Skip to content
build

Transfer to cpu only when torch.Tensor arguments in onnx export #6266

Sign in to view logs

Transfer to cpu only when torch.Tensor arguments in onnx export

Transfer to cpu only when torch.Tensor arguments in onnx export #6266

Workflow file for this run

.github/workflows/build.yml at 3152a27
name: build
on:
push:
paths-ignore:
- ".github/scripts/**"
- "demo/**"
- "docker/**"
- "tools/**"
pull_request:
paths-ignore:
- ".github/scripts/**"
- "demo/**"
- "docker/**"
- "tools/**"
- "docs/**"
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build_cpu_model_convert:
runs-on: ubuntu-20.04
strategy:
matrix:
torch: [1.9.0]
include:
- torch: 1.9.0
torchvision: 0.10.0
steps:
- uses: actions/checkout@v2
- name: Install PyTorch
run: |
python -m pip install --upgrade pip
python -V
python -m pip show pip
python -m pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install unittest dependencies
run: |
python -m pip install openmim
python -m pip install -r requirements.txt
python -m pip install -r requirements/backends.txt
python -m mim install "mmcv==2.0.1"
python -m mim install -r requirements/codebases.txt
python -m pip install clip numba transformers numpy==1.23 albumentations
python -m pip list
- name: Install mmyolo
run: |
git clone -b dev --depth 1 https://github.com/open-mmlab/mmyolo.git /home/runner/work/mmyolo
python -m pip install -v -e /home/runner/work/mmyolo
- name: Install mmpose
run: |
git clone --depth 1 https://github.com/open-mmlab/mmpose.git /home/runner/work/mmpose
python -m pip install -v -e /home/runner/work/mmpose
- name: Build and install
run: |
rm -rf .eggs && python -m pip install -e .
python tools/check_env.py
- name: Run python unittests and generate coverage report
run: |
coverage run --branch --source mmdeploy -m pytest -rsE tests
coverage xml
coverage report -m
- name: Run mmyolo deploy unittests
id: badge_status
run: |
python -m pip install xdoctest
cd /home/runner/work/mmyolo
pytest tests/test_deploy
- name: create badge
if: always()
uses: RubbaBoy/BYOB@v1.2.1
with:
NAME: build_cpu_model_convert
LABEL: 'build'
STATUS: ${{ steps.badge_status.conclusion == 'success' && 'passing' || 'failing' }}
COLOR: ${{ steps.badge_status.conclusion == 'success' && 'green' || 'red' }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
build_cpu_sdk:
runs-on: ubuntu-20.04
steps:
- name: Checkout repository
uses: actions/checkout@v3
with:
submodules: 'recursive'
- name: update
run: sudo apt update
- name: gcc-multilib
run: |
sudo apt install gcc-multilib g++-multilib wget libprotobuf-dev protobuf-compiler
sudo apt update
sudo apt install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev libc++1-9 libc++abi1-9
sudo apt install libopencv-dev lcov wget
- name: Build and run SDK unit test without backend
id: badge_status
run: |
mkdir -p build && pushd build
cmake .. -DCMAKE_CXX_COMPILER=g++ -DMMDEPLOY_CODEBASES=all -DMMDEPLOY_BUILD_SDK=ON -DMMDEPLOY_BUILD_SDK_PYTHON_API=OFF -DMMDEPLOY_TARGET_DEVICES=cpu -DMMDEPLOY_COVERAGE=ON -DMMDEPLOY_BUILD_TEST=ON
make -j2
mkdir -p mmdeploy_test_resources/transform
cp ../tests/data/tiger.jpeg mmdeploy_test_resources/transform/
./bin/mmdeploy_tests
lcov --capture --directory . --output-file coverage.info
ls -lah coverage.info
cp coverage.info ../
- name: create badge
if: always()
uses: RubbaBoy/BYOB@v1.2.1
with:
NAME: build_cpu_sdk
LABEL: 'build'
STATUS: ${{ steps.badge_status.conclusion == 'success' && 'passing' || 'failing' }}
COLOR: ${{ steps.badge_status.conclusion == 'success' && 'green' || 'red' }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
cross_build_aarch64:
runs-on: ubuntu-20.04
steps:
- name: Checkout repository
uses: actions/checkout@v3
with:
submodules: 'recursive'
- name: update
run: sudo apt update
- name: Set up Python
uses: actions/setup-python@v2
with:
python-version: 3.8
- name: gcc-multilib
id: badge_status
run: |
sh -ex tools/scripts/ubuntu_cross_build_aarch64.sh
- name: create badge
if: always()
uses: RubbaBoy/BYOB@v1.2.1
with:
NAME: cross_build_aarch64
