tensorflow 1.11 and cuda 8









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TensorFlow 1.11 fails to build with CUDA 8. I tried opening an issue on github (Issue opened on Github #23256 [https://github.com/tensorflow/tensorflow/issues/23256]) but the tensorflow team's response is to just upgrade CUDA to 9 or downgrade Tensorflow to 1.10, which isn't an option for me. Trying to find a way to get TF1.11 to work with CUDA 8.



Attempting to build a docker container with TF 1.11 and CUDA 8 on an GeForce 1060 3GB GPU. An error keeps occurring in the build. Github Issue 22729 (#22729) was looked at but the work around didn't work for TF 1.11 and that's what is needed. The docker file is also below. Any help you can provide would be greatly appreciated.



System information



OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04
TensorFlow installed from (source or binary): Source



TensorFlow version: TF 1.11



Python version: 2.7



Installed using virtualenv? pip? conda?: Docker



Bazel version (if compiling from source): 0.15.0



GCC/Compiler version (if compiling from source): 7.3.0



CUDA/cuDNN version: 8.0/7



GPU model and memory: GeForce GTX 1060 3GB



Provide the exact sequence of commands / steps that you executed before running into the problem
sudo docker build --no-cache . -f Dockerfile.tf-1.11-py27-gpu.txt -t tf-1.11-py27-gpu



Thank you,
Kyle



Dockerfile.tf-1.11-py27-gpu



FROM nvidia/cuda:8.0-cudnn7-devel-ubuntu16.04

LABEL maintainer="Craig Citro <craigcitro@google.com>; Modified for Cuda 8 by Jack Harris"

RUN apt-get update && apt-get install -y --allow-downgrades --allow-change-held-packages --no-install-recommends
build-essential
cuda-command-line-tools-8-0
cuda-cublas-dev-8-0
cuda-cudart-dev-8-0
cuda-cufft-dev-8-0
cuda-curand-dev-8-0
cuda-cusolver-dev-8-0
cuda-cusparse-dev-8-0
curl
git
libcudnn7=7.2.1.38-1+cuda8.0
libcudnn7-dev=7.2.1.38-1+cuda8.0
libnccl2=2.2.13-1+cuda8.0
libnccl-dev=2.2.13-1+cuda8.0
libcurl3-dev
libfreetype6-dev
libhdf5-serial-dev
libpng12-dev
libzmq3-dev
pkg-config
python-dev
rsync
software-properties-common
unzip
zip
zlib1g-dev
wget
&&
rm -rf /var/lib/apt/lists/* &&
find /usr/local/cuda-8.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete &&
rm -f /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a

RUN apt-get update &&
apt-get install nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda8.0 &&
apt-get update &&
apt-get install libnvinfer4=4.1.2-1+cuda8.0 &&
apt-get install libnvinfer-dev=4.1.2-1+cuda8.0

# Link NCCL libray and header where the build script expects them.
RUN mkdir /usr/local/cuda-8.0/lib &&
ln -s /usr/lib/x86_64-linux-gnu/libnccl.so.2 /usr/local/cuda/lib/libnccl.so.2 &&
ln -s /usr/include/nccl.h /usr/local/cuda/include/nccl.h

# TODO(tobyboyd): Remove after license is excluded from BUILD file.
#RUN gunzip /usr/share/doc/libnccl2/NCCL-SLA.txt.gz &&
# cp /usr/share/doc/libnccl2/NCCL-SLA.txt /usr/local/cuda/

# Add External Mount Points
RUN mkdir -p /external_lib
RUN mkdir -p /external_bin

RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py &&
python get-pip.py &&
rm get-pip.py

RUN pip --no-cache-dir install
ipykernel
jupyter
keras_applications==1.0.5
keras_preprocessing==1.0.3
matplotlib
numpy
pandas
scipy
sklearn
mock
&&
python -m ipykernel.kernelspec

