
|
||||
@@ -239,6 +240,7 @@ exclude = [
|
||||
"cereal",
|
||||
"panda",
|
||||
"opendbc",
|
||||
"opendbc_repo",
|
||||
"rednose_repo",
|
||||
"tinygrad_repo",
|
||||
"teleoprtc",
|
||||
|
||||
@@ -32,7 +32,6 @@ blacklist = [
|
||||
|
||||
".git/",
|
||||
".github/",
|
||||
".devcontainer/",
|
||||
"Darwin/",
|
||||
".vscode",
|
||||
|
||||
@@ -55,7 +54,7 @@ whitelist = [
|
||||
"tools/joystick/",
|
||||
"tools/longitudinal_maneuvers/",
|
||||
|
||||
"tinygrad_repo/openpilot/compile2.py",
|
||||
"tinygrad_repo/examples/openpilot/compile3.py",
|
||||
"tinygrad_repo/extra/onnx.py",
|
||||
"tinygrad_repo/extra/onnx_ops.py",
|
||||
"tinygrad_repo/extra/thneed.py",
|
||||
|
||||
@@ -37,7 +37,7 @@ for f in sorted(pyf):
|
||||
lns = len(src.split("\n"))
|
||||
tree = ast.parse(src)
|
||||
Analyzer().visit(tree)
|
||||
print("%5d %s %s" % (lns, f, xbit))
|
||||
print(f"{lns:5d} {f} {xbit}")
|
||||
if 'test' in f:
|
||||
testlns += lns
|
||||
elif f.startswith(('tools/', 'scripts/', 'selfdrive/debug')):
|
||||
@@ -47,8 +47,8 @@ for f in sorted(pyf):
|
||||
else:
|
||||
tlns += lns
|
||||
|
||||
print("%d lines of openpilot python" % tlns)
|
||||
print("%d lines of car ports" % carlns)
|
||||
print("%d lines of tools/scripts/debug" % scriptlns)
|
||||
print("%d lines of tests" % testlns)
|
||||
print(f"{tlns} lines of openpilot python")
|
||||
print(f"{carlns} lines of car ports")
|
||||
print(f"{scriptlns} lines of tools/scripts/debug")
|
||||
print(f"{testlns} lines of tests")
|
||||
#print(sorted(list(imps)))
|
||||
|
||||
Executable
+10
@@ -0,0 +1,10 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
FAIL=0
|
||||
|
||||
if grep -n '#include "third_party/raylib/include/raylib\.h"' $@ | grep -v '^system/ui/raylib/raylib\.h'; then
|
||||
echo -e "Bad raylib include found! Use '#include \"system/ui/raylib/raylib.h\"' instead\n"
|
||||
FAIL=1
|
||||
fi
|
||||
|
||||
exit $FAIL
|
||||
@@ -53,6 +53,7 @@ function run_tests() {
|
||||
run "check_shebang_scripts_are_executable" python3 -m pre_commit_hooks.check_shebang_scripts_are_executable $ALL_FILES
|
||||
run "check_shebang_format" $DIR/check_shebang_format.sh $ALL_FILES
|
||||
run "check_nomerge_comments" $DIR/check_nomerge_comments.sh $ALL_FILES
|
||||
run "check_raylib_includes" $DIR/check_raylib_includes.sh $ALL_FILES
|
||||
|
||||
if [[ -z "$FAST" ]]; then
|
||||
run "mypy" mypy $PYTHON_FILES
|
||||
|
||||
+2
-2
@@ -16,9 +16,9 @@ def waste(core):
|
||||
j = 0
|
||||
while 1:
|
||||
if (i % 100) == 0:
|
||||
setproctitle("%3d: %8d" % (core, i))
|
||||
setproctitle(f"{core:3d}: {i:8d}")
|
||||
lt = time.monotonic()
|
||||
print("%3d: %8d %f %.2f" % (core, i, lt-st, j))
|
||||
print(f"{core:3d}: {i:8d} {lt-st:f} {j:.2f}")
|
||||
st = lt
|
||||
i += 1
|
||||
j = np.sum(np.matmul(m1, m2))
|
||||
|
||||
@@ -1,3 +0,0 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:f7565541b4e6213221174839b9b2b67397ced0b9807ea56413989fd37325b3b6
|
||||
size 4908
|
||||
@@ -148,7 +148,8 @@ class CarSpecificEvents:
|
||||
# To avoid re-engaging when openpilot cancels, check user engagement intention via buttons
|
||||
# Main button also can trigger an engagement on these cars
|
||||
self.cruise_buttons.append(any(ev.type in HYUNDAI_ENABLE_BUTTONS for ev in CS.buttonEvents))
|
||||
events = self.create_common_events(CS, CS_prev, pcm_enable=self.CP.pcmCruise, allow_enable=any(self.cruise_buttons))
|
||||
events = self.create_common_events(CS, CS_prev, extra_gears=(GearShifter.sport, GearShifter.manumatic),
|
||||
pcm_enable=self.CP.pcmCruise, allow_enable=any(self.cruise_buttons))
|
||||
|
||||
# low speed steer alert hysteresis logic (only for cars with steer cut off above 10 m/s)
|
||||
if CS.vEgo < (self.CP.minSteerSpeed + 2.) and self.CP.minSteerSpeed > 10.:
|
||||
|
||||
@@ -17,7 +17,7 @@ class TestCarDocs:
|
||||
with open(CARS_MD_OUT) as f:
|
||||
current_cars_md = f.read()
|
||||
|
||||
assert generated_cars_md == current_cars_md, "Run selfdrive/opcar/docs.py to update the compatibility documentation"
|
||||
assert generated_cars_md == current_cars_md, "Run selfdrive/car/docs.py to update the compatibility documentation"
|
||||
|
||||
def test_docs_diff(self):
|
||||
dump_path = os.path.join(BASEDIR, "selfdrive", "car", "tests", "cars_dump")
|
||||
|
||||
@@ -394,7 +394,7 @@ class TestCarModelBase(unittest.TestCase):
|
||||
for msg in filter(lambda m: m.src in range(64), can.can):
|
||||
to_send = libpanda_py.make_CANPacket(msg.address, msg.src % 4, msg.dat)
|
||||
ret = self.safety.safety_rx_hook(to_send)
|
||||
self.assertEqual(1, ret, f"safety rx failed ({ret=}): {to_send}")
|
||||
self.assertEqual(1, ret, f"safety rx failed ({ret=}): {(msg.address, msg.src % 4)}")
|
||||
|
||||
# Skip first frame so CS_prev is properly initialized
|
||||
if idx == 0:
|
||||
|
||||
@@ -5,12 +5,15 @@ from openpilot.common.realtime import DT_CTRL
|
||||
MIN_SPEED = 1.0
|
||||
CONTROL_N = 17
|
||||
CAR_ROTATION_RADIUS = 0.0
|
||||
# This is a turn radius smaller than most cars can achieve
|
||||
MAX_CURVATURE = 0.2
|
||||
|
||||
# EU guidelines
|
||||
MAX_LATERAL_JERK = 5.0
|
||||
MAX_VEL_ERR = 5.0
|
||||
|
||||
def clip_curvature(v_ego, prev_curvature, new_curvature):
|
||||
new_curvature = clip(new_curvature, -MAX_CURVATURE, MAX_CURVATURE)
|
||||
v_ego = max(MIN_SPEED, v_ego)
|
||||
max_curvature_rate = MAX_LATERAL_JERK / (v_ego**2) # inexact calculation, check https://github.com/commaai/openpilot/pull/24755
|
||||
safe_desired_curvature = clip(new_curvature,
|
||||
|
||||
@@ -50,24 +50,20 @@ def limit_accel_in_turns(v_ego, angle_steers, a_target, CP):
|
||||
return [a_target[0], min(a_target[1], a_x_allowed)]
|
||||
|
||||
|
||||
def get_accel_from_plan(CP, speeds, accels):
|
||||
def get_accel_from_plan(speeds, accels, action_t=DT_MDL, vEgoStopping=0.05):
|
||||
if len(speeds) == CONTROL_N:
|
||||
v_target_now = interp(DT_MDL, CONTROL_N_T_IDX, speeds)
|
||||
a_target_now = interp(DT_MDL, CONTROL_N_T_IDX, accels)
|
||||
v_now = speeds[0]
|
||||
a_now = accels[0]
|
||||
|
||||
v_target = interp(CP.longitudinalActuatorDelay + DT_MDL, CONTROL_N_T_IDX, speeds)
|
||||
if v_target != v_target_now:
|
||||
a_target = 2 * (v_target - v_target_now) / CP.longitudinalActuatorDelay - a_target_now
|
||||
else:
|
||||
a_target = a_target_now
|
||||
|
||||
v_target_1sec = interp(CP.longitudinalActuatorDelay + DT_MDL + 1.0, CONTROL_N_T_IDX, speeds)
|
||||
v_target = interp(action_t, CONTROL_N_T_IDX, speeds)
|
||||
a_target = 2 * (v_target - v_now) / (action_t) - a_now
|
||||
v_target_1sec = interp(action_t + 1.0, CONTROL_N_T_IDX, speeds)
|
||||
else:
|
||||
v_target = 0.0
|
||||
v_target_1sec = 0.0
|
||||
a_target = 0.0
|
||||
should_stop = (v_target < CP.vEgoStopping and
|
||||
v_target_1sec < CP.vEgoStopping)
|
||||
should_stop = (v_target < vEgoStopping and
|
||||
v_target_1sec < vEgoStopping)
|
||||
return a_target, should_stop
|
||||
|
||||
|
||||
@@ -201,7 +197,9 @@ class LongitudinalPlanner:
|
||||
longitudinalPlan.longitudinalPlanSource = self.mpc.source
|
||||
longitudinalPlan.fcw = self.fcw
|
||||
|
||||
a_target, should_stop = get_accel_from_plan(self.CP, longitudinalPlan.speeds, longitudinalPlan.accels)
|
||||
action_t = self.CP.longitudinalActuatorDelay + DT_MDL
|
||||
a_target, should_stop = get_accel_from_plan(longitudinalPlan.speeds, longitudinalPlan.accels,
|
||||
action_t=action_t, vEgoStopping=self.CP.vEgoStopping)
|
||||
longitudinalPlan.aTarget = a_target
|
||||
longitudinalPlan.shouldStop = should_stop
|
||||
longitudinalPlan.allowBrake = True
|
||||
|
||||
@@ -28,7 +28,7 @@ def can_printer(bus, max_msg, addr, ascii_decode):
|
||||
x = binascii.hexlify(msgs[_addr][-1]).decode('ascii')
|
||||
freq = len(msgs[_addr]) / (time.monotonic() - start)
|
||||
if max_msg is None or _addr < max_msg:
|
||||
dd += "%04X(%4d)(%6d)(%3dHz) %s %s\n" % (_addr, _addr, len(msgs[_addr]), freq, x.ljust(20), a)
|
||||
dd += f"{_addr:04X}({_addr:4d})({len(msgs[_addr]):6d})({freq:3}dHz) {x.ljust(20)} {a}\n"
|
||||
print(dd)
|
||||
lp = time.monotonic()
|
||||
|
||||
|
||||
@@ -29,7 +29,7 @@ if __name__ == '__main__':
|
||||
start_t = time.process_time_ns()
|
||||
for msg in msgs:
|
||||
can_list = can_capnp_to_list([msg])
|
||||
for cp in tm.CI.can_parsers:
|
||||
for cp in tm.CI.can_parsers.values():
|
||||
if cp is not None:
|
||||
cp.update_strings(can_list)
|
||||
ets.append((time.process_time_ns() - start_t) * 1e-6)
|
||||
|
||||
@@ -8,6 +8,7 @@ from typing import cast
|
||||
|
||||
from cereal.services import SERVICE_LIST
|
||||
from openpilot.tools.lib.logreader import LogReader, ReadMode
|
||||
from openpilot.selfdrive.test.process_replay.migration import migrate_all
|
||||
|
||||
if __name__ == "__main__":
|
||||
cnt_events: Counter = Counter()
|
||||
@@ -20,7 +21,7 @@ if __name__ == "__main__":
|
||||
start_time = math.inf
|
||||
end_time = -math.inf
|
||||
ignition_off = None
|
||||
for msg in LogReader(sys.argv[1], ReadMode.QLOG):
|
||||
for msg in migrate_all(LogReader(sys.argv[1], ReadMode.QLOG)):
|
||||
t = (msg.logMonoTime - start_time) / 1e9
|
||||
end_time = max(end_time, msg.logMonoTime)
|
||||
start_time = min(start_time, msg.logMonoTime)
|
||||
|
||||
@@ -22,7 +22,7 @@ def get_fingerprint(lr):
|
||||
msgs[c.address] = len(c.dat)
|
||||
|
||||
# show CAN fingerprint
|
||||
fingerprint = ', '.join("%d: %d" % v for v in sorted(msgs.items()))
|
||||
fingerprint = ', '.join(f"{v[0]}: {v[1]}" for v in sorted(msgs.items()))
|
||||
print(f"\nfound {len(msgs)} messages. CAN fingerprint:\n")
|
||||
print(fingerprint)
|
||||
|
||||
|
||||
@@ -25,7 +25,7 @@ while True:
|
||||
if c.src % 0x80 == 0 and c.address < 0x800 and c.address not in (0x7df, 0x7e0, 0x7e8):
|
||||
msgs[c.address] = len(c.dat)
|
||||
|
||||
fingerprint = ', '.join("%d: %d" % v for v in sorted(msgs.items()))
|
||||
fingerprint = ', '.join(f"{v[0]}: {v[1]}" for v in sorted(msgs.items()))
|
||||
|
||||
print(f"number of messages {len(msgs)}:")
|
||||
print(f"fingerprint {fingerprint}")
|
||||
|
||||
Executable
+54
@@ -0,0 +1,54 @@
|
||||
#!/usr/bin/env python3
|
||||
import argparse
|
||||
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
from openpilot.tools.lib.logreader import LogReader
|
||||
|
||||
if __name__ == '__main__':
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument('--width', default=2160, type=int)
|
||||
parser.add_argument('--height', default=1080, type=int)
|
||||
parser.add_argument('--route', default='rlog', type=str)
|
||||
args = parser.parse_args()
|
||||
|
||||
w = args.width
|
||||
h = args.height
|
||||
route = args.route
|
||||
|
||||
fingers = [[-1, -1]] * 5
|
||||
touch_points = []
|
||||
current_slot = 0
|
||||
|
||||
lr = list(LogReader(route))
|
||||
for msg in lr:
|
||||
if msg.which() == 'touch':
|
||||
for event in msg.touch:
|
||||
if event.type == 3 and event.code == 47:
|
||||
current_slot = event.value
|
||||
elif event.type == 3 and event.code == 57 and event.value == -1:
|
||||
fingers[current_slot] = [-1, -1]
|
||||
elif event.type == 3 and event.code == 53:
|
||||
fingers[current_slot][1] = h - (h - event.value)
|
||||
if fingers[current_slot][0] != -1:
|
||||
touch_points.append(fingers[current_slot].copy())
|
||||
elif event.type == 3 and event.code == 54:
|
||||
fingers[current_slot][0] = w - event.value
|
||||
if fingers[current_slot][1] != -1:
|
||||
touch_points.append(fingers[current_slot].copy())
|
||||
|
||||
if not touch_points:
|
||||
print(f'No touch events found for {route}')
|
||||
quit()
|
||||
|
||||
unique_points, counts = np.unique(touch_points, axis=0, return_counts=True)
|
||||
|
||||
plt.figure(figsize=(10, 3))
|
||||
plt.scatter(unique_points[:, 0], unique_points[:, 1], c=counts, s=counts * 20, edgecolors='red')
|
||||
plt.colorbar()
|
||||
plt.title(f'Touches for {route}')
|
||||
plt.xlim(0, w)
|
||||
plt.ylim(0, h)
|
||||
plt.grid(True)
|
||||
plt.show()
|
||||
@@ -8,6 +8,7 @@ from enum import Enum
|
||||
from collections import defaultdict
|
||||
|
||||
from cereal import log, messaging
|
||||
from cereal.services import SERVICE_LIST
|
||||
from openpilot.common.transformations.orientation import rot_from_euler
|
||||
from openpilot.common.realtime import config_realtime_process
|
||||
from openpilot.common.params import Params
|
||||
@@ -23,8 +24,10 @@ MIN_STD_SANITY_CHECK = 1e-5 # m or rad
|
||||
MAX_FILTER_REWIND_TIME = 0.8 # s
|
||||
MAX_SENSOR_TIME_DIFF = 0.1 # s
|
||||
YAWRATE_CROSS_ERR_CHECK_FACTOR = 30
|
||||
INPUT_INVALID_THRESHOLD = 0.5
|
||||
INPUT_INVALID_DECAY = 0.9993 # ~10 secs to resume after a bad input
|
||||
INPUT_INVALID_THRESHOLD = 0.5 # 0 bad inputs ignored
|
||||
TIMING_INVALID_THRESHOLD = 2.5 # 2 bad timings ignored
|
||||
INPUT_INVALID_DECAY = 0.9993 # ~10 secs to resume after exceeding allowed bad inputs by one (at 100hz)
|
||||
TIMING_INVALID_DECAY = 0.9990 # ~2 secs to resume after exceeding allowed bad timings by one (at 100hz)
|
||||
POSENET_STD_INITIAL_VALUE = 10.0
|
||||
POSENET_STD_HIST_HALF = 20
|
||||
|
||||
@@ -265,10 +268,13 @@ def main():
|
||||
estimator = LocationEstimator(DEBUG)
|
||||
|
||||
filter_initialized = False
|
||||
critcal_services = ["accelerometer", "gyroscope", "liveCalibration", "cameraOdometry"]
|
||||
observation_timing_invalid = False
|
||||
critcal_services = ["accelerometer", "gyroscope", "cameraOdometry"]
|
||||
observation_timing_invalid = defaultdict(int)
|
||||
observation_input_invalid = defaultdict(int)
|
||||
|
||||
input_invalid_decay = {s: INPUT_INVALID_DECAY ** (100. / SERVICE_LIST[s].frequency) for s in critcal_services}
|
||||
timing_invalid_decay = {s: TIMING_INVALID_DECAY ** (100. / SERVICE_LIST[s].frequency) for s in critcal_services}
|
||||
|
||||
initial_pose = params.get("LocationFilterInitialState")
|
||||
if initial_pose is not None:
|
||||
initial_pose = json.loads(initial_pose)
|
||||
@@ -282,8 +288,6 @@ def main():
|
||||
acc_msgs, gyro_msgs = (messaging.drain_sock(sock) for sock in sensor_sockets)
|
||||
|
||||
if filter_initialized:
|
||||
observation_timing_invalid = False
|
||||
|
||||
msgs = []
|
||||
for msg in acc_msgs + gyro_msgs:
|
||||
t, valid, which, data = msg.logMonoTime, msg.valid, msg.which(), getattr(msg, msg.which())
|
||||
@@ -298,18 +302,23 @@ def main():
|
||||
if valid:
|
||||
t = log_mono_time * 1e-9
|
||||
res = estimator.handle_log(t, which, msg)
