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daily_ete_test.yml
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name: daily_ete_test
on:
workflow_dispatch:
schedule:
- cron: '00 18 * * *'
env:
HOST_PIP_CACHE_DIR: /nvme/github-actions/pip-cache
HOST_LOCALTIME: /usr/share/zoneinfo/Asia/Shanghai
jobs:
test_functions:
runs-on: [self-hosted, linux-a100]
timeout-minutes: 420
env:
REPORT_DIR: /nvme/qa_test_models/test-reports
container:
image: nvcr.io/nvidia/tritonserver:22.12-py3
options: "--gpus=all --ipc=host --user root -e PIP_CACHE_DIR=/root/.cache/pip"
volumes:
- /nvme/github-actions/pip-cache:/root/.cache/pip
- /nvme/github-actions/packages:/root/packages
- /nvme/qa_test_models:/nvme/qa_test_models
- /usr/share/zoneinfo/Asia/Shanghai:/etc/localtime:ro
steps:
- name: Setup systems
run: |
rm /etc/apt/sources.list.d/cuda*.list
apt-get update && apt-get install -y --no-install-recommends rapidjson-dev \
libgoogle-glog-dev libgl1 openjdk-8-jre-headless
dpkg -i /root/packages/allure_2.24.1-1_all.deb
rm -rf /var/lib/apt/lists/*
- name: Clone repository
uses: actions/checkout@v2
- name: Install pytorch
run: |
python3 -m pip cache dir
python3 -m pip install torch==2.1.0 torchvision==0.16.0 --index-url https://download.pytorch.org/whl/cu118
- name: Build lmdeploy
run: |
python3 -m pip install cmake
python3 -m pip install -r requirements/build.txt
mkdir build
cd build
cmake .. \
-DCMAKE_BUILD_TYPE=RelWithDebInfo \
-DCMAKE_EXPORT_COMPILE_COMMANDS=1 \
-DCMAKE_INSTALL_PREFIX=/opt/tritonserver \
-DBUILD_PY_FFI=ON \
-DBUILD_MULTI_GPU=ON \
-DCMAKE_CUDA_FLAGS="-lineinfo" \
-DUSE_NVTX=ON \
-DSM=80 \
-DCMAKE_CUDA_ARCHITECTURES=80 \
-DBUILD_TEST=OFF
make -j$(nproc) && make install
- name: Install lmdeploy
run: |
python3 -m pip install packaging protobuf transformers_stream_generator transformers datasets
# manually install flash attn
# the install packeage from. https://github.com/Dao-AILab/flash-attention/releases/download/v2.3.6/flash_attn-2.3.6+cu118torch2.0cxx11abiFALSE-cp38-cp38-linux_x86_64.whl
python3 -m pip install /root/packages/flash_attn-2.3.6+cu118torch2.1cxx11abiFALSE-cp38-cp38-linux_x86_64.whl
python3 -m pip install -r requirements.txt -r requirements/test.txt
python3 -m pip install .
- name: Check env
run: |
python3 -m pip list
lmdeploy check_env
- name: Test lmdeploy - quantization w4a16
continue-on-error: true
run: |
pytest autotest/tools/quantization/test_quantization_w4a16.py -m 'not pr_test' -n 8 --alluredir=allure-results --clean-alluredir
- name: Test lmdeploy - quantization kv int8
continue-on-error: true
run: |
pytest autotest/tools/quantization/test_quantization_kvint8.py -n 8 --alluredir=allure-results
- name: Test lmdeploy - quantization w8a8
continue-on-error: true
run: |
pytest autotest/tools/quantization/test_quantization_w8a8.py -n 8 --alluredir=allure-results
- name: Test lmdeploy - quantization kv int8 and w4a16
continue-on-error: true
run: |
pytest autotest/tools/quantization/test_quantization_kvint8_w4a16.py -n 8 --alluredir=allure-results
- name: Test lmdeploy - convert
continue-on-error: true
run: |
pytest autotest/tools/convert -m 'not pr_test' -n 6 --alluredir=allure-results --dist loadgroup
- name: Test lmdeploy - interface turbomind case
