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Update Linux Multi GPU TensorRT pipeline to TensorRT 8.4 (#11923)

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* Try manually installing trt8.4 in multi-gpu pipeline

* Remove stmts that clean up cmake, ctest. Update tensorrt repository name passed to get_docker_image.py

* Update trt and cudnn home

* Don't install trtexec cli tool.

* Increase job timeout

* Revert timeout change and use trt placeholder builder build option
This commit is contained in:
Adrian Lizarraga 2022-06-21 07:59:11 -07:00 committed by GitHub
parent 859ef277a0
commit b20daeda81
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3 changed files with 17 additions and 10 deletions
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19
tools/ci_build/github/linux/docker/Dockerfile.ubuntu_tensorrt
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@ -1,15 +1,22 @@
# Tag: nvcr.io/nvidia/tensorrt:21.12-py3
# Label: com.nvidia.cuda.version: 11.5.0
# Label: com.nvidia.cudnn.version: 8.3.1.22
# Tag: nvidia/cuda:11.6.1-cudnn8-devel-ubuntu20.04
# Label: com.nvidia.cuda.version: 11.6.1
# Label: com.nvidia.cudnn.version: 8.4.0
# Ubuntu 20.04
FROM nvcr.io/nvidia/tensorrt:21.12-py3
FROM nvidia/cuda:11.6.1-cudnn8-devel-ubuntu20.04
ARG PYTHON_VERSION=3.8
ARG DEBIAN_FRONTEND=noninteractive
ADD scripts /tmp/scripts
RUN /tmp/scripts/install_ubuntu.sh -p $PYTHON_VERSION && /tmp/scripts/install_os_deps.sh && /tmp/scripts/install_python_deps.sh -p $PYTHON_VERSION && rm -rf /tmp/scripts \
&& rm /usr/local/bin/cmake && rm /usr/local/bin/ctest && rm -r /usr/local/share/cmake-3.14
RUN /tmp/scripts/install_ubuntu.sh -p $PYTHON_VERSION && /tmp/scripts/install_os_deps.sh && /tmp/scripts/install_python_deps.sh -p $PYTHON_VERSION && rm -rf /tmp/scripts
# Install TensorRT
RUN v="8.4.1-1+cuda11.6" &&\
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub &&\
apt-get update &&\
sudo apt-get install -y libnvinfer8=${v} libnvonnxparsers8=${v} libnvparsers8=${v} libnvinfer-plugin8=${v} \
libnvinfer-dev=${v} libnvonnxparsers-dev=${v} libnvparsers-dev=${v} libnvinfer-plugin-dev=${v} \
python3-libnvinfer=${v}
WORKDIR /root

5
tools/ci_build/github/linux/run_build.sh
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@ -60,9 +60,10 @@ else
_CUDNN_VERSION=$(echo $CUDNN_VERSION | cut -d. -f1-2)
python3 $SCRIPT_DIR/../../build.py --build_dir /build \
--config Release $COMMON_BUILD_ARGS \
--use_tensorrt --tensorrt_home /workspace/tensorrt \
--tensorrt_placeholder_builder \
--use_tensorrt --tensorrt_home /usr/lib/x86_64-linux-gnu/ \
--cuda_home /usr/local/cuda \
--cudnn_home /usr/local/cuda $BUILD_EXTR_PAR
--cudnn_home /usr/lib/x86_64-linux-gnu/ $BUILD_EXTR_PAR
else #cpu and openvino
python3 $SCRIPT_DIR/../../build.py --build_dir /build \
--config Release $COMMON_BUILD_ARGS $BUILD_EXTR_PAR

3
tools/ci_build/github/linux/run_dockerbuild.sh
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@ -96,8 +96,7 @@ elif [ $BUILD_DEVICE = "gpu" ]; then
--docker-build-args="--build-arg BASEIMAGE=nvcr.io/nvidia/cuda:11.3.1-cudnn8-devel-${BUILD_OS} --build-arg BUILD_USER=onnxruntimedev --build-arg BUILD_UID=$(id -u) --build-arg PYTHON_VERSION=${PYTHON_VER} --build-arg INSTALL_DEPS_EXTRA_ARGS=\"${INSTALL_DEPS_EXTRA_ARGS}\" --build-arg USE_CONDA=${USE_CONDA} --network=host" \
--dockerfile Dockerfile.ubuntu_gpu_training --context .
elif [[ $BUILD_DEVICE = "tensorrt"* ]]; then
# TensorRT container release 21.12
IMAGE="$BUILD_OS-cuda11.5-cudnn8.3-tensorrt8.2"
IMAGE="$BUILD_OS-cuda11.6-cudnn8.4-tensorrt8.4"
DOCKER_FILE=Dockerfile.ubuntu_tensorrt
$GET_DOCKER_IMAGE_CMD --repository "onnxruntime-$IMAGE" \