|
||||
if which not in critcal_services:
|
||||
continue
|
||||
|
||||
if res == HandleLogResult.TIMING_INVALID:
|
||||
observation_timing_invalid = True
|
||||
observation_timing_invalid[which] += 1
|
||||
elif res == HandleLogResult.INPUT_INVALID:
|
||||
observation_input_invalid[which] += 1
|
||||
else:
|
||||
observation_input_invalid[which] *= INPUT_INVALID_DECAY
|
||||
observation_input_invalid[which] *= input_invalid_decay[which]
|
||||
observation_timing_invalid[which] *= timing_invalid_decay[which]
|
||||
else:
|
||||
filter_initialized = sm.all_checks() and sensor_all_checks(acc_msgs, gyro_msgs, sensor_valid, sensor_recv_time, sensor_alive, SIMULATION)
|
||||
|
||||
if sm.updated["cameraOdometry"]:
|
||||
critical_service_inputs_valid = all(observation_input_invalid[s] < INPUT_INVALID_THRESHOLD for s in critcal_services)
|
||||
inputs_valid = sm.all_valid() and critical_service_inputs_valid and not observation_timing_invalid
|
||||
critical_service_timing_valid = all(observation_timing_invalid[s] < TIMING_INVALID_THRESHOLD for s in critcal_services)
|
||||
inputs_valid = sm.all_valid() and critical_service_inputs_valid and critical_service_timing_valid
|
||||
sensors_valid = sensor_all_checks(acc_msgs, gyro_msgs, sensor_valid, sensor_recv_time, sensor_alive, SIMULATION)
|
||||
|
||||
msg = estimator.get_msg(sensors_valid, inputs_valid, filter_initialized)
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
import pytest
|
||||
import numpy as np
|
||||
from collections import defaultdict
|
||||
from enum import Enum
|
||||
@@ -17,6 +16,7 @@ SELECT_COMPARE_FIELDS = {
|
||||
'sensors_flag': ['sensorsOK'],
|
||||
}
|
||||
JUNK_IDX = 100
|
||||
CONSISTENT_SPIKES_COUNT = 10
|
||||
|
||||
|
||||
class Scenario(Enum):
|
||||
@@ -25,6 +25,8 @@ class Scenario(Enum):
|
||||
GYRO_SPIKE_MIDWAY = 'gyro_spike_midway'
|
||||
ACCEL_OFF = 'accel_off'
|
||||
ACCEL_SPIKE_MIDWAY = 'accel_spike_midway'
|
||||
SENSOR_TIMING_SPIKE_MIDWAY = 'timing_spikes'
|
||||
SENSOR_TIMING_CONSISTENT_SPIKES = 'timing_consistent_spikes'
|
||||
|
||||
|
||||
def get_select_fields_data(logs):
|
||||
@@ -43,6 +45,17 @@ def get_select_fields_data(logs):
|
||||
return data
|
||||
|
||||
|
||||
def modify_logs_midway(logs, which, count, fn):
|
||||
non_which = [x for x in logs if x.which() != which]
|
||||
which = [x for x in logs if x.which() == which]
|
||||
temps = which[len(which) // 2:len(which) // 2 + count]
|
||||
for i, temp in enumerate(temps):
|
||||
temp = temp.as_builder()
|
||||
fn(temp)
|
||||
which[len(which) // 2 + i] = temp.as_reader()
|
||||
return sorted(non_which + which, key=lambda x: x.logMonoTime)
|
||||
|
||||
|
||||
def run_scenarios(scenario, logs):
|
||||
if scenario == Scenario.BASE:
|
||||
pass
|
||||
@@ -51,30 +64,28 @@ def run_scenarios(scenario, logs):
|
||||
logs = sorted([x for x in logs if x.which() != 'gyroscope'], key=lambda x: x.logMonoTime)
|
||||
|
||||
elif scenario == Scenario.GYRO_SPIKE_MIDWAY:
|
||||
non_gyro = [x for x in logs if x.which() not in 'gyroscope']
|
||||
gyro = [x for x in logs if x.which() in 'gyroscope']
|
||||
temp = gyro[len(gyro) // 2].as_builder()
|
||||
temp.gyroscope.gyroUncalibrated.v[0] += 3.0
|
||||
gyro[len(gyro) // 2] = temp.as_reader()
|
||||
logs = sorted(non_gyro + gyro, key=lambda x: x.logMonoTime)
|
||||
def gyro_spike(msg):
|
||||
msg.gyroscope.gyroUncalibrated.v[0] += 3.0
|
||||
logs = modify_logs_midway(logs, 'gyroscope', 1, gyro_spike)
|
||||
|
||||
elif scenario == Scenario.ACCEL_OFF:
|
||||
logs = sorted([x for x in logs if x.which() != 'accelerometer'], key=lambda x: x.logMonoTime)
|
||||
|
||||
elif scenario == Scenario.ACCEL_SPIKE_MIDWAY:
|
||||
non_accel = [x for x in logs if x.which() not in 'accelerometer']
|
||||
accel = [x for x in logs if x.which() in 'accelerometer']
|
||||
temp = accel[len(accel) // 2].as_builder()
|
||||
temp.accelerometer.acceleration.v[0] += 10.0
|
||||
accel[len(accel) // 2] = temp.as_reader()
|
||||
logs = sorted(non_accel + accel, key=lambda x: x.logMonoTime)
|
||||
def acc_spike(msg):
|
||||
msg.accelerometer.acceleration.v[0] += 10.0
|
||||
logs = modify_logs_midway(logs, 'accelerometer', 1, acc_spike)
|
||||
|
||||
elif scenario == Scenario.SENSOR_TIMING_SPIKE_MIDWAY or scenario == Scenario.SENSOR_TIMING_CONSISTENT_SPIKES:
|
||||
def timing_spike(msg):
|
||||
msg.accelerometer.timestamp -= int(0.150 * 1e9)
|
||||
count = 1 if scenario == Scenario.SENSOR_TIMING_SPIKE_MIDWAY else CONSISTENT_SPIKES_COUNT
|
||||
logs = modify_logs_midway(logs, 'accelerometer', count, timing_spike)
|
||||
|
||||
replayed_logs = replay_process_with_name(name='locationd', lr=logs)
|
||||
return get_select_fields_data(logs), get_select_fields_data(replayed_logs)
|
||||
|
||||
|
||||
@pytest.mark.xdist_group("test_locationd_scenarios")
|
||||
@pytest.mark.shared_download_cache
|
||||
class TestLocationdScenarios:
|
||||
"""
|
||||
Test locationd with different scenarios. In all these scenarios, we expect the following:
|
||||
@@ -122,7 +133,7 @@ class TestLocationdScenarios:
|
||||
assert np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.35))
|
||||
assert np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(0.55))
|
||||
assert np.diff(replayed_data['inputs_flag'])[499] == -1.0
|
||||
assert np.diff(replayed_data['inputs_flag'])[696] == 1.0
|
||||
assert np.diff(replayed_data['inputs_flag'])[704] == 1.0
|
||||
|
||||
def test_accel_off(self):
|
||||
"""
|
||||
@@ -146,3 +157,21 @@ class TestLocationdScenarios:
|
||||
orig_data, replayed_data = run_scenarios(Scenario.ACCEL_SPIKE_MIDWAY, self.logs)
|
||||
assert np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.35))
|
||||
assert np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(0.55))
|
||||
|
||||
def test_single_timing_spike(self):
|
||||
"""
|
||||
Test: timing of 150ms off for the single accelerometer message in the middle of the segment
|
||||
Expected Result: the message is ignored, and inputsOK is False for that time
|
||||
"""
|
||||
orig_data, replayed_data = run_scenarios(Scenario.SENSOR_TIMING_SPIKE_MIDWAY, self.logs)
|
||||
assert np.all(replayed_data['inputs_flag'] == orig_data['inputs_flag'])
|
||||
assert np.all(replayed_data['sensors_flag'] == orig_data['sensors_flag'])
|
||||
|
||||
def test_consistent_timing_spikes(self):
|
||||
"""
|
||||
Test: consistent timing spikes for N accelerometer messages in the middle of the segment
|
||||
Expected Result: inputsOK becomes False after N of bad measurements
|
||||
"""
|
||||
orig_data, replayed_data = run_scenarios(Scenario.SENSOR_TIMING_CONSISTENT_SPIKES, self.logs)
|
||||
assert np.diff(replayed_data['inputs_flag'])[500] == -1.0
|
||||
assert np.diff(replayed_data['inputs_flag'])[787] == 1.0
|
||||
|
||||
+11
-35
@@ -13,20 +13,6 @@ common_src = [
|
||||
"transforms/transform.cc",
|
||||
]
|
||||
|
||||
thneed_src_common = [
|
||||
"thneed/thneed_common.cc",
|
||||
"thneed/serialize.cc",
|
||||
]
|
||||
|
||||
thneed_src_qcom = thneed_src_common + ["thneed/thneed_qcom2.cc"]
|
||||
thneed_src_pc = thneed_src_common + ["thneed/thneed_pc.cc"]
|
||||
thneed_src = thneed_src_qcom if arch == "larch64" else thneed_src_pc
|
||||
|
||||
# SNPE except on Mac and ARM Linux
|
||||
snpe_lib = []
|
||||
if arch != "Darwin" and arch != "aarch64":
|
||||
common_src += ['runners/snpemodel.cc']
|
||||
snpe_lib += ['SNPE']
|
||||
|
||||
# OpenCL is a framework on Mac
|
||||
if arch == "Darwin":
|
||||
@@ -45,34 +31,24 @@ snpe_rpath_pc = f"{Dir('#').abspath}/third_party/snpe/x86_64-linux-clang"
|
||||
snpe_rpath = lenvCython['RPATH'] + [snpe_rpath_qcom if arch == "larch64" else snpe_rpath_pc]
|
||||
|
||||
cython_libs = envCython["LIBS"] + libs
|
||||
snpemodel_lib = lenv.Library('snpemodel', ['runners/snpemodel.cc'])
|
||||
commonmodel_lib = lenv.Library('commonmodel', common_src)
|
||||
|
||||
lenvCython.Program('runners/runmodel_pyx.so', 'runners/runmodel_pyx.pyx', LIBS=cython_libs, FRAMEWORKS=frameworks)
|
||||
lenvCython.Program('runners/snpemodel_pyx.so', 'runners/snpemodel_pyx.pyx', LIBS=[snpemodel_lib, snpe_lib, *cython_libs], FRAMEWORKS=frameworks, RPATH=snpe_rpath)
|
||||
lenvCython.Program('models/commonmodel_pyx.so', 'models/commonmodel_pyx.pyx', LIBS=[commonmodel_lib, *cython_libs], FRAMEWORKS=frameworks)
|
||||
|
||||
tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=env.Dir("#").abspath)]
|
||||
tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=env.Dir("#").abspath) if 'pycache' not in x]
|
||||
|
||||
# Get model metadata
|
||||
fn = File("models/supercombo").abspath
|
||||
cmd = f'python3 {Dir("#selfdrive/modeld").abspath}/get_model_metadata.py {fn}.onnx'
|
||||
lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files, cmd)
|
||||
|
||||
# Build thneed model
|
||||
if arch == "larch64" or GetOption('pc_thneed'):
|
||||
tinygrad_opts = []
|
||||
if not GetOption('pc_thneed'):
|
||||
# use FLOAT16 on device for speed + don't cache the CL kernels for space
|
||||
tinygrad_opts += ["FLOAT16=1", "PYOPENCL_NO_CACHE=1"]
|
||||
cmd = f"cd {Dir('#').abspath}/tinygrad_repo && " + ' '.join(tinygrad_opts) + f" python3 openpilot/compile2.py {fn}.onnx {fn}.thneed"
|
||||
# Compile tinygrad model
|
||||
pythonpath_string = 'PYTHONPATH="${PYTHONPATH}:' + env.Dir("#tinygrad_repo").abspath + '"'
|
||||
if arch == 'larch64':
|
||||
device_string = 'QCOM=1'
|
||||
else:
|
||||
device_string = 'CLANG=1 IMAGE=0'
|
||||
|
||||
lenv.Command(fn + ".thneed", [fn + ".onnx"] + tinygrad_files, cmd)
|
||||
for model_name in ['supercombo', 'dmonitoring_model']:
|
||||
fn = File(f"models/{model_name}").abspath
|
||||
cmd = f'{pythonpath_string} {device_string} python3 {Dir("#tinygrad_repo").abspath}/examples/openpilot/compile3.py {fn}.onnx {fn}_tinygrad.pkl'
|
||||
lenv.Command(fn + "_tinygrad.pkl", [fn + ".onnx"] + tinygrad_files, cmd)
|
||||
|
||||
fn_dm = File("models/dmonitoring_model").abspath
|
||||
cmd = f"cd {Dir('#').abspath}/tinygrad_repo && " + ' '.join(tinygrad_opts) + f" python3 openpilot/compile2.py {fn_dm}.onnx {fn_dm}.thneed"
|
||||
lenv.Command(fn_dm + ".thneed", [fn_dm + ".onnx"] + tinygrad_files, cmd)
|
||||
|
||||
thneed_lib = env.SharedLibrary('thneed', thneed_src, LIBS=[gpucommon, common, 'OpenCL', 'dl'])
|
||||
thneedmodel_lib = env.Library('thneedmodel', ['runners/thneedmodel.cc'])
|
||||
lenvCython.Program('runners/thneedmodel_pyx.so', 'runners/thneedmodel_pyx.pyx', LIBS=envCython["LIBS"]+[thneedmodel_lib, thneed_lib, gpucommon, common, 'dl', 'OpenCL'])
|
||||
|
||||
@@ -1,10 +1,4 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" >/dev/null && pwd)"
|
||||
cd "$DIR/../../"
|
||||
|
||||
if [ -f "$DIR/libthneed.so" ]; then
|
||||
export LD_PRELOAD="$DIR/libthneed.so"
|
||||
fi
|
||||
|
||||
exec "$DIR/dmonitoringmodeld.py" "$@"
|
||||
|
||||
@@ -1,8 +1,17 @@
|
||||
#!/usr/bin/env python3
|
||||
import os
|
||||
from openpilot.system.hardware import TICI
|
||||
if TICI:
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.dtype import dtypes
|
||||
from openpilot.selfdrive.modeld.runners.tinygrad_helpers import qcom_tensor_from_opencl_address
|
||||
os.environ['QCOM'] = '1'
|
||||
else:
|
||||
from openpilot.selfdrive.modeld.runners.ort_helpers import make_onnx_cpu_runner
|
||||
import gc
|
||||
import math
|
||||
import time
|
||||
import pickle
|
||||
import ctypes
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
@@ -12,23 +21,21 @@ from cereal import messaging
|
||||
from cereal.messaging import PubMaster, SubMaster
|
||||
from msgq.visionipc import VisionIpcClient, VisionStreamType, VisionBuf
|
||||
from openpilot.common.swaglog import cloudlog
|
||||
from openpilot.common.params import Params
|
||||
from openpilot.common.realtime import set_realtime_priority
|
||||
from openpilot.selfdrive.modeld.runners import ModelRunner, Runtime
|
||||
from openpilot.selfdrive.modeld.models.commonmodel_pyx import CLContext
|
||||
from openpilot.common.transformations.model import dmonitoringmodel_intrinsics, DM_INPUT_SIZE
|
||||
from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
|
||||
from openpilot.selfdrive.modeld.models.commonmodel_pyx import CLContext, MonitoringModelFrame
|
||||
from openpilot.selfdrive.modeld.parse_model_outputs import sigmoid
|
||||
|
||||
MODEL_WIDTH, MODEL_HEIGHT = DM_INPUT_SIZE
|
||||
CALIB_LEN = 3
|
||||
MODEL_WIDTH = 1440
|
||||
MODEL_HEIGHT = 960
|
||||
FEATURE_LEN = 512
|
||||
OUTPUT_SIZE = 84 + FEATURE_LEN
|
||||
|
||||
PROCESS_NAME = "selfdrive.modeld.dmonitoringmodeld"
|
||||
SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
|
||||
MODEL_PATHS = {
|
||||
ModelRunner.THNEED: Path(__file__).parent / 'models/dmonitoring_model.thneed',
|
||||
ModelRunner.ONNX: Path(__file__).parent / 'models/dmonitoring_model.onnx'}
|
||||
MODEL_PATH = Path(__file__).parent / 'models/dmonitoring_model.onnx'
|
||||
MODEL_PKL_PATH = Path(__file__).parent / 'models/dmonitoring_model_tinygrad.pkl'
|
||||
|
||||
class DriverStateResult(ctypes.Structure):
|
||||
_fields_ = [
|
||||
@@ -59,33 +66,42 @@ class DMonitoringModelResult(ctypes.Structure):
|
||||
class ModelState:
|
||||
inputs: dict[str, np.ndarray]
|
||||
output: np.ndarray
|
||||
model: ModelRunner
|
||||
|
||||
def __init__(self, cl_ctx):
|
||||
assert ctypes.sizeof(DMonitoringModelResult) == OUTPUT_SIZE * ctypes.sizeof(ctypes.c_float)
|
||||
self.output = np.zeros(OUTPUT_SIZE, dtype=np.float32)
|
||||
self.inputs = {
|
||||
'input_img': np.zeros(MODEL_HEIGHT * MODEL_WIDTH, dtype=np.uint8),
|
||||
'calib': np.zeros(CALIB_LEN, dtype=np.float32)}
|
||||
|
||||
self.model = ModelRunner(MODEL_PATHS, self.output, Runtime.GPU, False, cl_ctx)
|
||||
self.model.addInput("input_img", None)
|
||||
self.model.addInput("calib", self.inputs['calib'])
|
||||
self.frame = MonitoringModelFrame(cl_ctx)
|
||||
self.numpy_inputs = {
|
||||
'calib': np.zeros((1, CALIB_LEN), dtype=np.float32),
|
||||
}
|
||||
|
||||
def run(self, buf:VisionBuf, calib:np.ndarray) -> tuple[np.ndarray, float]:
|
||||
self.inputs['calib'][:] = calib
|
||||
if TICI:
|
||||
self.tensor_inputs = {k: Tensor(v, device='NPY').realize() for k,v in self.numpy_inputs.items()}
|
||||
with open(MODEL_PKL_PATH, "rb") as f:
|
||||
self.model_run = pickle.load(f)
|
||||
else:
|
||||
self.onnx_cpu_runner = make_onnx_cpu_runner(MODEL_PATH)
|
||||
|
||||
v_offset = buf.height - MODEL_HEIGHT