continue-on-error: true
timeout-minutes: 20
run: |
pytest autotest/interface/pipeline/test_pipeline_turbomind_func.py -m 'not pr_test' --alluredir=allure-results
- name: Test lmdeploy - pipeline turbomind
continue-on-error: true
timeout-minutes: 45
run: pytest autotest/tools/pipeline/test_pipeline_chat_turbomind.py -m 'not pr_test' --alluredir=allure-results
- name: Test lmdeploy - pipeline torch
continue-on-error: true
timeout-minutes: 75
run: pytest autotest/tools/pipeline/test_pipeline_chat_pytorch.py -m 'not pr_test' --alluredir=allure-results
- name: Test lmdeploy - restful turbomind
continue-on-error: true
timeout-minutes: 60
run: pytest autotest/tools/restful/test_restful_chat_turbomind.py -m 'not pr_test' --alluredir=allure-results
- name: Test lmdeploy - restful torch
continue-on-error: true
timeout-minutes: 80
run: pytest autotest/tools/restful/test_restful_chat_pytorch.py -m 'not pr_test' --alluredir=allure-results
- name: Test lmdeploy - chat workspace
continue-on-error: true
timeout-minutes: 30
run: |
pytest autotest/tools/chat/test_command_chat_workspace.py -m 'not pr_test' -n 4 --alluredir=allure-results
- name: Test lmdeploy - chat hf turbomind
continue-on-error: true
timeout-minutes: 45
run: |
pytest autotest/tools/chat/test_command_chat_hf_turbomind.py -m 'not pr_test' -n 4 --alluredir=allure-results
- name: Test lmdeploy - chat hf torch
continue-on-error: true
timeout-minutes: 60
run: |
pytest autotest/tools/chat/test_command_chat_hf_pytorch.py -m 'not pr_test' -n 4 --alluredir=allure-results
- name: Test lmdeploy - rerun all fail cases
timeout-minutes: 60
run: |
pytest autotest --lf --alluredir=allure-results
- name: Generate reports
if: always()
run: |
export date_today="$(date +'%Y%m%d-%H%M%S')"
export report_dir="$REPORT_DIR/$date_today"
echo "Save report to $ALLURE_DIR"
allure generate -c -o $report_dir
- name: Clear workfile
if: always()
run: |
export workdir=$(pwd)
cd ..
rm -rf $workdir
mkdir $workdir
chmod -R 777 $workdir
test_triton:
runs-on: [self-hosted, linux-a100]
timeout-minutes: 30
env:
HF_MODEL: /nvme/qa_test_models/internlm-chat-20b
WORKDIR: /nvme/qa_test_models/triton_workspace
TB_MODEL: internlm-chat-20b-fp16-tp2
GRPC_PORT: 33337
steps:
- name: Clone repository
uses: actions/checkout@v2
- name: Create test container
run: |
export CONTAINER_ID=$(docker create \
--rm \
--gpus='"device=4,5"' \
--shm-size 16g \
--cap-add=SYS_PTRACE \
--cap-add=SYS_ADMIN \
--security-opt seccomp=unconfined \
--name "lmdeploy-ci-triton-$GITHUB_RUN_ID" \
--workdir /__w/lmdeploy/lmdeploy \
--env NCCL_LAUNCH_MODE=GROUP \
-v $(pwd)/../../:/__w \
-v ${HF_MODEL}:/root/workspace/hf_model \
-v ${WORKDIR}:/root/workspace/workdir \
-v ${HOST_PIP_CACHE_DIR}:/root/.cache/pip \
-v ${HOST_LOCALTIME}:/etc/localtime:ro \
openmmlab/lmdeploy:latest tail -f /dev/null \
)
docker start $CONTAINER_ID
echo "CONTAINER_ID=$CONTAINER_ID"
echo "CONTAINER_ID=$CONTAINER_ID" >> $GITHUB_ENV
- name: Build lmdeploy from source
run: |
docker exec $CONTAINER_ID mkdir build
docker exec --workdir /__w/lmdeploy/lmdeploy/build \
--env http_proxy=${{secrets.PROXY}} \
--env https_proxy=${{secrets.PROXY}} \
--env HTTP_PROXY=${{secrets.PROXY}} \