LABEL: 'build'
STATUS: ${{ steps.badge_status.conclusion == 'success' && 'passing' || 'failing' }}
COLOR: ${{ steps.badge_status.conclusion == 'success' && 'green' || 'red' }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
build_cuda117:
runs-on: ubuntu-20.04
container:
image: pytorch/pytorch:2.0.0-cuda11.7-cudnn8-devel
env:
FORCE_CUDA: 1
steps:
- uses: actions/checkout@v2
- name: Install system dependencies
run: |
apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev
apt-get clean
rm -rf /var/lib/apt/lists/*
- name: Install PyTorch
run: |
python -V
python -m pip show torch torchvision
python -m pip install --no-cache-dir --upgrade pip
- name: Check disk space
continue-on-error: true
run: |
df -h
rm -rf /__t/go
rm -rf /__t/node
rm -rf /__t/Ruby
rm -rf /__t/CodeQL
cat /proc/cpuinfo | grep -ic proc
free
df -h
- name: Install dependencies
run: |
python -V
python -m pip install --no-cache-dir openmim
python -m pip install --no-cache-dir -r requirements.txt
python -m pip install --no-cache-dir -r requirements/backends.txt
python -m mim install "mmcv==2.0.1"
python -m pip install --no-cache-dir -r requirements/codebases.txt
python -m pip install --no-cache-dir -U pycuda numpy==1.23 clip numba transformers albumentations
python -m pip list
- name: Build and install
run: |
rm -rf .eggs && python -m pip install -e .
python tools/check_env.py
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmdeploy -m pytest -rsE tests
coverage xml
coverage report -m
- name: Upload coverage to Codecov
id: badge_status
uses: codecov/codecov-action@v2
with:
file: ./coverage.xml,./coverage.info
flags: unittests
env_vars: OS,PYTHON,CPLUS
name: codecov-umbrella
fail_ci_if_error: false
- name: create badge
if: always()
uses: RubbaBoy/BYOB@v1.2.1
with:
NAME: build_cuda117
LABEL: 'build'
STATUS: ${{ steps.badge_status.conclusion == 'success' && 'passing' || 'failing' }}
COLOR: ${{ steps.badge_status.conclusion == 'success' && 'green' || 'red' }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
build_cuda113:
runs-on: ubuntu-20.04
container:
image: pytorch/pytorch:1.12.0-cuda11.3-cudnn8-devel
steps:
- uses: actions/checkout@v2
- name: Install system dependencies
run: |
apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev
apt-get clean
rm -rf /var/lib/apt/lists/*
- name: Install PyTorch
run: |
python -V
python -m pip show torch torchvision
python -m pip install --no-cache-dir --upgrade pip
- name: Check disk space
continue-on-error: true
run: |
df -h
rm -rf /__t/go
rm -rf /__t/node
rm -rf /__t/Ruby
rm -rf /__t/CodeQL
cat /proc/cpuinfo | grep -ic proc
free
df -h
- name: Install dependencies
run: |
python -V
python -m pip install --no-cache-dir openmim
python -m pip install --no-cache-dir -r requirements.txt
python -m pip install --no-cache-dir -r requirements/backends.txt
python -m mim install --no-cache-dir "mmcv==2.0.1"
python -m pip install --no-cache-dir -r requirements/codebases.txt
python -m pip install --no-cache-dir -U pycuda numpy clip numba transformers albumentations
python -m pip list
- name: Build and install
run: |
rm -rf .eggs && python -m pip install -e .
python tools/check_env.py
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmdeploy -m pytest -rsE tests
coverage xml
coverage report -m
- name: create badge
if: always()
uses: RubbaBoy/BYOB@v1.2.1
with:
NAME: build_cuda113
LABEL: 'build'
STATUS: ${{ steps.badge_status.conclusion == 'success' && 'passing' || 'failing' }}
COLOR: ${{ steps.badge_status.conclusion == 'success' && 'green' || 'red' }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
build_cuda118_linux:
needs: [build_cpu_model_convert, build_cpu_sdk, build_cuda117]
runs-on: [self-hosted, linux-3090]
container:
image: openmmlab/mmdeploy:ubuntu20.04-cuda11.8
options: "--gpus=all --ipc=host"
volumes:
- /data2/pip-cache:/root/.cache/pip
steps:
- name: Checkout repository
uses: actions/checkout@v3
with:
submodules: recursive
- name: Install dependencies
run: |
apt update && apt install unzip
python3 -V