|
||||
h_offset = (buf.width - MODEL_WIDTH) // 2
|
||||
buf_data = buf.data.reshape(-1, buf.stride)
|
||||
input_data = self.inputs['input_img'].reshape(MODEL_HEIGHT, MODEL_WIDTH)
|
||||
input_data[:] = buf_data[v_offset:v_offset+MODEL_HEIGHT, h_offset:h_offset+MODEL_WIDTH]
|
||||
def run(self, buf:VisionBuf, calib:np.ndarray, transform:np.ndarray) -> tuple[np.ndarray, float]:
|
||||
self.numpy_inputs['calib'][0,:] = calib
|
||||
|
||||
self.model.setInputBuffer("input_img", self.inputs['input_img'].view(np.float32))
|
||||
t1 = time.perf_counter()
|
||||
self.model.execute()
|
||||
|
||||
input_img_cl = self.frame.prepare(buf, transform.flatten())
|
||||
if TICI:
|
||||
# The imgs tensors are backed by opencl memory, only need init once
|
||||
if 'input_img' not in self.tensor_inputs:
|
||||
self.tensor_inputs['input_img'] = qcom_tensor_from_opencl_address(input_img_cl.mem_address, (1, MODEL_WIDTH*MODEL_HEIGHT), dtype=dtypes.uint8)
|
||||
else:
|
||||
self.numpy_inputs['input_img'] = self.frame.buffer_from_cl(input_img_cl).reshape((1, MODEL_WIDTH*MODEL_HEIGHT))
|
||||
|
||||
if TICI:
|
||||
output = self.model_run(**self.tensor_inputs).numpy().flatten()
|
||||
else:
|
||||
output = self.onnx_cpu_runner.run(None, self.numpy_inputs)[0].flatten()
|
||||
|
||||
t2 = time.perf_counter()
|
||||
return self.output, t2 - t1
|
||||
return output, t2 - t1
|
||||
|
||||
|
||||
def fill_driver_state(msg, ds_result: DriverStateResult):
|
||||
@@ -126,7 +142,6 @@ def main():
|
||||
cl_context = CLContext()
|
||||
model = ModelState(cl_context)
|
||||
cloudlog.warning("models loaded, dmonitoringmodeld starting")
|
||||
Params().put_bool("DmModelInitialized", True)
|
||||
|
||||
cloudlog.warning("connecting to driver stream")
|
||||
vipc_client = VisionIpcClient("camerad", VisionStreamType.VISION_STREAM_DRIVER, True, cl_context)
|
||||
@@ -139,18 +154,23 @@ def main():
|
||||
pm = PubMaster(["driverStateV2"])
|
||||
|
||||
calib = np.zeros(CALIB_LEN, dtype=np.float32)
|
||||
model_transform = None
|
||||
|
||||
while True:
|
||||
buf = vipc_client.recv()
|
||||
if buf is None:
|
||||
continue
|
||||
|
||||
if model_transform is None:
|
||||
cam = _os_fisheye if buf.width == _os_fisheye.width else _ar_ox_fisheye
|
||||
model_transform = np.linalg.inv(np.dot(dmonitoringmodel_intrinsics, np.linalg.inv(cam.intrinsics))).astype(np.float32)
|
||||
|
||||
sm.update(0)
|
||||
if sm.updated["liveCalibration"]:
|
||||
calib[:] = np.array(sm["liveCalibration"].rpyCalib)
|
||||
|
||||
t1 = time.perf_counter()
|
||||
model_output, gpu_execution_time = model.run(buf, calib)
|
||||
model_output, gpu_execution_time = model.run(buf, calib, model_transform)
|
||||
t2 = time.perf_counter()
|
||||
|
||||
pm.send("driverStateV2", get_driverstate_packet(model_output, vipc_client.frame_id, vipc_client.timestamp_sof, t2 - t1, gpu_execution_time))
|
||||
|
||||
@@ -3,11 +3,22 @@ import capnp
|
||||
import numpy as np
|
||||
from cereal import log
|
||||
from openpilot.selfdrive.modeld.constants import ModelConstants, Plan, Meta
|
||||
from openpilot.selfdrive.controls.lib.drive_helpers import MIN_SPEED
|
||||
|
||||
SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
|
||||
|
||||
ConfidenceClass = log.ModelDataV2.ConfidenceClass
|
||||
|
||||
def curv_from_psis(psi_target, psi_rate, vego, delay):
|
||||
vego = np.clip(vego, MIN_SPEED, np.inf)
|
||||
curv_from_psi = psi_target / (vego * delay) # epsilon to prevent divide-by-zero
|
||||
return 2*curv_from_psi - psi_rate / vego
|
||||
|
||||
def get_curvature_from_plan(plan, vego, delay):
|
||||
psi_target = np.interp(delay, ModelConstants.T_IDXS, plan[:, Plan.T_FROM_CURRENT_EULER][:, 2])
|
||||
psi_rate = plan[:, Plan.ORIENTATION_RATE][0, 2]
|
||||
return curv_from_psis(psi_target, psi_rate, vego, delay)
|
||||
|
||||
class PublishState:
|
||||
def __init__(self):
|
||||
self.disengage_buffer = np.zeros(ModelConstants.CONFIDENCE_BUFFER_LEN*ModelConstants.DISENGAGE_WIDTH, dtype=np.float32)
|
||||
@@ -55,14 +66,17 @@ def fill_lane_line_meta(builder, lane_lines, lane_line_probs):
|
||||
builder.rightProb = lane_line_probs[2]
|
||||
|
||||
def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._DynamicStructBuilder,
|
||||
net_output_data: dict[str, np.ndarray], publish_state: PublishState,
|
||||
vipc_frame_id: int, vipc_frame_id_extra: int, frame_id: int, frame_drop: float,
|
||||
timestamp_eof: int, model_execution_time: float, valid: bool) -> None:
|
||||
net_output_data: dict[str, np.ndarray], v_ego: float, delay: float,
|
||||
publish_state: PublishState, vipc_frame_id: int, vipc_frame_id_extra: int,
|
||||
frame_id: int, frame_drop: float, timestamp_eof: int, model_execution_time: float,
|
||||
valid: bool) -> None:
|
||||
frame_age = frame_id - vipc_frame_id if frame_id > vipc_frame_id else 0
|
||||
frame_drop_perc = frame_drop * 100
|
||||
extended_msg.valid = valid
|
||||
base_msg.valid = valid
|
||||
|
||||
desired_curv = float(get_curvature_from_plan(net_output_data['plan'][0], v_ego, delay))
|
||||
|
||||
driving_model_data = base_msg.drivingModelData
|
||||
|
||||
driving_model_data.frameId = vipc_frame_id
|
||||
@@ -71,7 +85,7 @@ def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._D
|
||||
driving_model_data.modelExecutionTime = model_execution_time
|
||||
|
||||
action = driving_model_data.action
|
||||
action.desiredCurvature = float(net_output_data['desired_curvature'][0,0])
|
||||
action.desiredCurvature = desired_curv
|
||||
|
||||
modelV2 = extended_msg.modelV2
|
||||
modelV2.frameId = vipc_frame_id
|
||||
@@ -106,7 +120,7 @@ def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._D
|
||||
|
||||
# lateral planning
|
||||
action = modelV2.action
|
||||
action.desiredCurvature = float(net_output_data['desired_curvature'][0,0])
|
||||
action.desiredCurvature = desired_curv
|
||||
|
||||
# times at X_IDXS according to model plan
|
||||
PLAN_T_IDXS = [np.nan] * ModelConstants.IDX_N
|
||||
|
||||
@@ -1,10 +1,4 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" >/dev/null && pwd)"
|
||||
cd "$DIR/../../"
|
||||
|
||||
if [ -f "$DIR/libthneed.so" ]; then
|
||||
export LD_PRELOAD="$DIR/libthneed.so"
|
||||
fi
|
||||
|
||||
exec "$DIR/modeld.py" "$@"
|
||||
|
||||
+47
-40
@@ -1,5 +1,15 @@
|
||||
#!/usr/bin/env python3
|
||||
import os
|
||||
from openpilot.system.hardware import TICI
|
||||
|
||||
#
|
||||
if TICI:
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.dtype import dtypes
|
||||
from openpilot.selfdrive.modeld.runners.tinygrad_helpers import qcom_tensor_from_opencl_address
|
||||
os.environ['QCOM'] = '1'
|
||||
else:
|
||||
from openpilot.selfdrive.modeld.runners.ort_helpers import make_onnx_cpu_runner
|
||||
import time
|
||||
import pickle
|
||||
import numpy as np
|
||||
@@ -18,22 +28,19 @@ from openpilot.common.transformations.camera import DEVICE_CAMERAS
|
||||
from openpilot.common.transformations.model import get_warp_matrix
|
||||
from openpilot.system import sentry
|
||||
from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
|
||||
from openpilot.selfdrive.modeld.runners import ModelRunner, Runtime
|
||||
from openpilot.selfdrive.modeld.parse_model_outputs import Parser
|
||||
from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState
|
||||
from openpilot.selfdrive.modeld.constants import ModelConstants
|
||||
from openpilot.selfdrive.modeld.models.commonmodel_pyx import ModelFrame, CLContext
|
||||
from openpilot.selfdrive.modeld.models.commonmodel_pyx import DrivingModelFrame, CLContext
|
||||
|
||||
|
||||
PROCESS_NAME = "selfdrive.modeld.modeld"
|
||||
SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
|
||||
|
||||
MODEL_PATHS = {
|
||||
ModelRunner.THNEED: Path(__file__).parent / 'models/supercombo.thneed',
|
||||
ModelRunner.ONNX: Path(__file__).parent / 'models/supercombo.onnx'}
|
||||
|
||||
MODEL_PATH = Path(__file__).parent / 'models/supercombo.onnx'
|
||||
MODEL_PKL_PATH = Path(__file__).parent / 'models/supercombo_tinygrad.pkl'
|
||||
METADATA_PATH = Path(__file__).parent / 'models/supercombo_metadata.pkl'
|
||||
|
||||
|
||||
class FrameMeta:
|
||||
frame_id: int = 0
|
||||
timestamp_sof: int = 0
|
||||
@@ -44,43 +51,39 @@ class FrameMeta:
|
||||
self.frame_id, self.timestamp_sof, self.timestamp_eof = vipc.frame_id, vipc.timestamp_sof, vipc.timestamp_eof
|
||||
|
||||
class ModelState:
|
||||
frame: ModelFrame
|
||||
wide_frame: ModelFrame
|
||||
frames: dict[str, DrivingModelFrame]
|
||||
inputs: dict[str, np.ndarray]
|
||||
output: np.ndarray
|
||||
prev_desire: np.ndarray # for tracking the rising edge of the pulse
|
||||
model: ModelRunner
|
||||
|
||||
def __init__(self, context: CLContext):
|
||||
self.frame = ModelFrame(context)
|
||||
self.wide_frame = ModelFrame(context)
|
||||
self.frames = {'input_imgs': DrivingModelFrame(context), 'big_input_imgs': DrivingModelFrame(context)}
|
||||
self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32)
|
||||
self.full_features_20Hz = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.FEATURE_LEN), dtype=np.float32)
|
||||
self.desire_20Hz = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN + 1, ModelConstants.DESIRE_LEN), dtype=np.float32)
|
||||
self.prev_desired_curv_20hz = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN + 1, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32)
|
||||
|
||||
# img buffers are managed in openCL transform code
|
||||
self.inputs = {
|
||||
'desire': np.zeros(ModelConstants.DESIRE_LEN * (ModelConstants.HISTORY_BUFFER_LEN+1), dtype=np.float32),
|
||||
'traffic_convention': np.zeros(ModelConstants.TRAFFIC_CONVENTION_LEN, dtype=np.float32),
|
||||
'lateral_control_params': np.zeros(ModelConstants.LATERAL_CONTROL_PARAMS_LEN, dtype=np.float32),
|
||||
'prev_desired_curv': np.zeros(ModelConstants.PREV_DESIRED_CURV_LEN * (ModelConstants.HISTORY_BUFFER_LEN+1), dtype=np.float32),
|
||||
'features_buffer': np.zeros(ModelConstants.HISTORY_BUFFER_LEN * ModelConstants.FEATURE_LEN, dtype=np.float32),
|
||||
self.numpy_inputs = {
|
||||
'desire': np.zeros((1, (ModelConstants.HISTORY_BUFFER_LEN+1), ModelConstants.DESIRE_LEN), dtype=np.float32),
|
||||
'traffic_convention': np.zeros((1, ModelConstants.TRAFFIC_CONVENTION_LEN), dtype=np.float32),
|
||||
'features_buffer': np.zeros((1, ModelConstants.HISTORY_BUFFER_LEN, ModelConstants.FEATURE_LEN), dtype=np.float32),
|
||||
}
|
||||
|
||||
with open(METADATA_PATH, 'rb') as f:
|
||||
model_metadata = pickle.load(f)
|
||||
self.input_shapes = model_metadata['input_shapes']
|
||||
|
||||
self.output_slices = model_metadata['output_slices']
|
||||
net_output_size = model_metadata['output_shapes']['outputs'][1]
|
||||
self.output = np.zeros(net_output_size, dtype=np.float32)
|
||||
self.parser = Parser()
|
||||
|
||||
self.model = ModelRunner(MODEL_PATHS, self.output, Runtime.GPU, False, context)
|
||||
self.model.addInput("input_imgs", None)
|
||||
self.model.addInput("big_input_imgs", None)
|
||||
for k,v in self.inputs.items():
|
||||
self.model.addInput(k, v)
|
||||
if TICI:
|
||||
self.tensor_inputs = {k: Tensor(v, device='NPY').realize() for k,v in self.numpy_inputs.items()}
|
||||
with open(MODEL_PKL_PATH, "rb") as f:
|
||||
self.model_run = pickle.load(f)
|
||||
else:
|
||||
self.onnx_cpu_runner = make_onnx_cpu_runner(MODEL_PATH)
|
||||
|
||||
def slice_outputs(self, model_outputs: np.ndarray) -> dict[str, np.ndarray]:
|
||||
parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in self.output_slices.items()}
|
||||
@@ -97,30 +100,36 @@ class ModelState:
|
||||
|
||||
self.desire_20Hz[:-1] = self.desire_20Hz[1:]
|
||||
self.desire_20Hz[-1] = new_desire
|
||||
self.inputs['desire'][:] = self.desire_20Hz.reshape((25,4,-1)).max(axis=1).flatten()
|
||||
self.numpy_inputs['desire'][:] = self.desire_20Hz.reshape((1,25,4,-1)).max(axis=2)
|
||||
|
||||
self.inputs['traffic_convention'][:] = inputs['traffic_convention']
|
||||
self.inputs['lateral_control_params'][:] = inputs['lateral_control_params']
|
||||
self.numpy_inputs['traffic_convention'][:] = inputs['traffic_convention']
|
||||
imgs_cl = {'input_imgs': self.frames['input_imgs'].prepare(buf, transform.flatten()),
|
||||
'big_input_imgs': self.frames['big_input_imgs'].prepare(wbuf, transform_wide.flatten())}
|
||||
|
||||
self.model.setInputBuffer("input_imgs", self.frame.prepare(buf, transform.flatten(), self.model.getCLBuffer("input_imgs")))
|
||||
self.model.setInputBuffer("big_input_imgs", self.wide_frame.prepare(wbuf, transform_wide.flatten(), self.model.getCLBuffer("big_input_imgs")))
|
||||
if TICI:
|
||||
# The imgs tensors are backed by opencl memory, only need init once
|
||||
for key in imgs_cl:
|
||||
if key not in self.tensor_inputs:
|
||||
self.tensor_inputs[key] = qcom_tensor_from_opencl_address(imgs_cl[key].mem_address, self.input_shapes[key], dtype=dtypes.uint8)
|
||||
else:
|
||||
for key in imgs_cl:
|
||||
self.numpy_inputs[key] = self.frames[key].buffer_from_cl(imgs_cl[key]).reshape(self.input_shapes[key])
|
||||
|
||||
if prepare_only:
|
||||
return None
|
||||
|
||||
self.model.execute()
|
||||
if TICI:
|
||||
self.output = self.model_run(**self.tensor_inputs).numpy().flatten()
|
||||
else:
|
||||
self.output = self.onnx_cpu_runner.run(None, self.numpy_inputs)[0].flatten()
|
||||
|
||||
outputs = self.parser.parse_outputs(self.slice_outputs(self.output))
|
||||
|
||||
self.full_features_20Hz[:-1] = self.full_features_20Hz[1:]
|
||||
self.full_features_20Hz[-1] = outputs['hidden_state'][0, :]
|
||||
|
||||
self.prev_desired_curv_20hz[:-1] = self.prev_desired_curv_20hz[1:]
|
||||
self.prev_desired_curv_20hz[-1] = outputs['desired_curvature'][0, :]
|
||||
|
||||
idxs = np.arange(-4,-100,-4)[::-1]
|
||||
self.inputs['features_buffer'][:] = self.full_features_20Hz[idxs].flatten()
|
||||
# TODO model only uses last value now, once that changes we need to input strided action history buffer
|
||||
self.inputs['prev_desired_curv'][-ModelConstants.PREV_DESIRED_CURV_LEN:] = 0. * self.prev_desired_curv_20hz[-4, :]
|
||||
self.numpy_inputs['features_buffer'][:] = self.full_features_20Hz[idxs]
|
||||
return outputs
|
||||
|
||||
|
||||
@@ -231,7 +240,6 @@ def main(demo=False):
|
||||
is_rhd = sm["driverMonitoringState"].isRHD
|
||||
frame_id = sm["roadCameraState"].frameId
|
||||
v_ego = max(sm["carState"].vEgo, 0.)
