Fix repetition penalty for long context #459
Workflow file for this run
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: test | |
| on: | |
| pull_request: | |
| paths: | |
| - ".github/scripts/test_triton_server.py" | |
| - ".github/workflows/test.yml" | |
| - "cmake/**" | |
| - "src/**" | |
| - "autotest/**" | |
| - "3rdparty/**" | |
| - "lmdeploy/**" | |
| - "requirements/**" | |
| - "requirements.txt" | |
| - "CMakeLists.txt" | |
| - "setup.py" | |
| push: | |
| branches: | |
| - main | |
| paths: | |
| - "lmdeploy/version.py" | |
| tags: | |
| - "v*.*.*" | |
| workflow_dispatch: | |
| inputs: | |
| markers: | |
| required: false | |
| description: 'Tested markers. eg: "-m internlm_chat_7b"' | |
| type: string | |
| default: '' | |
| 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: 4320 # 72hours | |
| environment: 'prod' | |
| 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==2.0.1 torchvision==0.15.2 --extra-index-url https://download.pytorch.org/whl/cu117 | |
| - name: Build lmdeploy | |
| run: | | |
| python3 -m pip install cmake | |
| python3 -m pip install -r requirements/build.txt | |
| # use cached build | |
| mkdir build | |
| cd build | |
| cmake .. \ | |
| -DCMAKE_BUILD_TYPE=RelWithDebInfo \ | |
| -DCMAKE_EXPORT_COMPILE_COMMANDS=1 \ | |
| -DCMAKE_INSTALL_PREFIX=./install \ | |
| -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==4.33.0 | |
| # 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+cu118torch2.0cxx11abiFALSE-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 | |
| run: | | |
| pytest autotest ${{github.event.inputs.markers}} --alluredir=allure-results --clean-alluredir | |
| - name: Generate reports | |
| if: always() | |
| run: | | |
| export date_today="$(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 $workdir | |
| test_triton: | |
| runs-on: [self-hosted, linux-a100] | |
| timeout-minutes: 4320 # 72hours | |
| environment: 'prod' | |
| env: | |
| HF_MODEL: /nvme/qa_test_models/internlm-chat-20b | |
| WORKDIR: /nvme/qa_test_models/triton_workspace | |
| TB_MODEL: internlm-chat-20b-fp16-tp2 | |
| GRPC_PORT: 33337 | |
| steps: | |
| - name: Clone repository | |
| uses: actions/checkout@v2 | |
| - name: Create test container | |
| run: | | |
| export CONTAINER_ID=$(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=./install \ | |
| -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 $CONTAINER_ID make install | |
| - name: Install lmdeploy | |
| run: | | |
| docker exec \ | |
| --env http_proxy=${{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 |