python3 -m pip install opencv-python==4.5.4.60 opencv-python-headless==4.5.4.60 opencv-contrib-python==4.5.4.60
python3 -m pip install openmim numpy pycuda clip transformers
python3 -m pip install -r requirements.txt
python3 -m mim install $(cat requirements/codebases.txt | grep mmpretrain)
python3 -m pip list
- name: Build SDK
run: |
export Torch_DIR=$(python3 -c "import torch;print(torch.utils.cmake_prefix_path + '/Torch')")
bash .github/scripts/linux/build.sh "cpu;cuda" "ort;trt;ncnn;torchscript" \
-Dpplcv_DIR=${pplcv_DIR} \
-DTENSORRT_DIR=${TENSORRT_DIR} \
-DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \
-Dncnn_DIR=${ncnn_DIR} \
-DTorch_DIR=${Torch_DIR}
ls build/lib
- name: Install converter
run: |
rm -rf .eggs && python3 -m pip install -e .
export LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:${LD_LIBRARY_PATH}"
python3 tools/check_env.py
- name: Test TensorRT pipeline
id: badge_status
run: |
export LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:${LD_LIBRARY_PATH}"
export LD_LIBRARY_PATH="/root/workspace/mmdeploy/mmdeploy/lib:${LD_LIBRARY_PATH}"
bash .github/scripts/linux/test_full_pipeline.sh trt cuda
- name: create badge
if: always()
uses: RubbaBoy/BYOB@v1.2.1
with:
NAME: build_cuda118_linux
LABEL: 'build'
STATUS: ${{ steps.badge_status.conclusion == 'success' && 'passing' || 'failing' }}
COLOR: ${{ steps.badge_status.conclusion == 'success' && 'green' || 'red' }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
build_cuda118_windows:
needs: [build_cpu_model_convert, build_cpu_sdk, build_cuda117]
runs-on: [self-hosted, win10-3080]
env:
BASE_ENV: mmdeploy-cuda11.8-torch2.0-py38
defaults:
run:
shell: powershell
steps:
- name: Checkout repository
uses: actions/checkout@v3
with:
submodules: 'recursive'
- name: Setup Python Environment
run: |
echo "============================== Info =============================="
echo "env:path= $env:path"
echo "============================== Info =============================="
conda info
conda info -e
$env:TEMP_ENV = "$pwd/../temp_envs/$env:GITHUB_RUN_ID"
New-Item -Path "$env:TEMP_ENV" -ItemType Directory -Force
echo "TEMP_ENV=$env:TEMP_ENV" >> $env:GITHUB_ENV
conda create -p $env:TEMP_ENV --clone $env:BASE_ENV -y
conda activate $env:TEMP_ENV
python -V
python -m pip install openmim
python -m pip install -r requirements.txt
python -m pip install -r requirements/backends.txt
python -m mim install "mmpretrain>=1.0.0rc7"
python -m pip list
- name: Build mmdeploy
run: |
conda activate $env:TEMP_ENV
python -V
mkdir build
cd build
cmake .. -A x64 -T v142,cuda=$env:CUDA_PATH `
-DMMDEPLOY_BUILD_TEST=ON `
-DMMDEPLOY_BUILD_SDK_CSHARP_API=ON `
-DMMDEPLOY_BUILD_SDK_PYTHON_API=ON `
-DMMDEPLOY_BUILD_SDK=ON `
-DMMDEPLOY_TARGET_DEVICES='cuda' `
-DMMDEPLOY_TARGET_BACKENDS='ort;trt' `
-DMMDEPLOY_CODEBASES='all' `
-Dpplcv_DIR="$env:pplcv_DIR" `
-DOpenCV_DIR="$env:OpenCV_DIR" `
-DTENSORRT_DIR="$env:TENSORRT_DIR" `
-DONNXRUNTIME_DIR="$env:ONNXRUNTIME_GPU_DIR" `
-DMMDEPLOY_BUILD_EXAMPLES=ON `
-DCUDNN_DIR="$env:CUDNN_DIR"
cmake --build . --config Release -- /m
cmake --install . --config Release
ls $pwd\bin\Release
- name: Install mmdeploy converter
run: |
conda activate $env:TEMP_ENV
python -m pip install -e .
python .\tools\check_env.py
- name: Test trt full pipeline
run: |
conda activate $env:TEMP_ENV
$env:path = "$pwd\build\bin\Release;" + $env:path
$env:path = "$env:ONNXRUNTIME_GPU_DIR\lib;" + $env:path
echo $env:path
.github\scripts\windows\test_full_pipeline.ps1 -Backend trt -Device cuda
- name: Clear temp env
if: always()
run: |
conda env remove --prefix "$env:TEMP_ENV"
badge_build_cuda118_windows:
needs: build_cuda118_windows
if: always()
runs-on: ubuntu-20.04
steps:
- name: create badge
uses: RubbaBoy/BYOB@v1.2.1
with:
NAME: build_cuda118_windows
LABEL: 'build'
STATUS: ${{ needs.build_cuda113_windows.result == 'success' && 'passing' || needs.build_cuda113_windows.result }}
COLOR: ${{ needs.build_cuda113_windows.result == 'success' && 'green' || 'red' }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}