ab81f099bf
Install a recent and well-tested clang release in our manylinux docker image, and provide a example Dockerfile on how to use that image to build TensorFlow with cuda-clang. PiperOrigin-RevId: 276302595 Change-Id: I4513dfe580a808a9e44d58e7a2e021bbb7ca234b
34 lines
1.0 KiB
Docker
34 lines
1.0 KiB
Docker
# Dockerfile to build a manylinux 2010 compliant TensorFlow pip package with
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# cuda-clang.
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#
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# To build, first build the manylinux2010 toolchain docker image and tag it,
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# then build the TensorFlow docker image using the tagged image as base.
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#
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# $ docker build -f Dockerfile.rbe.cuda10.0-cudnn7-ubuntu16.04-manylinux2010 \
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# --tag "local-manylinux-toolchain" .
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# $ docker build -f Dockerfile.cuda-clang .
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FROM local-manylinux-toolchain
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WORKDIR /
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RUN git clone https://github.com/tensorflow/tensorflow
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WORKDIR /tensorflow
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ENV TF_NEED_GCP=1 \
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TF_NEED_HDFS=1 \
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TF_NEED_CUDA=1 \
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TF_CUDA_CLANG=1 \
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PATH=/dt7/usr/bin:$PATH \
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PYTHON_BIN_PATH=/usr/bin/python3.6 \
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CLANG_CUDA_COMPILER_PATH=/clang_${CLANG_VERSION}/bin/clang
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ADD cuda-clang.patch cuda-clang.patch
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RUN patch -p1 < cuda-clang.patch
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RUN yes "" | ./configure
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RUN bazel build --config=opt tensorflow/tools/pip_package:build_pip_package \
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--nodistinct_host_configuration
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RUN ./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tf-wheel
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