|
||||
lateral_control_params = np.array([v_ego, steer_delay], dtype=np.float32)
|
||||
if sm.updated["liveCalibration"] and sm.seen['roadCameraState'] and sm.seen['deviceState']:
|
||||
device_from_calib_euler = np.array(sm["liveCalibration"].rpyCalib, dtype=np.float32)
|
||||
dc = DEVICE_CAMERAS[(str(sm['deviceState'].deviceType), str(sm['roadCameraState'].sensor))]
|
||||
@@ -262,7 +270,6 @@ def main(demo=False):
|
||||
inputs:dict[str, np.ndarray] = {
|
||||
'desire': vec_desire,
|
||||
'traffic_convention': traffic_convention,
|
||||
'lateral_control_params': lateral_control_params,
|
||||
}
|
||||
|
||||
mt1 = time.perf_counter()
|
||||
@@ -274,7 +281,8 @@ def main(demo=False):
|
||||
modelv2_send = messaging.new_message('modelV2')
|
||||
drivingdata_send = messaging.new_message('drivingModelData')
|
||||
posenet_send = messaging.new_message('cameraOdometry')
|
||||
fill_model_msg(drivingdata_send, modelv2_send, model_output, publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
|
||||
fill_model_msg(drivingdata_send, modelv2_send, model_output, v_ego, steer_delay,
|
||||
publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
|
||||
frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, live_calib_seen)
|
||||
|
||||
desire_state = modelv2_send.modelV2.meta.desireState
|
||||
@@ -291,7 +299,6 @@ def main(demo=False):
|
||||
pm.send('modelV2', modelv2_send)
|
||||
pm.send('drivingModelData', drivingdata_send)
|
||||
pm.send('cameraOdometry', posenet_send)
|
||||
|
||||
last_vipc_frame_id = meta_main.frame_id
|
||||
|
||||
|
||||
|
||||
@@ -1,58 +1,61 @@
|
||||
#include "selfdrive/modeld/models/commonmodel.h"
|
||||
|
||||
#include <cassert>
|
||||
#include <cmath>
|
||||
#include <cstring>
|
||||
|
||||
#include "common/clutil.h"
|
||||
|
||||
ModelFrame::ModelFrame(cl_device_id device_id, cl_context context) {
|
||||
DrivingModelFrame::DrivingModelFrame(cl_device_id device_id, cl_context context) : ModelFrame(device_id, context) {
|
||||
input_frames = std::make_unique<uint8_t[]>(buf_size);
|
||||
|
||||
q = CL_CHECK_ERR(clCreateCommandQueue(context, device_id, 0, &err));
|
||||
y_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, MODEL_WIDTH * MODEL_HEIGHT, NULL, &err));
|
||||
u_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, (MODEL_WIDTH / 2) * (MODEL_HEIGHT / 2), NULL, &err));
|
||||
v_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, (MODEL_WIDTH / 2) * (MODEL_HEIGHT / 2), NULL, &err));
|
||||
input_frames_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, buf_size, NULL, &err));
|
||||
img_buffer_20hz_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, 5*frame_size_bytes, NULL, &err));
|
||||
region.origin = 4 * frame_size_bytes;
|
||||
region.size = frame_size_bytes;
|
||||
last_img_cl = CL_CHECK_ERR(clCreateSubBuffer(img_buffer_20hz_cl, CL_MEM_READ_WRITE, CL_BUFFER_CREATE_TYPE_REGION, ®ion, &err));
|
||||
|
||||
transform_init(&transform, context, device_id);
|
||||
loadyuv_init(&loadyuv, context, device_id, MODEL_WIDTH, MODEL_HEIGHT);
|
||||
init_transform(device_id, context, MODEL_WIDTH, MODEL_HEIGHT);
|
||||
}
|
||||
|
||||
uint8_t* ModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3 &projection, cl_mem *output) {
|
||||
transform_queue(&this->transform, q,
|
||||
yuv_cl, frame_width, frame_height, frame_stride, frame_uv_offset,
|
||||
y_cl, u_cl, v_cl, MODEL_WIDTH, MODEL_HEIGHT, projection);
|
||||
cl_mem* DrivingModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) {
|
||||
run_transform(yuv_cl, MODEL_WIDTH, MODEL_HEIGHT, frame_width, frame_height, frame_stride, frame_uv_offset, projection);
|
||||
|
||||
for (int i = 0; i < 4; i++) {
|
||||
CL_CHECK(clEnqueueCopyBuffer(q, img_buffer_20hz_cl, img_buffer_20hz_cl, (i+1)*frame_size_bytes, i*frame_size_bytes, frame_size_bytes, 0, nullptr, nullptr));
|
||||
}
|
||||
loadyuv_queue(&loadyuv, q, y_cl, u_cl, v_cl, last_img_cl);
|
||||
if (output == NULL) {
|
||||
CL_CHECK(clEnqueueReadBuffer(q, img_buffer_20hz_cl, CL_TRUE, 0, frame_size_bytes, &input_frames[0], 0, nullptr, nullptr));
|
||||
CL_CHECK(clEnqueueReadBuffer(q, last_img_cl, CL_TRUE, 0, frame_size_bytes, &input_frames[MODEL_FRAME_SIZE], 0, nullptr, nullptr));
|
||||
clFinish(q);
|
||||
return &input_frames[0];
|
||||
} else {
|
||||
copy_queue(&loadyuv, q, img_buffer_20hz_cl, *output, 0, 0, frame_size_bytes);
|
||||
copy_queue(&loadyuv, q, last_img_cl, *output, 0, frame_size_bytes, frame_size_bytes);
|
||||
|
||||
// NOTE: Since thneed is using a different command queue, this clFinish is needed to ensure the image is ready.
|
||||
clFinish(q);
|
||||
return NULL;
|
||||
}
|
||||
copy_queue(&loadyuv, q, img_buffer_20hz_cl, input_frames_cl, 0, 0, frame_size_bytes);
|
||||
copy_queue(&loadyuv, q, last_img_cl, input_frames_cl, 0, frame_size_bytes, frame_size_bytes);
|
||||
|
||||
// NOTE: Since thneed is using a different command queue, this clFinish is needed to ensure the image is ready.
|
||||
clFinish(q);
|
||||
return &input_frames_cl;
|
||||
}
|
||||
|
||||
ModelFrame::~ModelFrame() {
|
||||
transform_destroy(&transform);
|
||||
DrivingModelFrame::~DrivingModelFrame() {
|
||||
deinit_transform();
|
||||
loadyuv_destroy(&loadyuv);
|
||||
CL_CHECK(clReleaseMemObject(img_buffer_20hz_cl));
|
||||
CL_CHECK(clReleaseMemObject(last_img_cl));
|
||||
CL_CHECK(clReleaseMemObject(v_cl));
|
||||
CL_CHECK(clReleaseMemObject(u_cl));
|
||||
CL_CHECK(clReleaseMemObject(y_cl));
|
||||
CL_CHECK(clReleaseCommandQueue(q));
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
MonitoringModelFrame::MonitoringModelFrame(cl_device_id device_id, cl_context context) : ModelFrame(device_id, context) {
|
||||
input_frames = std::make_unique<uint8_t[]>(buf_size);
|
||||
input_frame_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, buf_size, NULL, &err));
|
||||
|
||||
init_transform(device_id, context, MODEL_WIDTH, MODEL_HEIGHT);
|
||||
}
|
||||
|
||||
cl_mem* MonitoringModelFrame::prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) {
|
||||
run_transform(yuv_cl, MODEL_WIDTH, MODEL_HEIGHT, frame_width, frame_height, frame_stride, frame_uv_offset, projection);
|
||||
clFinish(q);
|
||||
return &y_cl;
|
||||
}
|
||||
|
||||
MonitoringModelFrame::~MonitoringModelFrame() {
|
||||
deinit_transform();
|
||||
CL_CHECK(clReleaseCommandQueue(q));
|
||||
}
|
||||
|
||||
@@ -2,6 +2,7 @@
|
||||
|
||||
#include <cfloat>
|
||||
#include <cstdlib>
|
||||
#include <cassert>
|
||||
|
||||
#include <memory>
|
||||
|
||||
@@ -18,9 +19,54 @@
|
||||
|
||||
class ModelFrame {
|
||||
public:
|
||||
ModelFrame(cl_device_id device_id, cl_context context);
|
||||
~ModelFrame();
|
||||
uint8_t* prepare(cl_mem yuv_cl, int width, int height, int frame_stride, int frame_uv_offset, const mat3& transform, cl_mem *output);
|
||||
ModelFrame(cl_device_id device_id, cl_context context) {
|
||||
q = CL_CHECK_ERR(clCreateCommandQueue(context, device_id, 0, &err));
|
||||
}
|
||||
virtual ~ModelFrame() {}
|
||||
virtual cl_mem* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) { return NULL; }
|
||||
uint8_t* buffer_from_cl(cl_mem *in_frames, int buffer_size) {
|
||||
CL_CHECK(clEnqueueReadBuffer(q, *in_frames, CL_TRUE, 0, buffer_size, input_frames.get(), 0, nullptr, nullptr));
|
||||
clFinish(q);
|
||||
return &input_frames[0];
|
||||
}
|
||||
|
||||
int MODEL_WIDTH;
|
||||
int MODEL_HEIGHT;
|
||||
int MODEL_FRAME_SIZE;
|
||||
int buf_size;
|
||||
|
||||
protected:
|
||||
cl_mem y_cl, u_cl, v_cl;
|
||||
Transform transform;
|
||||
cl_command_queue q;
|
||||
std::unique_ptr<uint8_t[]> input_frames;
|
||||
|
||||
void init_transform(cl_device_id device_id, cl_context context, int model_width, int model_height) {
|
||||
y_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, model_width * model_height, NULL, &err));
|
||||
u_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, (model_width / 2) * (model_height / 2), NULL, &err));
|
||||
v_cl = CL_CHECK_ERR(clCreateBuffer(context, CL_MEM_READ_WRITE, (model_width / 2) * (model_height / 2), NULL, &err));
|
||||
transform_init(&transform, context, device_id);
|
||||
}
|
||||
|
||||
void deinit_transform() {
|
||||
transform_destroy(&transform);
|
||||
CL_CHECK(clReleaseMemObject(v_cl));
|
||||
CL_CHECK(clReleaseMemObject(u_cl));
|
||||
CL_CHECK(clReleaseMemObject(y_cl));
|
||||
}
|
||||
|
||||
void run_transform(cl_mem yuv_cl, int model_width, int model_height, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection) {
|
||||
transform_queue(&transform, q,
|
||||
yuv_cl, frame_width, frame_height, frame_stride, frame_uv_offset,
|
||||
y_cl, u_cl, v_cl, model_width, model_height, projection);
|
||||
}
|
||||
};
|
||||
|
||||
class DrivingModelFrame : public ModelFrame {
|
||||
public:
|
||||
DrivingModelFrame(cl_device_id device_id, cl_context context);
|
||||
~DrivingModelFrame();
|
||||
cl_mem* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection);
|
||||
|
||||
const int MODEL_WIDTH = 512;
|
||||
const int MODEL_HEIGHT = 256;
|
||||
@@ -29,10 +75,22 @@ public:
|
||||
const size_t frame_size_bytes = MODEL_FRAME_SIZE * sizeof(uint8_t);
|
||||
|
||||
private:
|
||||
Transform transform;
|
||||
LoadYUVState loadyuv;
|
||||
cl_command_queue q;
|
||||
cl_mem y_cl, u_cl, v_cl, img_buffer_20hz_cl, last_img_cl;
|
||||
cl_mem img_buffer_20hz_cl, last_img_cl, input_frames_cl;
|
||||
cl_buffer_region region;
|
||||
std::unique_ptr<uint8_t[]> input_frames;
|
||||
};
|
||||
};
|
||||
|
||||
class MonitoringModelFrame : public ModelFrame {
|
||||
public:
|
||||
MonitoringModelFrame(cl_device_id device_id, cl_context context);
|
||||
~MonitoringModelFrame();
|
||||
cl_mem* prepare(cl_mem yuv_cl, int frame_width, int frame_height, int frame_stride, int frame_uv_offset, const mat3& projection);
|
||||
|
||||
const int MODEL_WIDTH = 1440;
|
||||
const int MODEL_HEIGHT = 960;
|
||||
const int MODEL_FRAME_SIZE = MODEL_WIDTH * MODEL_HEIGHT;
|
||||
const int buf_size = MODEL_FRAME_SIZE;
|
||||
|
||||
private:
|
||||
cl_mem input_frame_cl;
|
||||
};
|
||||
|
||||
@@ -14,5 +14,13 @@ cdef extern from "common/clutil.h":
|
||||
cdef extern from "selfdrive/modeld/models/commonmodel.h":
|
||||
cppclass ModelFrame:
|
||||
int buf_size
|
||||
ModelFrame(cl_device_id, cl_context)
|
||||
unsigned char * prepare(cl_mem, int, int, int, int, mat3, cl_mem*)
|
||||
unsigned char * buffer_from_cl(cl_mem*, int);
|
||||
cl_mem * prepare(cl_mem, int, int, int, int, mat3)
|
||||
|
||||
cppclass DrivingModelFrame:
|
||||
int buf_size
|
||||
DrivingModelFrame(cl_device_id, cl_context)
|
||||
|
||||
cppclass MonitoringModelFrame:
|
||||
int buf_size
|
||||
MonitoringModelFrame(cl_device_id, cl_context)
|
||||
|
||||
@@ -4,11 +4,12 @@
|
||||
import numpy as np
|
||||
cimport numpy as cnp
|
||||
from libc.string cimport memcpy
|
||||
from libc.stdint cimport uintptr_t
|
||||
|
||||
from msgq.visionipc.visionipc cimport cl_mem
|
||||
from msgq.visionipc.visionipc_pyx cimport VisionBuf, CLContext as BaseCLContext
|
||||
from .commonmodel cimport CL_DEVICE_TYPE_DEFAULT, cl_get_device_id, cl_create_context
|
||||
from .commonmodel cimport mat3, ModelFrame as cppModelFrame
|
||||
from .commonmodel cimport mat3, ModelFrame as cppModelFrame, DrivingModelFrame as cppDrivingModelFrame, MonitoringModelFrame as cppMonitoringModelFrame
|
||||
|
||||
|
||||
cdef class CLContext(BaseCLContext):
|
||||
@@ -23,23 +24,47 @@ cdef class CLMem:
|
||||
mem.mem = <cl_mem*> cmem
|
||||
return mem
|
||||
|
||||
@property
|
||||
def mem_address(self):
|
||||
return <uintptr_t>(self.mem)
|
||||
|
||||
def cl_from_visionbuf(VisionBuf buf):
|
||||
return CLMem.create(<void*>&buf.buf.buf_cl)
|
||||
|
||||
|
||||
cdef class ModelFrame:
|
||||
cdef cppModelFrame * frame
|
||||
|
||||
def __cinit__(self, CLContext context):
|
||||
self.frame = new cppModelFrame(context.device_id, context.context)
|
||||
cdef int buf_size
|
||||
|
||||
def __dealloc__(self):
|
||||
del self.frame
|
||||
|
||||
def prepare(self, VisionBuf buf, float[:] projection, CLMem output):
|
||||
def prepare(self, VisionBuf buf, float[:] projection):
|
||||
cdef mat3 cprojection
|
||||
memcpy(cprojection.v, &projection[0], 9*sizeof(float))
|
||||
cdef unsigned char * data
|
||||
if output is None:
|
||||
data = self.frame.prepare(buf.buf.buf_cl, buf.width, buf.height, buf.stride, buf.uv_offset, cprojection, NULL)
|
||||
else:
|
||||
data = self.frame.prepare(buf.buf.buf_cl, buf.width, buf.height, buf.stride, buf.uv_offset, cprojection, output.mem)
|
||||
if not data:
|
||||
return None
|
||||
return np.asarray(<cnp.uint8_t[:self.frame.buf_size]> data)
|
||||
cdef cl_mem * data
|
||||
data = self.frame.prepare(buf.buf.buf_cl, buf.width, buf.height, buf.stride, buf.uv_offset, cprojection)
|
||||
return CLMem.create(data)
|
||||
|
||||
def buffer_from_cl(self, CLMem in_frames):
|
||||
cdef unsigned char * data2
|
||||
data2 = self.frame.buffer_from_cl(in_frames.mem, self.buf_size)
|
||||
return np.asarray(<cnp.uint8_t[:self.buf_size]> data2)
|
||||
|
||||
|
||||
cdef class DrivingModelFrame(ModelFrame):
|
||||
cdef cppDrivingModelFrame * _frame
|
||||
|
||||
def __cinit__(self, CLContext context):
|
||||
self._frame = new cppDrivingModelFrame(context.device_id, context.context)
