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544e53e24e
* remove onnx-tensorrt submodule * add new onnx-tensorrt submodule (experiment) for trt6 * update engine build for trt6 * update compile and compute for tensorrt6.0 * Update tensorrt_execution_provider.cc * Update tensorrt_execution_provider.cc * Update tensorrt_execution_provider.cc * Update tensorrt_execution_provider.cc * switch to onnx-tensorrt master for TensorRT6' * Update tensorrt_execution_provider.cc * Handle dynamic batch size and add memcpy in TensorRT EP * update test cases * Update tensorrt_execution_provider.cc * update onnx-tensorrt submodule * Update Dockerfile.ubuntu_tensorrt * Update Dockerfile.ubuntu_tensorrt * Update run_dockerbuild.sh * Update run_dockerbuild.sh * Update install_ubuntu.sh * Update concat_op_test.cc * Update tensorrt_execution_provider.cc * Upgrade TensorRT to version 6.0.1.5 * Update onnxruntime_providers.cmake * Update CMakeLists.txt * Update reduction_ops_test.cc * Update install_ubuntu.sh * Update Dockerfile.ubuntu_tensorrt * Update Dockerfile.tensorrt * Update BUILD.md * Update run_dockerbuild.sh * Update install_ubuntu.sh * Update onnxruntime_providers.cmake * Update install_ubuntu.sh * Update install_ubuntu.sh * Update gemm_test.cc * Update gather_op_test.cc * Update CMakeLists.txt * Removed submodule * update onnx-tensorrt submodule * Add Ubuntu18.04 build option * Add Ubuntu18.04 build option * Add Ubuntu18.04 build option * Add Ubuntu18.04 build option * Remove redundency * Fix issue that it does not add memcopy node correctly if some nodes fall back to CUDA EP. e.g. after partition, there's TRT_Node -> Cuda_node (with CPU memory expected), we still need to add memcpy node between them. * update for Trt Windows build * Update onnxruntime_providers.cmake * Disable opset11 tests on TensorRT * Update pad_test.cc * Update build.py * update scripts for ubuntu18.04 * Disable warning for Windows build
31 lines
1.3 KiB
Text
31 lines
1.3 KiB
Text
# Tag: nvcr.io/nvidia/tensorrt:19.09-py3
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# Label: com.nvidia.cuda.version: 10.1.243
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# Label: com.nvidia.cudnn.version: 7.6.3
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# Ubuntu 18.04
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FROM nvcr.io/nvidia/tensorrt:19.09-py3
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ARG PYTHON_VERSION=3.6
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ARG OS_VERSION=18.04
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ADD scripts /tmp/scripts
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RUN /tmp/scripts/install_ubuntu.sh -p $PYTHON_VERSION -o ${OS_VERSION} && /tmp/scripts/install_deps.sh -p $PYTHON_VERSION && rm -rf /tmp/scripts \
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&& rm /usr/local/bin/cmake && rm /usr/local/bin/ctest && rm -r /usr/local/share/cmake-3.12
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WORKDIR /root
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# Allow configure to pick up GDK and CuDNN where it expects it.
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# (Note: $CUDNN_VERSION is defined by NVidia's base image)
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RUN _CUDNN_VERSION=$(echo $CUDNN_VERSION | cut -d. -f1-2) && \
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mkdir -p /usr/local/cudnn-$_CUDNN_VERSION/cuda/include && \
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ln -s /usr/include/cudnn.h /usr/local/cudnn-$_CUDNN_VERSION/cuda/include/cudnn.h && \
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mkdir -p /usr/local/cudnn-$_CUDNN_VERSION/cuda/lib64 && \
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ln -s /etc/alternatives/libcudnn_so /usr/local/cudnn-$_CUDNN_VERSION/cuda/lib64/libcudnn.so && \
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ln -s /usr/local/cudnn{-$_CUDNN_VERSION,}
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ENV LD_LIBRARY_PATH /usr/local/openblas/lib:$LD_LIBRARY_PATH
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ARG BUILD_USER=onnxruntimedev
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ARG BUILD_UID=1000
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WORKDIR /home/$BUILD_USER
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RUN adduser --gecos 'onnxruntime Build User' --disabled-password $BUILD_USER --uid $BUILD_UID
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USER $BUILD_USER
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