--env HTTPS_PROXY=${{secrets.PROXY}} \
--env no_proxy="localhost,127.0.0.1" \
--env NO_PROXY="localhost,127.0.0.1" \
$CONTAINER_ID cmake .. \
-DCMAKE_BUILD_TYPE=RelWithDebInfo \
-DCMAKE_EXPORT_COMPILE_COMMANDS=1 \
-DCMAKE_INSTALL_PREFIX=/opt/tritonserver \
-DBUILD_PY_FFI=ON \
-DBUILD_MULTI_GPU=ON \
-DCMAKE_CUDA_FLAGS="-lineinfo" \
-DUSE_NVTX=ON \
-DSM=80 \
-DCMAKE_CUDA_ARCHITECTURES=80 \
-DBUILD_TEST=OFF
docker exec --workdir /__w/lmdeploy/lmdeploy/build $CONTAINER_ID make -j$(nproc)
docker exec --workdir /__w/lmdeploy/lmdeploy/build $CONTAINER_ID make install \
--env http_proxy=${{secrets.PROXY}} \
--env https_proxy=${{secrets.PROXY}} \
--env HTTP_PROXY=${{secrets.PROXY}} \
--env HTTPS_PROXY=${{secrets.PROXY}}
- name: Install lmdeploy
run: |
docker exec \
--env http_proxy=${{secrets.PROXY}} \
--env https_proxy=${{secrets.PROXY}} \
$CONTAINER_ID python3 -m pip install tritonclient[grpc] protobuf
docker exec \
--env http_proxy=${{secrets.PROXY}} \
--env https_proxy=${{secrets.PROXY}} \
$CONTAINER_ID python3 -m pip install -r requirements/test.txt
docker exec \
--env http_proxy=${{secrets.PROXY}} \
--env https_proxy=${{secrets.PROXY}} \
$CONTAINER_ID python3 -m pip install .
docker exec $CONTAINER_ID lmdeploy check_env
- name: Convert to turbomind model
run: |
docker exec $CONTAINER_ID \
lmdeploy convert \
internlm-chat-20b \
/root/workspace/hf_model \
--tp 2 \
--dst-path /root/workspace/workdir/${TB_MODEL}
- name: Start triton server service
run: |
docker exec --detach $CONTAINER_ID bash -c \
"tritonserver \
--model-repository=/root/workspace/workdir/${TB_MODEL}/model_repository \
--allow-http=0 \
--allow-grpc=1 \
--grpc-port=${GRPC_PORT} \
--log-verbose=0 \
--allow-metrics=1 > run.log 2>&1 ; touch finish.txt"
# wait for triton server to fully start up
sleep 180s
# print triton server log file
cat run.log
python3 -c 'import os; assert not os.path.exists("finish.txt"), "Failed to start tritonserver"'
- name: Test triton server
run: |
docker exec \
--env no_proxy="localhost,127.0.0.1" \
--env NO_PROXY="localhost,127.0.0.1" \
$CONTAINER_ID python3 .github/scripts/test_triton_server.py --port ${GRPC_PORT}
# print triton server log file
cat run.log
- name: Clear workfile
if: always()
run: |
export workdir=$(pwd)
docker exec --workdir /__w/lmdeploy $CONTAINER_ID rm -rf lmdeploy
mkdir $workdir
chmod -R 777 $workdir
docker exec --workdir /__w/lmdeploy $CONTAINER_ID rm -rf /root/workspace/workdir/${TB_MODEL}
docker stop $CONTAINER_ID
notify_to_feishu:
if: always() && !cancelled() && (github.ref_name == 'develop' || github.ref_name == 'main')
needs: [test_functions, test_triton]
timeout-minutes: 5
runs-on: [self-hosted, linux-a100]
steps:
- name: fail notify
if: contains(needs.*.result, 'failure')
run: |
curl -X POST -H "Content-Type: application/json" -d '{"msg_type":"post","content":{"post":{"zh_cn":{"title":"Lmdeploy- daily test failed","content":[[{"tag":"text","text":"branch: ${{github.ref_name}}, run action: ${{github.workflow}} failed. "},{"tag":"a","text":"Please click here for details ","href":"https://github.com/'${{ github.repository }}'/actions/runs/'${GITHUB_RUN_ID}'"},{"tag":"at","user_id":"'${{ secrets.FEISHU_USER_ID }}'"}]]}}}}' ${{ secrets.FEISHU_WEBHOOK_URL }}