|
||||
self.frame = <cppModelFrame*>(self._frame)
|
||||
self.buf_size = self._frame.buf_size
|
||||
|
||||
cdef class MonitoringModelFrame(ModelFrame):
|
||||
cdef cppMonitoringModelFrame * _frame
|
||||
|
||||
def __cinit__(self, CLContext context):
|
||||
self._frame = new cppMonitoringModelFrame(context.device_id, context.context)
|
||||
self.frame = <cppModelFrame*>(self._frame)
|
||||
self.buf_size = self._frame.buf_size
|
||||
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:c829d824ebc73d15da82516592c07d9784369ccbf710698e919e06a702e70924
|
||||
size 50320138
|
||||
oid sha256:72d3d6f8d3c98f5431ec86be77b6350d7d4f43c25075c0106f1d1e7ec7c77668
|
||||
size 49096168
|
||||
|
||||
@@ -96,8 +96,6 @@ class Parser:
|
||||
out_shape=(ModelConstants.LEAD_TRAJ_LEN,ModelConstants.LEAD_WIDTH))
|
||||
if 'lat_planner_solution' in outs:
|
||||
self.parse_mdn('lat_planner_solution', outs, in_N=0, out_N=0, out_shape=(ModelConstants.IDX_N,ModelConstants.LAT_PLANNER_SOLUTION_WIDTH))
|
||||
if 'desired_curvature' in outs:
|
||||
self.parse_mdn('desired_curvature', outs, in_N=0, out_N=0, out_shape=(ModelConstants.DESIRED_CURV_WIDTH,))
|
||||
for k in ['lead_prob', 'lane_lines_prob', 'meta']:
|
||||
self.parse_binary_crossentropy(k, outs)
|
||||
self.parse_categorical_crossentropy('desire_state', outs, out_shape=(ModelConstants.DESIRE_PRED_WIDTH,))
|
||||
|
||||
@@ -1,27 +0,0 @@
|
||||
import os
|
||||
from openpilot.system.hardware import TICI
|
||||
from openpilot.selfdrive.modeld.runners.runmodel_pyx import RunModel, Runtime
|
||||
assert Runtime
|
||||
|
||||
USE_THNEED = int(os.getenv('USE_THNEED', str(int(TICI))))
|
||||
USE_SNPE = int(os.getenv('USE_SNPE', str(int(TICI))))
|
||||
|
||||
class ModelRunner(RunModel):
|
||||
THNEED = 'THNEED'
|
||||
SNPE = 'SNPE'
|
||||
ONNX = 'ONNX'
|
||||
|
||||
def __new__(cls, paths, *args, **kwargs):
|
||||
if ModelRunner.THNEED in paths and USE_THNEED:
|
||||
from openpilot.selfdrive.modeld.runners.thneedmodel_pyx import ThneedModel as Runner
|
||||
runner_type = ModelRunner.THNEED
|
||||
elif ModelRunner.SNPE in paths and USE_SNPE:
|
||||
from openpilot.selfdrive.modeld.runners.snpemodel_pyx import SNPEModel as Runner
|
||||
runner_type = ModelRunner.SNPE
|
||||
elif ModelRunner.ONNX in paths:
|
||||
from openpilot.selfdrive.modeld.runners.onnxmodel import ONNXModel as Runner
|
||||
runner_type = ModelRunner.ONNX
|
||||
else:
|
||||
raise Exception("Couldn't select a model runner, make sure to pass at least one valid model path")
|
||||
|
||||
return Runner(str(paths[runner_type]), *args, **kwargs)
|
||||
@@ -1,98 +0,0 @@
|
||||
import onnx
|
||||
import itertools
|
||||
import os
|
||||
import sys
|
||||
import numpy as np
|
||||
from typing import Any
|
||||
|
||||
from openpilot.selfdrive.modeld.runners.runmodel_pyx import RunModel
|
||||
|
||||
ORT_TYPES_TO_NP_TYPES = {'tensor(float16)': np.float16, 'tensor(float)': np.float32, 'tensor(uint8)': np.uint8}
|
||||
|
||||
def attributeproto_fp16_to_fp32(attr):
|
||||
float32_list = np.frombuffer(attr.raw_data, dtype=np.float16)
|
||||
attr.data_type = 1
|
||||
attr.raw_data = float32_list.astype(np.float32).tobytes()
|
||||
|
||||
def convert_fp16_to_fp32(onnx_path_or_bytes):
|
||||
if isinstance(onnx_path_or_bytes, bytes):
|
||||
model = onnx.load_from_string(onnx_path_or_bytes)
|
||||
elif isinstance(onnx_path_or_bytes, str):
|
||||
model = onnx.load(onnx_path_or_bytes)
|
||||
|
||||
for i in model.graph.initializer:
|
||||
if i.data_type == 10:
|
||||
attributeproto_fp16_to_fp32(i)
|
||||
for i in itertools.chain(model.graph.input, model.graph.output):
|
||||
if i.type.tensor_type.elem_type == 10:
|
||||
i.type.tensor_type.elem_type = 1
|
||||
for i in model.graph.node:
|
||||
if i.op_type == 'Cast' and i.attribute[0].i == 10:
|
||||
i.attribute[0].i = 1
|
||||
for a in i.attribute:
|
||||
if hasattr(a, 't'):
|
||||
if a.t.data_type == 10:
|
||||
attributeproto_fp16_to_fp32(a.t)
|
||||
return model.SerializeToString()
|
||||
|
||||
def create_ort_session(path, fp16_to_fp32):
|
||||
os.environ["OMP_NUM_THREADS"] = "4"
|
||||
os.environ["OMP_WAIT_POLICY"] = "PASSIVE"
|
||||
|
||||
import onnxruntime as ort
|
||||
print("Onnx available providers: ", ort.get_available_providers(), file=sys.stderr)
|
||||
options = ort.SessionOptions()
|
||||
options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
|
||||
|
||||
provider: str | tuple[str, dict[Any, Any]]
|
||||
if 'OpenVINOExecutionProvider' in ort.get_available_providers() and 'ONNXCPU' not in os.environ:
|
||||
provider = 'OpenVINOExecutionProvider'
|
||||
elif 'CUDAExecutionProvider' in ort.get_available_providers() and 'ONNXCPU' not in os.environ:
|
||||
options.intra_op_num_threads = 2
|
||||
provider = ('CUDAExecutionProvider', {'cudnn_conv_algo_search': 'DEFAULT'})
|
||||
else:
|
||||
options.intra_op_num_threads = 2
|
||||
options.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL
|
||||
options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
|
||||
provider = 'CPUExecutionProvider'
|
||||
|
||||
model_data = convert_fp16_to_fp32(path) if fp16_to_fp32 else path
|
||||
print("Onnx selected provider: ", [provider], file=sys.stderr)
|
||||
ort_session = ort.InferenceSession(model_data, options, providers=[provider])
|
||||
print("Onnx using ", ort_session.get_providers(), file=sys.stderr)
|
||||
return ort_session
|
||||
|
||||
|
||||
class ONNXModel(RunModel):
|
||||
def __init__(self, path, output, runtime, use_tf8, cl_context):
|
||||
self.inputs = {}
|
||||
self.output = output
|
||||
|
||||
self.session = create_ort_session(path, fp16_to_fp32=True)
|
||||
self.input_names = [x.name for x in self.session.get_inputs()]
|
||||
self.input_shapes = {x.name: [1, *x.shape[1:]] for x in self.session.get_inputs()}
|
||||
self.input_dtypes = {x.name: ORT_TYPES_TO_NP_TYPES[x.type] for x in self.session.get_inputs()}
|
||||
|
||||
# run once to initialize CUDA provider
|
||||
if "CUDAExecutionProvider" in self.session.get_providers():
|
||||
self.session.run(None, {k: np.zeros(self.input_shapes[k], dtype=self.input_dtypes[k]) for k in self.input_names})
|
||||
print("ready to run onnx model", self.input_shapes, file=sys.stderr)
|
||||
|
||||
def addInput(self, name, buffer):
|
||||
assert name in self.input_names
|
||||
self.inputs[name] = buffer
|
||||
|
||||
def setInputBuffer(self, name, buffer):
|
||||
assert name in self.inputs
|
||||
self.inputs[name] = buffer
|
||||
|
||||
def getCLBuffer(self, name):
|
||||
return None
|
||||
|
||||
def execute(self):
|
||||
inputs = {k: v.view(self.input_dtypes[k]) for k,v in self.inputs.items()}
|
||||
inputs = {k: v.reshape(self.input_shapes[k]).astype(self.input_dtypes[k]) for k,v in inputs.items()}
|
||||
outputs = self.session.run(None, inputs)
|
||||
assert len(outputs) == 1, "Only single model outputs are supported"
|
||||
self.output[:] = outputs[0]
|
||||
return self.output
|
||||
@@ -0,0 +1,36 @@
|
||||
import onnx
|
||||
import onnxruntime as ort
|
||||
import numpy as np
|
||||
import itertools
|
||||
|
||||
ORT_TYPES_TO_NP_TYPES = {'tensor(float16)': np.float16, 'tensor(float)': np.float32, 'tensor(uint8)': np.uint8}
|
||||
|
||||
def attributeproto_fp16_to_fp32(attr):
|
||||
float32_list = np.frombuffer(attr.raw_data, dtype=np.float16)
|
||||
attr.data_type = 1
|
||||
attr.raw_data = float32_list.astype(np.float32).tobytes()
|
||||
|
||||
def convert_fp16_to_fp32(model):
|
||||
for i in model.graph.initializer:
|
||||
if i.data_type == 10:
|
||||
attributeproto_fp16_to_fp32(i)
|
||||
for i in itertools.chain(model.graph.input, model.graph.output):
|
||||
if i.type.tensor_type.elem_type == 10:
|
||||
i.type.tensor_type.elem_type = 1
|
||||
for i in model.graph.node:
|
||||
if i.op_type == 'Cast' and i.attribute[0].i == 10:
|
||||
i.attribute[0].i = 1
|
||||
for a in i.attribute:
|
||||
if hasattr(a, 't'):
|
||||
if a.t.data_type == 10:
|
||||
attributeproto_fp16_to_fp32(a.t)
|
||||
return model.SerializeToString()
|
||||
|
||||
|
||||
def make_onnx_cpu_runner(model_path):
|
||||
options = ort.SessionOptions()
|
||||
options.intra_op_num_threads = 4
|
||||
options.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL
|
||||
options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
|
||||
model_data = convert_fp16_to_fp32(onnx.load(model_path))
|
||||
return ort.InferenceSession(model_data, options, providers=['CPUExecutionProvider'])
|
||||
@@ -1,4 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include "selfdrive/modeld/runners/runmodel.h"
|
||||
#include "selfdrive/modeld/runners/snpemodel.h"
|
||||
@@ -1,49 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <memory>
|
||||
#include <cassert>
|
||||
|
||||
#include "common/clutil.h"
|
||||
#include "common/swaglog.h"
|
||||
|
||||
#define USE_CPU_RUNTIME 0
|
||||
#define USE_GPU_RUNTIME 1
|
||||
#define USE_DSP_RUNTIME 2
|
||||
|
||||
struct ModelInput {
|
||||
const std::string name;
|
||||
float *buffer;
|
||||
int size;
|
||||
|
||||
ModelInput(const std::string _name, float *_buffer, int _size) : name(_name), buffer(_buffer), size(_size) {}
|
||||
virtual void setBuffer(float *_buffer, int _size) {
|
||||
assert(size == _size || size == 0);
|
||||
buffer = _buffer;
|
||||
size = _size;
|
||||
}
|
||||
};
|
||||
|
||||
class RunModel {
|
||||
public:
|
||||
std::vector<std::unique_ptr<ModelInput>> inputs;
|
||||
|
||||
virtual ~RunModel() {}
|
||||
virtual void execute() {}
|
||||
virtual void* getCLBuffer(const std::string name) { return nullptr; }
|
||||
|
||||
virtual void addInput(const std::string name, float *buffer, int size) {
|
||||
inputs.push_back(std::unique_ptr<ModelInput>(new ModelInput(name, buffer, size)));
|
||||
}
|
||||
virtual void setInputBuffer(const std::string name, float *buffer, int size) {
|
||||
for (auto &input : inputs) {
|
||||
if (name == input->name) {
|
||||
input->setBuffer(buffer, size);
|
||||
return;
|
||||
}
|
||||
}
|
||||
LOGE("Tried to update input `%s` but no input with this name exists", name.c_str());
|
||||
assert(false);
|
||||
}
|
||||
};
|
||||
@@ -1,14 +0,0 @@
|
||||
# distutils: language = c++
|
||||
|
||||
from libcpp.string cimport string
|
||||
|
||||
cdef extern from "selfdrive/modeld/runners/runmodel.h":
|
||||
cdef int USE_CPU_RUNTIME
|
||||
cdef int USE_GPU_RUNTIME
|
||||
cdef int USE_DSP_RUNTIME
|
||||
|
||||
cdef cppclass RunModel:
|
||||
void addInput(string, float*, int)
|
||||
void setInputBuffer(string, float*, int)
|
||||
void * getCLBuffer(string)
|
||||
void execute()
|
||||
@@ -1,6 +0,0 @@
|
||||
# distutils: language = c++
|
||||
|
||||
from .runmodel cimport RunModel as cppRunModel
|
||||
|
||||
cdef class RunModel:
|
||||
cdef cppRunModel * model
|
||||
@@ -1,37 +0,0 @@
|
||||
# distutils: language = c++
|
||||
# cython: c_string_encoding=ascii, language_level=3
|
||||
|
||||
from libcpp.string cimport string
|
||||
|
||||
from .runmodel cimport USE_CPU_RUNTIME, USE_GPU_RUNTIME, USE_DSP_RUNTIME
|
||||
from selfdrive.modeld.models.commonmodel_pyx cimport CLMem
|
||||
|
||||
class Runtime:
|
||||
CPU = USE_CPU_RUNTIME
|
||||
GPU = USE_GPU_RUNTIME
|
||||
DSP = USE_DSP_RUNTIME
|
||||
|
||||
cdef class RunModel:
|
||||
def __dealloc__(self):
|
||||
del self.model
|
||||
|
||||
def addInput(self, string name, float[:] buffer):
|
||||
if buffer is not None:
|
||||
self.model.addInput(name, &buffer[0], len(buffer))
|
||||
else:
|
||||
self.model.addInput(name, NULL, 0)
|
||||
|
||||
def setInputBuffer(self, string name, float[:] buffer):
|
||||
if buffer is not None:
|
||||
self.model.setInputBuffer(name, &buffer[0], len(buffer))
|
||||
else:
|
||||
self.model.setInputBuffer(name, NULL, 0)
|
||||
|
||||
def getCLBuffer(self, string name):
|
||||
cdef void * cl_buf = self.model.getCLBuffer(name)
|
||||
if not cl_buf:
|
||||
return None
|
||||
return CLMem.create(cl_buf)
|
||||
|
||||
def execute(self):
|
||||
self.model.execute()
|
||||
@@ -1,116 +0,0 @@
|
||||
#pragma clang diagnostic ignored "-Wexceptions"
|
||||
|
||||
#include "selfdrive/modeld/runners/snpemodel.h"
|
||||
|
||||
#include <cstring>
|
||||
#include <memory>
|
||||
#include <string>
|
||||
#include <utility>
|
||||
#include <vector>
|
||||
|
||||
#include "common/util.h"
|
||||
#include "common/timing.h"
|
||||
|
||||
void PrintErrorStringAndExit() {
|
||||
std::cerr << zdl::DlSystem::getLastErrorString() << std::endl;
|
||||
std::exit(EXIT_FAILURE);
|
||||
}
|
||||
|
||||
SNPEModel::SNPEModel(const std::string path, float *_output, size_t _output_size, int runtime, bool _use_tf8, cl_context context) {
|
||||
output = _output;
|
||||
output_size = _output_size;
|
||||
use_tf8 = _use_tf8;
|
||||
|
||||
#ifdef QCOM2
|
||||
if (runtime == USE_GPU_RUNTIME) {
|
||||
snpe_runtime = zdl::DlSystem::Runtime_t::GPU;
|
||||
} else if (runtime == USE_DSP_RUNTIME) {
|
||||
snpe_runtime = zdl::DlSystem::Runtime_t::DSP;
|
||||
} else {
|
||||
snpe_runtime = zdl::DlSystem::Runtime_t::CPU;
|
||||
}
|
||||
assert(zdl::SNPE::SNPEFactory::isRuntimeAvailable(snpe_runtime));
|
||||
#endif
|
||||
model_data = util::read_file(path);
|
||||
assert(model_data.size() > 0);
|
||||
|
||||
// load model
|
||||
