fix multinomial sampling #25
Workflow file for this run
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name: pr_ete_test | |
on: | |
pull_request: | |
paths: | |
- ".github/workflows/pr_ete_test.yml" | |
- "cmake/**" | |
- "src/**" | |
- "autotest/**" | |
- "3rdparty/**" | |
- "lmdeploy/**" | |
- "requirements/**" | |
- "requirements.txt" | |
- "CMakeLists.txt" | |
- "setup.py" | |
workflow_dispatch: | |
env: | |
HOST_PIP_CACHE_DIR: /nvme/github-actions/pip-cache | |
HOST_LOCALTIME: /usr/share/zoneinfo/Asia/Shanghai | |
jobs: | |
pr_functions_test: | |
runs-on: [self-hosted, linux-a100-pr] | |
timeout-minutes: 120 | |
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/share_data/github-actions/pip-cache:/root/.cache/pip | |
- /nvme/share_data/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$(nproc) && make install | |
- name: Install lmdeploy | |
run: | | |
python3 -m pip install packaging protobuf transformers_stream_generator transformers datasets | |
# manually install flash attn | |
# the install packeage from. https://github.com/Dao-AILab/flash-attention/releases/download/v2.3.6/flash_attn-2.3.6+cu118torch2.0cxx11abiFALSE-cp38-cp38-linux_x86_64.whl | |
python3 -m pip install /root/packages/flash_attn-2.3.6+cu118torch2.1cxx11abiFALSE-cp38-cp38-linux_x86_64.whl | |
python3 -m pip install -r requirements.txt -r requirements/test.txt | |
python3 -m pip install . | |
- name: Check env | |
run: | | |
python3 -m pip list | |
lmdeploy check_env | |
- name: Test lmdeploy | |
timeout-minutes: 120 | |
run: CUDA_VISIBLE_DEVICES=5,6 pytest autotest -m pr_test --alluredir=allure-results --clean-alluredir | |
- name: Generate reports | |
if: always() | |
run: | | |
export date_today="$(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 |