std::unique_ptr<zdl::DlContainer::IDlContainer> container = zdl::DlContainer::IDlContainer::open((uint8_t*)model_data.data(), model_data.size());
|
||||
if (!container) { PrintErrorStringAndExit(); }
|
||||
LOGW("loaded model with size: %lu", model_data.size());
|
||||
|
||||
// create model runner
|
||||
zdl::SNPE::SNPEBuilder snpe_builder(container.get());
|
||||
while (!snpe) {
|
||||
#ifdef QCOM2
|
||||
snpe = snpe_builder.setOutputLayers({})
|
||||
.setRuntimeProcessor(snpe_runtime)
|
||||
.setUseUserSuppliedBuffers(true)
|
||||
.setPerformanceProfile(zdl::DlSystem::PerformanceProfile_t::HIGH_PERFORMANCE)
|
||||
.build();
|
||||
#else
|
||||
snpe = snpe_builder.setOutputLayers({})
|
||||
.setUseUserSuppliedBuffers(true)
|
||||
.setPerformanceProfile(zdl::DlSystem::PerformanceProfile_t::HIGH_PERFORMANCE)
|
||||
.build();
|
||||
#endif
|
||||
if (!snpe) std::cerr << zdl::DlSystem::getLastErrorString() << std::endl;
|
||||
}
|
||||
|
||||
// create output buffer
|
||||
zdl::DlSystem::UserBufferEncodingFloat ub_encoding_float;
|
||||
zdl::DlSystem::IUserBufferFactory &ub_factory = zdl::SNPE::SNPEFactory::getUserBufferFactory();
|
||||
|
||||
const auto &output_tensor_names_opt = snpe->getOutputTensorNames();
|
||||
if (!output_tensor_names_opt) throw std::runtime_error("Error obtaining output tensor names");
|
||||
const auto &output_tensor_names = *output_tensor_names_opt;
|
||||
assert(output_tensor_names.size() == 1);
|
||||
const char *output_tensor_name = output_tensor_names.at(0);
|
||||
const zdl::DlSystem::TensorShape &buffer_shape = snpe->getInputOutputBufferAttributes(output_tensor_name)->getDims();
|
||||
if (output_size != 0) {
|
||||
assert(output_size == buffer_shape[1]);
|
||||
} else {
|
||||
output_size = buffer_shape[1];
|
||||
}
|
||||
std::vector<size_t> output_strides = {output_size * sizeof(float), sizeof(float)};
|
||||
output_buffer = ub_factory.createUserBuffer(output, output_size * sizeof(float), output_strides, &ub_encoding_float);
|
||||
output_map.add(output_tensor_name, output_buffer.get());
|
||||
}
|
||||
|
||||
void SNPEModel::addInput(const std::string name, float *buffer, int size) {
|
||||
const int idx = inputs.size();
|
||||
const auto &input_tensor_names_opt = snpe->getInputTensorNames();
|
||||
if (!input_tensor_names_opt) throw std::runtime_error("Error obtaining input tensor names");
|
||||
const auto &input_tensor_names = *input_tensor_names_opt;
|
||||
const char *input_tensor_name = input_tensor_names.at(idx);
|
||||
const bool input_tf8 = use_tf8 && strcmp(input_tensor_name, "input_img") == 0; // TODO: This is a terrible hack, get rid of this name check both here and in onnx_runner.py
|
||||
LOGW("adding index %d: %s", idx, input_tensor_name);
|
||||
|
||||
zdl::DlSystem::UserBufferEncodingFloat ub_encoding_float;
|
||||
zdl::DlSystem::UserBufferEncodingTf8 ub_encoding_tf8(0, 1./255); // network takes 0-1
|
||||
zdl::DlSystem::IUserBufferFactory &ub_factory = zdl::SNPE::SNPEFactory::getUserBufferFactory();
|
||||
zdl::DlSystem::UserBufferEncoding *input_encoding = input_tf8 ? (zdl::DlSystem::UserBufferEncoding*)&ub_encoding_tf8 : (zdl::DlSystem::UserBufferEncoding*)&ub_encoding_float;
|
||||
|
||||
const auto &buffer_shape_opt = snpe->getInputDimensions(input_tensor_name);
|
||||
const zdl::DlSystem::TensorShape &buffer_shape = *buffer_shape_opt;
|
||||
size_t size_of_input = input_tf8 ? sizeof(uint8_t) : sizeof(float);
|
||||
std::vector<size_t> strides(buffer_shape.rank());
|
||||
strides[strides.size() - 1] = size_of_input;
|
||||
size_t product = 1;
|
||||
for (size_t i = 0; i < buffer_shape.rank(); i++) product *= buffer_shape[i];
|
||||
size_t stride = strides[strides.size() - 1];
|
||||
for (size_t i = buffer_shape.rank() - 1; i > 0; i--) {
|
||||
stride *= buffer_shape[i];
|
||||
strides[i-1] = stride;
|
||||
}
|
||||
|
||||
auto input_buffer = ub_factory.createUserBuffer(buffer, product*size_of_input, strides, input_encoding);
|
||||
input_map.add(input_tensor_name, input_buffer.get());
|
||||
inputs.push_back(std::unique_ptr<SNPEModelInput>(new SNPEModelInput(name, buffer, size, std::move(input_buffer))));
|
||||
}
|
||||
|
||||
void SNPEModel::execute() {
|
||||
if (!snpe->execute(input_map, output_map)) {
|
||||
PrintErrorStringAndExit();
|
||||
}
|
||||
}
|
||||
@@ -1,52 +0,0 @@
|
||||
#pragma once
|
||||
#pragma clang diagnostic ignored "-Wdeprecated-declarations"
|
||||
|
||||
#include <memory>
|
||||
#include <string>
|
||||
#include <utility>
|
||||
|
||||
#include <DlContainer/IDlContainer.hpp>
|
||||
#include <DlSystem/DlError.hpp>
|
||||
#include <DlSystem/ITensor.hpp>
|
||||
#include <DlSystem/ITensorFactory.hpp>
|
||||
#include <DlSystem/IUserBuffer.hpp>
|
||||
#include <DlSystem/IUserBufferFactory.hpp>
|
||||
#include <SNPE/SNPE.hpp>
|
||||
#include <SNPE/SNPEBuilder.hpp>
|
||||
#include <SNPE/SNPEFactory.hpp>
|
||||
|
||||
#include "selfdrive/modeld/runners/runmodel.h"
|
||||
|
||||
struct SNPEModelInput : public ModelInput {
|
||||
std::unique_ptr<zdl::DlSystem::IUserBuffer> snpe_buffer;
|
||||
|
||||
SNPEModelInput(const std::string _name, float *_buffer, int _size, std::unique_ptr<zdl::DlSystem::IUserBuffer> _snpe_buffer) : ModelInput(_name, _buffer, _size), snpe_buffer(std::move(_snpe_buffer)) {}
|
||||
void setBuffer(float *_buffer, int _size) {
|
||||
ModelInput::setBuffer(_buffer, _size);
|
||||
assert(snpe_buffer->setBufferAddress(_buffer) == true);
|
||||
}
|
||||
};
|
||||
|
||||
class SNPEModel : public RunModel {
|
||||
public:
|
||||
SNPEModel(const std::string path, float *_output, size_t _output_size, int runtime, bool use_tf8 = false, cl_context context = NULL);
|
||||
void addInput(const std::string name, float *buffer, int size);
|
||||
void execute();
|
||||
|
||||
private:
|
||||
std::string model_data;
|
||||
|
||||
#ifdef QCOM2
|
||||
zdl::DlSystem::Runtime_t snpe_runtime;
|
||||
#endif
|
||||
|
||||
// snpe model stuff
|
||||
std::unique_ptr<zdl::SNPE::SNPE> snpe;
|
||||
zdl::DlSystem::UserBufferMap input_map;
|
||||
zdl::DlSystem::UserBufferMap output_map;
|
||||
std::unique_ptr<zdl::DlSystem::IUserBuffer> output_buffer;
|
||||
|
||||
bool use_tf8;
|
||||
float *output;
|
||||
size_t output_size;
|
||||
};
|
||||
@@ -1,9 +0,0 @@
|
||||
# distutils: language = c++
|
||||
|
||||
from libcpp.string cimport string
|
||||
|
||||
from msgq.visionipc.visionipc cimport cl_context
|
||||
|
||||
cdef extern from "selfdrive/modeld/runners/snpemodel.h":
|
||||
cdef cppclass SNPEModel:
|
||||
SNPEModel(string, float*, size_t, int, bool, cl_context)
|
||||
@@ -1,17 +0,0 @@
|
||||
# distutils: language = c++
|
||||
# cython: c_string_encoding=ascii, language_level=3
|
||||
|
||||
import os
|
||||
from libcpp cimport bool
|
||||
from libcpp.string cimport string
|
||||
|
||||
from .snpemodel cimport SNPEModel as cppSNPEModel
|
||||
from selfdrive.modeld.models.commonmodel_pyx cimport CLContext
|
||||
from selfdrive.modeld.runners.runmodel_pyx cimport RunModel
|
||||
from selfdrive.modeld.runners.runmodel cimport RunModel as cppRunModel
|
||||
|
||||
os.environ['ADSP_LIBRARY_PATH'] = "/data/pythonpath/third_party/snpe/dsp/"
|
||||
|
||||
cdef class SNPEModel(RunModel):
|
||||
def __cinit__(self, string path, float[:] output, int runtime, bool use_tf8, CLContext context):
|
||||
self.model = <cppRunModel *> new cppSNPEModel(path, &output[0], len(output), runtime, use_tf8, context.context)
|
||||
@@ -1,58 +0,0 @@
|
||||
#include "selfdrive/modeld/runners/thneedmodel.h"
|
||||
|
||||
#include <string>
|
||||
|
||||
#include "common/swaglog.h"
|
||||
|
||||
ThneedModel::ThneedModel(const std::string path, float *_output, size_t _output_size, int runtime, bool luse_tf8, cl_context context) {
|
||||
thneed = new Thneed(true, context);
|
||||
thneed->load(path.c_str());
|
||||
thneed->clexec();
|
||||
|
||||
recorded = false;
|
||||
output = _output;
|
||||
}
|
||||
|
||||
void* ThneedModel::getCLBuffer(const std::string name) {
|
||||
int index = -1;
|
||||
for (int i = 0; i < inputs.size(); i++) {
|
||||
if (name == inputs[i]->name) {
|
||||
index = i;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (index == -1) {
|
||||
LOGE("Tried to get CL buffer for input `%s` but no input with this name exists", name.c_str());
|
||||
assert(false);
|
||||
}
|
||||
|
||||
if (thneed->input_clmem.size() >= inputs.size()) {
|
||||
return &thneed->input_clmem[inputs.size() - index - 1];
|
||||
} else {
|
||||
return nullptr;
|
||||
}
|
||||
}
|
||||
|
||||
void ThneedModel::execute() {
|
||||
if (!recorded) {
|
||||
thneed->record = true;
|
||||
float *input_buffers[inputs.size()];
|
||||
for (int i = 0; i < inputs.size(); i++) {
|
||||
input_buffers[inputs.size() - i - 1] = inputs[i]->buffer;
|
||||
}
|
||||
|
||||
thneed->copy_inputs(input_buffers);
|
||||
thneed->clexec();
|
||||
thneed->copy_output(output);
|
||||
thneed->stop();
|
||||
|
||||
recorded = true;
|
||||
} else {
|
||||
float *input_buffers[inputs.size()];
|
||||
for (int i = 0; i < inputs.size(); i++) {
|
||||
input_buffers[inputs.size() - i - 1] = inputs[i]->buffer;
|
||||
}
|
||||
thneed->execute(input_buffers, output);
|
||||
}
|
||||
}
|
||||
@@ -1,17 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include <string>
|
||||
|
||||
#include "selfdrive/modeld/runners/runmodel.h"
|
||||
#include "selfdrive/modeld/thneed/thneed.h"
|
||||
|
||||
class ThneedModel : public RunModel {
|
||||
public:
|
||||
ThneedModel(const std::string path, float *_output, size_t _output_size, int runtime, bool use_tf8 = false, cl_context context = NULL);
|
||||
void *getCLBuffer(const std::string name);
|
||||
void execute();
|
||||
private:
|
||||
Thneed *thneed = NULL;
|
||||
bool recorded;
|
||||
float *output;
|
||||
};
|
||||
@@ -1,9 +0,0 @@
|
||||
# distutils: language = c++
|
||||
|
||||
from libcpp.string cimport string
|
||||
|
||||
from msgq.visionipc.visionipc cimport cl_context
|
||||
|
||||
cdef extern from "selfdrive/modeld/runners/thneedmodel.h":
|
||||
cdef cppclass ThneedModel:
|
||||
ThneedModel(string, float*, size_t, int, bool, cl_context)
|
||||
@@ -1,14 +0,0 @@
|
||||
# distutils: language = c++
|
||||
# cython: c_string_encoding=ascii, language_level=3
|
||||
|
||||
from libcpp cimport bool
|
||||
from libcpp.string cimport string
|
||||
|
||||
from .thneedmodel cimport ThneedModel as cppThneedModel
|
||||
from selfdrive.modeld.models.commonmodel_pyx cimport CLContext
|
||||
from selfdrive.modeld.runners.runmodel_pyx cimport RunModel
|
||||
from selfdrive.modeld.runners.runmodel cimport RunModel as cppRunModel
|
||||
|
||||
cdef class ThneedModel(RunModel):
|
||||
def __cinit__(self, string path, float[:] output, int runtime, bool use_tf8, CLContext context):
|
||||
self.model = <cppRunModel *> new cppThneedModel(path, &output[0], len(output), runtime, use_tf8, context.context)
|
||||
@@ -0,0 +1,8 @@
|
||||
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.helpers import to_mv
|
||||
|
||||
def qcom_tensor_from_opencl_address(opencl_address, shape, dtype):
|
||||
cl_buf_desc_ptr = to_mv(opencl_address, 8).cast('Q')[0]
|
||||
rawbuf_ptr = to_mv(cl_buf_desc_ptr, 0x100).cast('Q')[20] # offset 0xA0 is a raw gpu pointer.
|
||||
return Tensor.from_blob(rawbuf_ptr, shape, dtype=dtype, device='QCOM')
|
||||
@@ -1,8 +0,0 @@
|
||||
thneed is an SNPE accelerator. I know SNPE is already an accelerator, but sometimes things need to go even faster..
|
||||
|
||||
It runs on the local device, and caches a single model run. Then it replays it, but fast.
|
||||
|
||||
thneed slices through abstraction layers like a fish.
|
||||
|
||||
You need a thneed.
|
||||
|
||||
@@ -1,154 +0,0 @@
|
||||
#include <cassert>
|
||||
#include <set>
|
||||
|
||||
#include "third_party/json11/json11.hpp"
|
||||
#include "common/util.h"
|
||||
#include "common/clutil.h"
|
||||
#include "common/swaglog.h"
|
||||
#include "selfdrive/modeld/thneed/thneed.h"
|
||||
using namespace json11;
|
||||
|
||||
extern map<cl_program, string> g_program_source;
|
||||
|
||||
void Thneed::load(const char *filename) {
|
||||
LOGD("Thneed::load: loading from %s\n", filename);
|
||||
|
||||
string buf = util::read_file(filename);
|
||||
int jsz = *(int *)buf.data();
|
||||
string jsonerr;
|
||||
string jj(buf.data() + sizeof(int), jsz);
|
||||
Json jdat = Json::parse(jj, jsonerr);
|
||||
|
||||
map<cl_mem, cl_mem> real_mem;
|
||||
real_mem[NULL] = NULL;
|
||||
|
||||
int ptr = sizeof(int)+jsz;
|
||||
for (auto &obj : jdat["objects"].array_items()) {
|
||||
auto mobj = obj.object_items();
|
||||
int sz = mobj["size"].int_value();
|
||||
cl_mem clbuf = NULL;
|
||||
|
||||
if (mobj["buffer_id"].string_value().size() > 0) {
|
||||
// image buffer must already be allocated
|
||||
clbuf = real_mem[*(cl_mem*)(mobj["buffer_id"].string_value().data())];
|
||||
assert(mobj["needs_load"].bool_value() == false);
|
||||
} else {
|
||||
if (mobj["needs_load"].bool_value()) {
|
||||
clbuf = clCreateBuffer(context, CL_MEM_COPY_HOST_PTR | CL_MEM_READ_WRITE, sz, &buf[ptr], NULL);
|
||||
if (debug >= 1) printf("loading %p %d @ 0x%X\n", clbuf, sz, ptr);
|
||||
ptr += sz;
|
||||
} else {
|
||||
// TODO: is there a faster way to init zeroed out buffers?
|
||||
void *host_zeros = calloc(sz, 1);
|
||||
clbuf = clCreateBuffer(context, CL_MEM_COPY_HOST_PTR | CL_MEM_READ_WRITE, sz, host_zeros, NULL);
|
||||
free(host_zeros);
|
||||
}
|
||||
}
|
||||
assert(clbuf != NULL);
|
||||
|
||||
if (mobj["arg_type"] == "image2d_t" || mobj["arg_type"] == "image1d_t") {
|
||||
cl_image_desc desc = {0};
|
||||
desc.image_type = (mobj["arg_type"] == "image2d_t") ? CL_MEM_OBJECT_IMAGE2D : CL_MEM_OBJECT_IMAGE1D_BUFFER;
|
||||
desc.image_width = mobj["width"].int_value();
|
||||
desc.image_height = mobj["height"].int_value();
|
||||
desc.image_row_pitch = mobj["row_pitch"].int_value();
|
||||
assert(sz == desc.image_height*desc.image_row_pitch);
|
||||
#ifdef QCOM2
|
||||
desc.buffer = clbuf;
|
||||
#else
|
||||
// TODO: we are creating unused buffers on PC
|
||||
clReleaseMemObject(clbuf);
|
||||
#endif
|
||||
cl_image_format format = {0};
|
||||
format.image_channel_order = CL_RGBA;
|
||||
format.image_channel_data_type = mobj["float32"].bool_value() ? CL_FLOAT : CL_HALF_FLOAT;
|
||||
|
||||
cl_int errcode;
|
||||
|
||||
#ifndef QCOM2
|
||||
if (mobj["needs_load"].bool_value()) {
|
||||
clbuf = clCreateImage(context, CL_MEM_COPY_HOST_PTR | CL_MEM_READ_WRITE, &format, &desc, &buf[ptr-sz], &errcode);
|
||||
} else {
|
||||
clbuf = clCreateImage(context, CL_MEM_READ_WRITE, &format, &desc, NULL, &errcode);
|
||||
}
|
||||
#else
|
||||
clbuf = clCreateImage(context, CL_MEM_READ_WRITE, &format, &desc, NULL, &errcode);
|
||||
#endif
|
||||
if (clbuf == NULL) {
|
||||
LOGE("clError: %s create image %zux%zu rp %zu with buffer %p\n", cl_get_error_string(errcode),
|
||||
desc.image_width, desc.image_height, desc.image_row_pitch, desc.buffer);
|
||||
}
|
||||
assert(clbuf != NULL);
|
||||
}
|
||||
|
||||
real_mem[*(cl_mem*)(mobj["id"].string_value().data())] = clbuf;
|
||||
}
|
||||
|
||||
map<string, cl_program> g_programs;
|
||||
for (const auto &[name, source] : jdat["programs"].object_items()) {
|
||||
if (debug >= 1) printf("building %s with size %zu\n", name.c_str(), source.string_value().size());
|
||||
g_programs[name] = cl_program_from_source(context, device_id, source.string_value());
|
||||
}
|
||||
|
||||
for (auto &obj : jdat["inputs"].array_items()) {
|
||||
auto mobj = obj.object_items();
|
||||
int sz = mobj["size"].int_value();
|
||||
cl_mem aa = real_mem[*(cl_mem*)(mobj["buffer_id"].string_value().data())];
|
||||
input_clmem.push_back(aa);
|
||||
input_sizes.push_back(sz);
|
||||
LOGD("Thneed::load: adding input %s with size %d\n", mobj["name"].string_value().data(), sz);
|
||||
|
||||
cl_int cl_err;
|
||||
void *ret = clEnqueueMapBuffer(command_queue, aa, CL_TRUE, CL_MAP_WRITE, 0, sz, 0, NULL, NULL, &cl_err);
|
||||
if (cl_err != CL_SUCCESS) LOGE("clError: %s map %p %d\n", cl_get_error_string(cl_err), aa, sz);
|
||||
assert(cl_err == CL_SUCCESS);
|
||||
inputs.push_back(ret);
|
||||
}
|
||||
|
||||
for (auto &obj : jdat["outputs"].array_items()) {
|
||||
auto mobj = obj.object_items();
|
||||
int sz = mobj["size"].int_value();
|
||||
LOGD("Thneed::save: adding output with size %d\n", sz);
|
||||
// TODO: support multiple outputs
|
||||
output = real_mem[*(cl_mem*)(mobj["buffer_id"].string_value().data())];
|
||||
assert(output != NULL);
|
||||
}
|
||||
|
||||
for (auto &obj : jdat["binaries"].array_items()) {
|
||||
string name = obj["name"].string_value();
|
||||
size_t length = obj["length"].int_value();
|
||||
if (debug >= 1) printf("binary %s with size %zu\n", name.c_str(), length);
|
||||
g_programs[name] = cl_program_from_binary(context, device_id, (const uint8_t*)&buf[ptr], length);
|
||||
ptr += length;
|
||||
}
|
||||
|
||||
for (auto &obj : jdat["kernels"].array_items()) {
|
||||
auto gws = obj["global_work_size"];
|
||||
auto lws = obj["local_work_size"];
|
||||
auto kk = shared_ptr<CLQueuedKernel>(new CLQueuedKernel(this));
|
||||
|
||||
kk->name = obj["name"].string_value();
|
||||
kk->program = g_programs[kk->name];
|
||||
kk->work_dim = obj["work_dim"].int_value();
|
||||
for (int i = 0; i < kk->work_dim; i++) {
|
||||
kk->global_work_size[i] = gws[i].int_value();
|
||||
kk->local_work_size[i] = lws[i].int_value();
|
||||
}
|
||||
kk->num_args = obj["num_args"].int_value();
|
||||
for (int i = 0; i < kk->num_args; i++) {
|
||||
string arg = obj["args"].array_items()[i].string_value();
|
||||
int arg_size = obj["args_size"].array_items()[i].int_value();
|
||||
kk->args_size.push_back(arg_size);
|
||||
if (arg_size == 8) {
|
||||
cl_mem val = *(cl_mem*)(arg.data());
|
||||
val = real_mem[val];
|
||||
kk->args.push_back(string((char*)&val, sizeof(val)));
|
||||
} else {
|
||||
kk->args.push_back(arg);
|
||||
}
|
||||
}
|
||||
kq.push_back(kk);
|
||||
}
|
||||
|
||||
clFinish(command_queue);
|
||||
}
|
||||
@@ -1,133 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#ifndef __user
|
||||
#define __user __attribute__(())
|
||||
#endif
|
||||
|
||||
#include <cstdint>
|
||||
#include <cstdlib>
|
||||
#include <memory>
|
||||
#include <string>
|
||||
#include <vector>
|
||||
|
||||
#include <CL/cl.h>
|
||||
|
||||
#include "third_party/linux/include/msm_kgsl.h"
|
||||
|
||||
using namespace std;
|
||||
|
||||
cl_int thneed_clSetKernelArg(cl_kernel kernel, cl_uint arg_index, size_t arg_size, const void *arg_value);
|
||||
|
||||
namespace json11 {
|
||||
class Json;
|
||||
}
|
||||
class Thneed;
|
||||
|
||||
class GPUMalloc {
|
||||
public:
|
||||
GPUMalloc(int size, int fd);
|
||||
~GPUMalloc();
|
||||
void *alloc(int size);
|
||||
private:
|
||||
uint64_t base;
|
||||
int remaining;
|
||||
};
|
||||
|
||||
class CLQueuedKernel {
|
||||
public:
|
||||
CLQueuedKernel(Thneed *lthneed) { thneed = lthneed; }
|
||||
CLQueuedKernel(Thneed *lthneed,
|
||||
cl_kernel _kernel,
|
||||
cl_uint _work_dim,
|
||||
const size_t *_global_work_size,
|
||||
const size_t *_local_work_size);
|
||||
cl_int exec();
|
||||
void debug_print(bool verbose);
|
||||
int get_arg_num(const char *search_arg_name);
|
||||
cl_program program;
|
||||
string name;
|
||||
cl_uint num_args;
|
||||
vector<string> arg_names;
|
||||
vector<string> arg_types;
|
||||
vector<string> args;
|
||||
vector<int> args_size;
|
||||
cl_kernel kernel = NULL;
|
||||
json11::Json to_json() const;
|
||||
|
||||
cl_uint work_dim;
|
||||
size_t global_work_size[3] = {0};
|
||||
size_t local_work_size[3] = {0};
|
||||
private:
|
||||
Thneed *thneed;
|
||||
};
|
||||
|
||||
class CachedIoctl {
|
||||
public:
|
||||
virtual void exec() {}
|
||||
};
|
||||
|
||||
class CachedSync: public CachedIoctl {
|
||||
public:
|
||||
CachedSync(Thneed *lthneed, string ldata) { thneed = lthneed; data = ldata; }
|
||||
void exec();
|
||||
private:
|
||||
Thneed *thneed;
|
||||
string data;
|
||||
};
|
||||
|
||||
class CachedCommand: public CachedIoctl {
|
||||
public:
|
||||
CachedCommand(Thneed *lthneed, struct kgsl_gpu_command *cmd);
|
||||
void exec();
|
||||
private:
|
||||
void disassemble(int cmd_index);
|
||||
struct kgsl_gpu_command cache;
|
||||
unique_ptr<kgsl_command_object[]> cmds;
|
||||
unique_ptr<kgsl_command_object[]> objs;
|
||||
Thneed *thneed;
|
||||
vector<shared_ptr<CLQueuedKernel> > kq;
|
||||
};
|
||||
|
||||
class Thneed {
|
||||
public:
|
||||
Thneed(bool do_clinit=false, cl_context _context = NULL);
|
||||
void stop();
|
||||
void execute(float **finputs, float *foutput, bool slow=false);
|
||||
void wait();
|
||||
|
||||
vector<cl_mem> input_clmem;
|
||||
vector<void *> inputs;
|
||||
vector<size_t> input_sizes;
|
||||
cl_mem output = NULL;
|
||||
|
||||
cl_context context = NULL;
|
||||
cl_command_queue command_queue;
|
||||
cl_device_id device_id;
|
||||
int context_id;
|
||||
|
||||
// protected?
|
||||
bool record = false;
|
||||
int debug;
|
||||
int timestamp;
|
||||
|
||||
#ifdef QCOM2
|
||||
unique_ptr<GPUMalloc> ram;
|
||||
vector<unique_ptr<CachedIoctl> > cmds;
|
||||
int fd;
|
||||
#endif
|
||||
|
||||
// all CL kernels
|
||||
void copy_inputs(float **finputs, bool internal=false);
|
||||
void copy_output(float *foutput);
|
||||
cl_int clexec();
|
||||
vector<shared_ptr<CLQueuedKernel> > kq;
|
||||
|
||||
// pending CL kernels
|
||||
vector<shared_ptr<CLQueuedKernel> > ckq;
|
||||
|
||||
// loading
|
||||
void load(const char *filename);
|
||||
private:
|
||||
void clinit();
|
||||
};
|
||||
|
||||
@@ -1,216 +0,0 @@
|
||||
#include "selfdrive/modeld/thneed/thneed.h"
|
||||
|
||||
#include <cassert>
|
||||
#include <cstring>
|
||||
#include <map>
|
||||
|
||||
#include "common/clutil.h"
|
||||
#include "common/timing.h"
|
||||
|
||||
map<pair<cl_kernel, int>, string> g_args;
|
||||
map<pair<cl_kernel, int>, int> g_args_size;
|
||||
map<cl_program, string> g_program_source;
|
||||
|
||||
void Thneed::stop() {
|
||||
//printf("Thneed::stop: recorded %lu commands\n", cmds.size());
|
||||
record = false;
|
||||
}
|
||||
|
||||
void Thneed::clinit() {
|
||||
device_id = cl_get_device_id(CL_DEVICE_TYPE_DEFAULT);
|
||||
if (context == NULL) context = CL_CHECK_ERR(clCreateContext(NULL, 1, &device_id, NULL, NULL, &err));
|
||||
//cl_command_queue_properties props[3] = {CL_QUEUE_PROPERTIES, CL_QUEUE_PROFILING_ENABLE, 0};
|
||||
cl_command_queue_properties props[3] = {CL_QUEUE_PROPERTIES, 0, 0};
|
||||
command_queue = CL_CHECK_ERR(clCreateCommandQueueWithProperties(context, device_id, props, &err));
|
||||
printf("Thneed::clinit done\n");
|
||||
}
|
||||
|
||||
cl_int Thneed::clexec() {
|
||||
if (debug >= 1) printf("Thneed::clexec: running %lu queued kernels\n", kq.size());
|
||||
for (auto &k : kq) {
|
||||
if (record) ckq.push_back(k);
|
||||
cl_int ret = k->exec();
|
||||
assert(ret == CL_SUCCESS);
|
||||
}
|
||||
return clFinish(command_queue);
|
||||
}
|
||||
|
||||
void Thneed::copy_inputs(float **finputs, bool internal) {
|
||||
for (int idx = 0; idx < inputs.size(); ++idx) {
|
||||
if (debug >= 1) printf("copying %lu -- %p -> %p (cl %p)\n", input_sizes[idx], finputs[idx], inputs[idx], input_clmem[idx]);
|
||||
|
||||
if (internal) {
|
||||
// if it's internal, using memcpy is fine since the buffer sync is cached in the ioctl layer
|
||||
if (finputs[idx] != NULL) memcpy(inputs[idx], finputs[idx], input_sizes[idx]);
|
||||
} else {
|
||||
if (finputs[idx] != NULL) CL_CHECK(clEnqueueWriteBuffer(command_queue, input_clmem[idx], CL_TRUE, 0, input_sizes[idx], finputs[idx], 0, NULL, NULL));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void Thneed::copy_output(float *foutput) {
|
||||
if (output != NULL) {
|
||||
size_t sz;
|
||||
clGetMemObjectInfo(output, CL_MEM_SIZE, sizeof(sz), &sz, NULL);
|
||||
if (debug >= 1) printf("copying %lu for output %p -> %p\n", sz, output, foutput);
|
||||
CL_CHECK(clEnqueueReadBuffer(command_queue, output, CL_TRUE, 0, sz, foutput, 0, NULL, NULL));
|
||||
} else {
|
||||
printf("CAUTION: model output is NULL, does it have no outputs?\n");
|
||||
}
|
||||
}
|
||||
|
||||
// *********** CLQueuedKernel ***********
|
||||
|
||||
CLQueuedKernel::CLQueuedKernel(Thneed *lthneed,
|
||||
cl_kernel _kernel,
|
||||
cl_uint _work_dim,
|
||||
const size_t *_global_work_size,
|
||||
const size_t *_local_work_size) {
|
||||
thneed = lthneed;
|
||||
kernel = _kernel;
|
||||
work_dim = _work_dim;
|
||||
assert(work_dim <= 3);
|
||||
for (int i = 0; i < work_dim; i++) {
|
||||
global_work_size[i] = _global_work_size[i];
|
||||
local_work_size[i] = _local_work_size[i];
|
||||
}
|
||||
|
||||
char _name[0x100];
|
||||
clGetKernelInfo(kernel, CL_KERNEL_FUNCTION_NAME, sizeof(_name), _name, NULL);
|
||||
name = string(_name);
|
||||
clGetKernelInfo(kernel, CL_KERNEL_NUM_ARGS, sizeof(num_args), &num_args, NULL);
|
||||
|
||||
// get args
|
||||
for (int i = 0; i < num_args; i++) {
|
||||
char arg_name[0x100] = {0};
|
||||
clGetKernelArgInfo(kernel, i, CL_KERNEL_ARG_NAME, sizeof(arg_name), arg_name, NULL);
|
||||
arg_names.push_back(string(arg_name));
|
||||
clGetKernelArgInfo(kernel, i, CL_KERNEL_ARG_TYPE_NAME, sizeof(arg_name), arg_name, NULL);
|
||||
arg_types.push_back(string(arg_name));
|
||||
|
||||
args.push_back(g_args[make_pair(kernel, i)]);
|
||||
args_size.push_back(g_args_size[make_pair(kernel, i)]);
|
||||
}
|
||||
|
||||
// get program
|
||||
clGetKernelInfo(kernel, CL_KERNEL_PROGRAM, sizeof(program), &program, NULL);
|
||||
}
|
||||
|
||||
int CLQueuedKernel::get_arg_num(const char *search_arg_name) {
|
||||
for (int i = 0; i < num_args; i++) {
|
||||
if (arg_names[i] == search_arg_name) return i;
|
||||
}
|
||||
printf("failed to find %s in %s\n", search_arg_name, name.c_str());
|
||||
assert(false);
|
||||
}
|
||||
|
||||
cl_int CLQueuedKernel::exec() {
|
||||
if (kernel == NULL) {
|
||||
kernel = clCreateKernel(program, name.c_str(), NULL);
|
||||
arg_names.clear();
|
||||
arg_types.clear();
|
||||
|
||||
for (int j = 0; j < num_args; j++) {
|
||||
char arg_name[0x100] = {0};
|
||||
clGetKernelArgInfo(kernel, j, CL_KERNEL_ARG_NAME, sizeof(arg_name), arg_name, NULL);
|
||||
arg_names.push_back(string(arg_name));
|
||||
clGetKernelArgInfo(kernel, j, CL_KERNEL_ARG_TYPE_NAME, sizeof(arg_name), arg_name, NULL);
|
||||
arg_types.push_back(string(arg_name));
|
||||
|
||||
cl_int ret;
|
||||
if (args[j].size() != 0) {
|
||||
assert(args[j].size() == args_size[j]);
|
||||
ret = thneed_clSetKernelArg(kernel, j, args[j].size(), args[j].data());
|
||||
} else {
|
||||
ret = thneed_clSetKernelArg(kernel, j, args_size[j], NULL);
|
||||
}
|
||||
assert(ret == CL_SUCCESS);
|
||||
}
|
||||
}
|
||||
|
||||
if (thneed->debug >= 1) {
|
||||
debug_print(thneed->debug >= 2);
|
||||
}
|
||||
|
||||
return clEnqueueNDRangeKernel(thneed->command_queue,
|
||||
kernel, work_dim, NULL, global_work_size, local_work_size, 0, NULL, NULL);
|
||||
}
|
||||
|
||||
void CLQueuedKernel::debug_print(bool verbose) {
|
||||
printf("%p %56s -- ", kernel, name.c_str());
|
||||
for (int i = 0; i < work_dim; i++) {
|
||||
printf("%4zu ", global_work_size[i]);
|
||||
}
|
||||
printf(" -- ");
|
||||
for (int i = 0; i < work_dim; i++) {
|
||||
printf("%4zu ", local_work_size[i]);
|
||||
}
|
||||
printf("\n");
|
||||
|
||||
if (verbose) {
|
||||
for (int i = 0; i < num_args; i++) {
|
||||
string arg = args[i];
|
||||
printf(" %s %s", arg_types[i].c_str(), arg_names[i].c_str());
|
||||
void *arg_value = (void*)arg.data();
|
||||
int arg_size = arg.size();
|
||||
if (arg_size == 0) {
|
||||
printf(" (size) %d", args_size[i]);
|
||||
} else if (arg_size == 1) {
|
||||
printf(" = %d", *((char*)arg_value));
|
||||
} else if (arg_size == 2) {
|
||||
printf(" = %d", *((short*)arg_value));
|
||||
} else if (arg_size == 4) {
|
||||
if (arg_types[i] == "float") {
|
||||
printf(" = %f", *((float*)arg_value));
|
||||
} else {
|
||||
printf(" = %d", *((int*)arg_value));
|
||||
}
|
||||
} else if (arg_size == 8) {
|
||||
cl_mem val = (cl_mem)(*((uintptr_t*)arg_value));
|
||||
printf(" = %p", val);
|
||||
if (val != NULL) {
|
||||
cl_mem_object_type obj_type;
|
||||
clGetMemObjectInfo(val, CL_MEM_TYPE, sizeof(obj_type), &obj_type, NULL);
|
||||
if (arg_types[i] == "image2d_t" || arg_types[i] == "image1d_t" || obj_type == CL_MEM_OBJECT_IMAGE2D) {
|
||||
cl_image_format format;
|
||||
size_t width, height, depth, array_size, row_pitch, slice_pitch;
|
||||
cl_mem buf;
|
||||
clGetImageInfo(val, CL_IMAGE_FORMAT, sizeof(format), &format, NULL);
|
||||
assert(format.image_channel_order == CL_RGBA);
|
||||
assert(format.image_channel_data_type == CL_HALF_FLOAT || format.image_channel_data_type == CL_FLOAT);
|
||||
clGetImageInfo(val, CL_IMAGE_WIDTH, sizeof(width), &width, NULL);
|
||||
clGetImageInfo(val, CL_IMAGE_HEIGHT, sizeof(height), &height, NULL);
|
||||
clGetImageInfo(val, CL_IMAGE_ROW_PITCH, sizeof(row_pitch), &row_pitch, NULL);
|
||||
clGetImageInfo(val, CL_IMAGE_DEPTH, sizeof(depth), &depth, NULL);
|
||||
clGetImageInfo(val, CL_IMAGE_ARRAY_SIZE, sizeof(array_size), &array_size, NULL);
|
||||
clGetImageInfo(val, CL_IMAGE_SLICE_PITCH, sizeof(slice_pitch), &slice_pitch, NULL);
|
||||
assert(depth == 0);
|
||||
assert(array_size == 0);
|
||||
assert(slice_pitch == 0);
|
||||
|
||||
clGetImageInfo(val, CL_IMAGE_BUFFER, sizeof(buf), &buf, NULL);
|
||||
size_t sz = 0;
|
||||
if (buf != NULL) clGetMemObjectInfo(buf, CL_MEM_SIZE, sizeof(sz), &sz, NULL);
|
||||
printf(" image %zu x %zu rp %zu @ %p buffer %zu", width, height, row_pitch, buf, sz);
|
||||
} else {
|
||||
size_t sz;
|
||||
clGetMemObjectInfo(val, CL_MEM_SIZE, sizeof(sz), &sz, NULL);
|
||||
printf(" buffer %zu", sz);
|
||||
}
|
||||
}
|
||||
}
|
||||
printf("\n");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
cl_int thneed_clSetKernelArg(cl_kernel kernel, cl_uint arg_index, size_t arg_size, const void *arg_value) {
|
||||
g_args_size[make_pair(kernel, arg_index)] = arg_size;
|
||||
if (arg_value != NULL) {
|
||||
g_args[make_pair(kernel, arg_index)] = string((char*)arg_value, arg_size);
|
||||
} else {
|
||||
g_args[make_pair(kernel, arg_index)] = string("");
|
||||
}
|
||||
cl_int ret = clSetKernelArg(kernel, arg_index, arg_size, arg_value);
|
||||
return ret;
|
||||
}
|
||||
@@ -1,32 +0,0 @@
|
||||
#include "selfdrive/modeld/thneed/thneed.h"
|
||||
|
||||
#include <cassert>
|
||||
|
||||
#include "common/clutil.h"
|
||||
#include "common/timing.h"
|
||||
|
||||
Thneed::Thneed(bool do_clinit, cl_context _context) {
|
||||
context = _context;
|
||||
if (do_clinit) clinit();
|
||||
char *thneed_debug_env = getenv("THNEED_DEBUG");
|
||||
debug = (thneed_debug_env != NULL) ? atoi(thneed_debug_env) : 0;
|
||||
}
|
||||
|
||||
void Thneed::execute(float **finputs, float *foutput, bool slow) {
|
||||
uint64_t tb, te;
|
||||
if (debug >= 1) tb = nanos_since_boot();
|
||||
|
||||
// ****** copy inputs
|
||||
copy_inputs(finputs);
|
||||
|
||||
// ****** run commands
|
||||
clexec();
|
||||
|
||||
// ****** copy outputs
|
||||
copy_output(foutput);
|
||||
|
||||
if (debug >= 1) {
|
||||
te = nanos_since_boot();
|
||||
printf("model exec in %lu us\n", (te-tb)/1000);
|
||||
}
|
||||
}
|
||||
@@ -1,258 +0,0 @@
|
||||
#include "selfdrive/modeld/thneed/thneed.h"
|
||||
|
||||
#include <dlfcn.h>
|
||||
#include <sys/mman.h>
|
||||
|
||||
#include <cassert>
|
||||
#include <cerrno>
|
||||
#include <cstring>
|
||||
#include <map>
|
||||
#include <string>
|
||||
|
||||
#include "common/clutil.h"
|
||||
#include "common/timing.h"
|
||||
|
||||
Thneed *g_thneed = NULL;
|
||||
int g_fd = -1;
|
||||
|
||||
void hexdump(uint8_t *d, int len) {
|
||||
assert((len%4) == 0);
|
||||
printf(" dumping %p len 0x%x\n", d, len);
|
||||
for (int i = 0; i < len/4; i++) {
|
||||
if (i != 0 && (i%0x10) == 0) printf("\n");
|
||||
printf("%8x ", d[i]);
|
||||
}
|
||||
printf("\n");
|
||||
}
|
||||
|
||||
// *********** ioctl interceptor ***********
|
||||
|
||||
extern "C" {
|
||||
|
||||
int (*my_ioctl)(int filedes, unsigned long request, void *argp) = NULL;
|
||||
#undef ioctl
|
||||
int ioctl(int filedes, unsigned long request, void *argp) {
|
||||
request &= 0xFFFFFFFF; // needed on QCOM2
|
||||
if (my_ioctl == NULL) my_ioctl = reinterpret_cast<decltype(my_ioctl)>(dlsym(RTLD_NEXT, "ioctl"));
|
||||
Thneed *thneed = g_thneed;
|
||||
|
||||
// save the fd
|
||||
if (request == IOCTL_KGSL_GPUOBJ_ALLOC) g_fd = filedes;
|
||||
|
||||
// note that this runs always, even without a thneed object
|
||||
if (request == IOCTL_KGSL_DRAWCTXT_CREATE) {
|
||||
struct kgsl_drawctxt_create *create = (struct kgsl_drawctxt_create *)argp;
|
||||
create->flags &= ~KGSL_CONTEXT_PRIORITY_MASK;
|
||||
create->flags |= 6 << KGSL_CONTEXT_PRIORITY_SHIFT; // priority from 1-15, 1 is max priority
|
||||
printf("IOCTL_KGSL_DRAWCTXT_CREATE: creating context with flags 0x%x\n", create->flags);
|
||||
}
|
||||
|
||||
if (thneed != NULL) {
|
||||
if (request == IOCTL_KGSL_GPU_COMMAND) {
|
||||
struct kgsl_gpu_command *cmd = (struct kgsl_gpu_command *)argp;
|
||||
if (thneed->record) {
|
||||
thneed->timestamp = cmd->timestamp;
|
||||
thneed->context_id = cmd->context_id;
|
||||
thneed->cmds.push_back(unique_ptr<CachedCommand>(new CachedCommand(thneed, cmd)));
|
||||
}
|
||||
if (thneed->debug >= 1) {
|
||||
printf("IOCTL_KGSL_GPU_COMMAND(%2zu): flags: 0x%lx context_id: %u timestamp: %u numcmds: %d numobjs: %d\n",
|
||||
thneed->cmds.size(),
|
||||
cmd->flags,
|
||||
cmd->context_id, cmd->timestamp, cmd->numcmds, cmd->numobjs);
|
||||
}
|
||||
} else if (request == IOCTL_KGSL_GPUOBJ_SYNC) {
|
||||
struct kgsl_gpuobj_sync *cmd = (struct kgsl_gpuobj_sync *)argp;
|
||||
struct kgsl_gpuobj_sync_obj *objs = (struct kgsl_gpuobj_sync_obj *)(cmd->objs);
|
||||
|
||||
if (thneed->debug >= 2) {
|
||||
printf("IOCTL_KGSL_GPUOBJ_SYNC count:%d ", cmd->count);
|
||||
for (int i = 0; i < cmd->count; i++) {
|
||||
printf(" -- offset:0x%lx len:0x%lx id:%d op:%d ", objs[i].offset, objs[i].length, objs[i].id, objs[i].op);
|
||||
}
|
||||
printf("\n");
|
||||
}
|
||||
|
||||
if (thneed->record) {
|
||||
thneed->cmds.push_back(unique_ptr<CachedSync>(new
|
||||
CachedSync(thneed, string((char *)objs, sizeof(struct kgsl_gpuobj_sync_obj)*cmd->count))));
|
||||
}
|
||||
} else if (request == IOCTL_KGSL_DEVICE_WAITTIMESTAMP_CTXTID) {
|
||||
struct kgsl_device_waittimestamp_ctxtid *cmd = (struct kgsl_device_waittimestamp_ctxtid *)argp;
|
||||
if (thneed->debug >= 1) {
|
||||
printf("IOCTL_KGSL_DEVICE_WAITTIMESTAMP_CTXTID: context_id: %d timestamp: %d timeout: %d\n",
|
||||
cmd->context_id, cmd->timestamp, cmd->timeout);
|
||||
}
|
||||
} else if (request == IOCTL_KGSL_SETPROPERTY) {
|
||||
if (thneed->debug >= 1) {
|
||||
struct kgsl_device_getproperty *prop = (struct kgsl_device_getproperty *)argp;
|
||||
printf("IOCTL_KGSL_SETPROPERTY: 0x%x sizebytes:%zu\n", prop->type, prop->sizebytes);
|
||||
if (thneed->debug >= 2) {
|
||||
hexdump((uint8_t *)prop->value, prop->sizebytes);
|
||||
if (prop->type == KGSL_PROP_PWR_CONSTRAINT) {
|
||||
struct kgsl_device_constraint *constraint = (struct kgsl_device_constraint *)prop->value;
|
||||
hexdump((uint8_t *)constraint->data, constraint->size);
|
||||
}
|
||||
}
|
||||
}
|
||||
} else if (request == IOCTL_KGSL_DRAWCTXT_CREATE || request == IOCTL_KGSL_DRAWCTXT_DESTROY) {
|
||||
// this happens
|
||||
} else if (request == IOCTL_KGSL_GPUOBJ_ALLOC || request == IOCTL_KGSL_GPUOBJ_FREE) {
|
||||
// this happens
|
||||
} else {
|
||||
if (thneed->debug >= 1) {
|
||||
printf("other ioctl %lx\n", request);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
int ret = my_ioctl(filedes, request, argp);
|
||||
// NOTE: This error message goes into stdout and messes up pyenv
|
||||
// if (ret != 0) printf("ioctl returned %d with errno %d\n", ret, errno);
|
||||
return ret;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
// *********** GPUMalloc ***********
|
||||
|
||||
GPUMalloc::GPUMalloc(int size, int fd) {
|
||||
struct kgsl_gpuobj_alloc alloc;
|
||||
memset(&alloc, 0, sizeof(alloc));
|
||||
alloc.size = size;
|
||||
alloc.flags = 0x10000a00;
|
||||
ioctl(fd, IOCTL_KGSL_GPUOBJ_ALLOC, &alloc);
|
||||
void *addr = mmap64(NULL, alloc.mmapsize, 0x3, 0x1, fd, alloc.id*0x1000);
|
||||
assert(addr != MAP_FAILED);
|
||||
|
||||
base = (uint64_t)addr;
|
||||
remaining = size;
|
||||
}
|
||||
|
||||
GPUMalloc::~GPUMalloc() {
|
||||
// TODO: free the GPU malloced area
|
||||
}
|
||||
|
||||
void *GPUMalloc::alloc(int size) {
|
||||
void *ret = (void*)base;
|
||||
size = (size+0xff) & (~0xFF);
|
||||
assert(size <= remaining);
|
||||
remaining -= size;
|
||||
base += size;
|
||||
return ret;
|
||||
}
|
||||
|
||||
// *********** CachedSync, at the ioctl layer ***********
|
||||
|
||||
void CachedSync::exec() {
|
||||
struct kgsl_gpuobj_sync cmd;
|
||||
|
||||
cmd.objs = (uint64_t)data.data();
|
||||
cmd.obj_len = data.length();
|
||||
cmd.count = data.length() / sizeof(struct kgsl_gpuobj_sync_obj);
|
||||
|
||||
int ret = ioctl(thneed->fd, IOCTL_KGSL_GPUOBJ_SYNC, &cmd);
|
||||
assert(ret == 0);
|
||||
}
|
||||
|
||||
// *********** CachedCommand, at the ioctl layer ***********
|
||||
|
||||
CachedCommand::CachedCommand(Thneed *lthneed, struct kgsl_gpu_command *cmd) {
|
||||
thneed = lthneed;
|
||||
assert(cmd->numsyncs == 0);
|
||||
|
||||
memcpy(&cache, cmd, sizeof(cache));
|
||||
|
||||
if (cmd->numcmds > 0) {
|
||||
cmds = make_unique<struct kgsl_command_object[]>(cmd->numcmds);
|
||||
memcpy(cmds.get(), (void *)cmd->cmdlist, sizeof(struct kgsl_command_object)*cmd->numcmds);
|
||||
cache.cmdlist = (uint64_t)cmds.get();
|
||||
for (int i = 0; i < cmd->numcmds; i++) {
|
||||
void *nn = thneed->ram->alloc(cmds[i].size);
|
||||
memcpy(nn, (void*)cmds[i].gpuaddr, cmds[i].size);
|
||||
cmds[i].gpuaddr = (uint64_t)nn;
|
||||
}
|
||||
}
|
||||
|
||||
if (cmd->numobjs > 0) {
|
||||
objs = make_unique<struct kgsl_command_object[]>(cmd->numobjs);
|
||||
memcpy(objs.get(), (void *)cmd->objlist, sizeof(struct kgsl_command_object)*cmd->numobjs);
|
||||
cache.objlist = (uint64_t)objs.get();
|
||||
for (int i = 0; i < cmd->numobjs; i++) {
|
||||
void *nn = thneed->ram->alloc(objs[i].size);
|
||||
memset(nn, 0, objs[i].size);
|
||||
objs[i].gpuaddr = (uint64_t)nn;
|
||||
}
|
||||
}
|
||||
|
||||
kq = thneed->ckq;
|
||||
thneed->ckq.clear();
|
||||
}
|
||||
|
||||
void CachedCommand::exec() {
|
||||
cache.timestamp = ++thneed->timestamp;
|
||||
int ret = ioctl(thneed->fd, IOCTL_KGSL_GPU_COMMAND, &cache);
|
||||
|
||||
if (thneed->debug >= 1) printf("CachedCommand::exec got %d\n", ret);
|
||||
|
||||
if (thneed->debug >= 2) {
|
||||
for (auto &it : kq) {
|
||||
it->debug_print(false);
|
||||
}
|
||||
}
|
||||
|
||||
assert(ret == 0);
|
||||
}
|
||||
|
||||
// *********** Thneed ***********
|
||||
|
||||
Thneed::Thneed(bool do_clinit, cl_context _context) {
|
||||
// TODO: QCOM2 actually requires a different context
|
||||
//context = _context;
|
||||
if (do_clinit) clinit();
|
||||
assert(g_fd != -1);
|
||||
fd = g_fd;
|
||||
ram = make_unique<GPUMalloc>(0x80000, fd);
|
||||
timestamp = -1;
|
||||
g_thneed = this;
|
||||
char *thneed_debug_env = getenv("THNEED_DEBUG");
|
||||
debug = (thneed_debug_env != NULL) ? atoi(thneed_debug_env) : 0;
|
||||
}
|
||||
|
||||
void Thneed::wait() {
|
||||
struct kgsl_device_waittimestamp_ctxtid wait;
|
||||
wait.context_id = context_id;
|
||||
wait.timestamp = timestamp;
|
||||
wait.timeout = -1;
|
||||
|
||||
uint64_t tb = nanos_since_boot();
|
||||
int wret = ioctl(fd, IOCTL_KGSL_DEVICE_WAITTIMESTAMP_CTXTID, &wait);
|
||||
uint64_t te = nanos_since_boot();
|
||||
|
||||
if (debug >= 1) printf("wait %d after %lu us\n", wret, (te-tb)/1000);
|
||||
}
|
||||
|
||||
void Thneed::execute(float **finputs, float *foutput, bool slow) {
|
||||
uint64_t tb, te;
|
||||
if (debug >= 1) tb = nanos_since_boot();
|
||||
|
||||
// ****** copy inputs
|
||||
copy_inputs(finputs, true);
|
||||
|
||||
// ****** run commands
|
||||
int i = 0;
|
||||
for (auto &it : cmds) {
|
||||
++i;
|
||||
if (debug >= 1) printf("run %2d @ %7lu us: ", i, (nanos_since_boot()-tb)/1000);
|
||||
it->exec();
|
||||
if ((i == cmds.size()) || slow) wait();
|
||||
}
|
||||
|
||||
// ****** copy outputs
|
||||
copy_output(foutput);
|
||||
|
||||
if (debug >= 1) {
|
||||
te = nanos_since_boot();
|
||||
printf("model exec in %lu us\n", (te-tb)/1000);
|
||||
}
|
||||
}
|
||||
@@ -145,6 +145,10 @@ void Panda::set_can_speed_kbps(uint16_t bus, uint16_t speed) {
|
||||
handle->control_write(0xde, bus, (speed * 10));
|
||||
}
|
||||
|
||||
void Panda::set_can_fd_auto(uint16_t bus, bool enabled) {
|
||||
handle->control_write(0xe8, bus, enabled);
|
||||
}
|
||||
|
||||
void Panda::set_data_speed_kbps(uint16_t bus, uint16_t speed) {
|
||||
handle->control_write(0xf9, bus, (speed * 10));
|
||||
}
|
||||
|
||||
@@ -77,6 +77,7 @@ public:
|
||||
void enable_deepsleep();
|
||||
void send_heartbeat(bool engaged);
|
||||
void set_can_speed_kbps(uint16_t bus, uint16_t speed);
|
||||
void set_can_fd_auto(uint16_t bus, bool enabled);
|
||||
void set_data_speed_kbps(uint16_t bus, uint16_t speed);
|
||||
void set_canfd_non_iso(uint16_t bus, bool non_iso);
|
||||
void can_send(const capnp::List<cereal::CanData>::Reader &can_data_list);
|
||||
|
||||
@@ -36,7 +36,7 @@ PandaUsbHandle::PandaUsbHandle(std::string serial) : PandaCommsHandle(serial) {
|
||||
for (size_t i = 0; i < num_devices; ++i) {
|
||||
libusb_device_descriptor desc;
|
||||
libusb_get_device_descriptor(dev_list[i], &desc);
|
||||
if (desc.idVendor == 0xbbaa && desc.idProduct == 0xddcc) {
|
||||
if (desc.idVendor == 0x3801 && desc.idProduct == 0xddcc) {
|
||||
int ret = libusb_open(dev_list[i], &dev_handle);
|
||||
if (dev_handle == NULL || ret < 0) { goto fail; }
|
||||
|
||||
@@ -110,7 +110,7 @@ std::vector<std::string> PandaUsbHandle::list() {
|
||||
libusb_device *device = dev_list[i];
|
||||
libusb_device_descriptor desc;
|
||||
libusb_get_device_descriptor(device, &desc);
|
||||
if (desc.idVendor == 0xbbaa && desc.idProduct == 0xddcc) {
|
||||
if (desc.idVendor == 0x3801 && desc.idProduct == 0xddcc) {
|
||||
libusb_device_handle *handle = NULL;
|
||||
int ret = libusb_open(device, &handle);
|
||||
if (ret < 0) { goto finish; }
|
||||
|
||||
@@ -67,6 +67,10 @@ Panda *connect(std::string serial="", uint32_t index=0) {
|
||||
}
|
||||
//panda->enable_deepsleep();
|
||||
|
||||
for (int i = 0; i < PANDA_BUS_CNT; i++) {
|
||||
panda->set_can_fd_auto(i, true);
|
||||
}
|
||||
|
||||
if (!panda->up_to_date() && !getenv("BOARDD_SKIP_FW_CHECK")) {
|
||||
throw std::runtime_error("Panda firmware out of date. Run pandad.py to update.");
|
||||
}
|
||||
@@ -412,6 +416,7 @@ void process_peripheral_state(Panda *panda, PubMaster *pm, bool no_fan_control)
|
||||
|
||||
if (ir_pwr != prev_ir_pwr || sm.frame % 100 == 0 || ir_pwr >= 50.0) {
|
||||
panda->set_ir_pwr(ir_pwr);
|
||||
Hardware::set_ir_power(ir_pwr);
|
||||
prev_ir_pwr = ir_pwr;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -239,7 +239,7 @@ int PandaSpiHandle::spi_transfer_retry(uint8_t endpoint, uint8_t *tx_data, uint1
|
||||
// due to full TX buffers
|
||||
nack_count += 1;
|
||||
if (nack_count > 3) {
|
||||
SPILOG(LOGE, "NACK sleep %d", nack_count);
|
||||
SPILOG(LOGD, "NACK sleep %d", nack_count);
|
||||
usleep(std::clamp(nack_count*10, 200, 2000));
|
||||
}
|
||||
}
|
||||
@@ -418,7 +418,7 @@ fail:
|
||||
}
|
||||
}
|
||||
|
||||
if (ret > 0) ret = -1;
|
||||
if (ret >= 0) ret = -1;
|
||||
return ret;
|
||||
}
|
||||
#endif
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user