# Set up our notebook config.
#COPY jupyter_notebook_config.py /root/.jupyter/

# Jupyter has issues with being run directly:
# https://github.com/ipython/ipython/issues/7062
# We just add a little wrapper script.
# COPY run_jupyter.sh /

# Set up Bazel.

# Running bazel inside a `docker build` command causes trouble, cf:
# https://github.com/bazelbuild/bazel/issues/134
# The easiest solution is to set up a bazelrc file forcing --batch.
RUN echo "startup --batch" >>/etc/bazel.bazelrc
# Similarly, we need to workaround sandboxing issues:
# https://github.com/bazelbuild/bazel/issues/418
RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone"
>>/etc/bazel.bazelrc
# Install the most recent bazel release.
ENV BAZEL_VERSION 0.15.0
WORKDIR /
RUN mkdir /bazel &&
cd /bazel &&
curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh &&
curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE &&
chmod +x bazel-*.sh &&
./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh &&
cd / &&
rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh

# Download and build TensorFlow.
RUN git clone http://github.com/tensorflow/tensorflow --branch r1.11 --depth=1

WORKDIR /tensorflow

RUN sed -i 's/^#if TF_HAS_.*$/#if !defined(__NVCC__)/g' tensorflow/core/platform/macros.h

ENV TF_NCCL_VERSION=2

#RUN /bin/echo -e "/usr/bin/pythonnnnnnnnnnnnnnnnnnnnnyn8.0n/usr/local/cudan7.0n/usr/local/cudannnnnnnnn-march=nativennn" | ./configure
RUN /bin/echo -e "/usr/bin/pythonnnnnnnnnnnnnnnnnnnnnnnyn8.0n/usr/local/cudan7.0n/usr/local/cudannnnnnnnnnnnn-march=nativennn" | ./configure
#RUN /bin/echo -e "nnnnnnnnnnnnnnnnnnnnnnn-march=nativennn" | ./configure

# Configure the build for our CUDA configuration.
ENV CI_BUILD_PYTHON python
ENV PATH /external_bin:$PATH
ENV LD_LIBRARY_PATH /external_lib:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
ENV TF_NEED_CUDA 1
ENV TF_NEED_TENSORRT 1
ENV TF_CUDA_COMPUTE_CAPABILITIES=3.0,3.5,5.2,6.0,6.1
ENV TF_CUDA_VERSION=8.0
ENV TF_CUDNN_VERSION=7

# https://github.com/tensorflow/tensorflow/issues/17801
RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 &&
ln -s /usr/local/cuda/nvvm/libdevice/libdevice.compute_50.10.bc /usr/local/cuda/nvvm/libdevice/libdevice.10.bc &&
LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs:$LD_LIBRARY_PATH
tensorflow/tools/ci_build/builds/configured GPU
bazel build -c opt --copt=-mavx --config=cuda
--cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"
tensorflow/tools/pip_package/build_pip_package &&
rm /usr/local/cuda/lib64/stubs/libcuda.so.1

RUN bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/pip

RUN pip --no-cache-dir install --upgrade /tmp/pip/tensorflow-*.whl &&
rm -rf /tmp/pip &&
rm -rf /root/.cache
# Clean up pip wheel and Bazel cache when done.

WORKDIR /root

# TensorBoard
EXPOSE 6006
# IPython
EXPOSE 8888

CMD [ "/bin/bash" ]


tf11cuda8.log - Log attached to github issue (too long to post here)










share|improve this question



























    up vote
    1
    down vote

    favorite












    TensorFlow 1.11 fails to build with CUDA 8. I tried opening an issue on github (Issue opened on Github #23256 [https://github.com/tensorflow/tensorflow/issues/23256]) but the tensorflow team's response is to just upgrade CUDA to 9 or downgrade Tensorflow to 1.10, which isn't an option for me. Trying to find a way to get TF1.11 to work with CUDA 8.



    Attempting to build a docker container with TF 1.11 and CUDA 8 on an GeForce 1060 3GB GPU. An error keeps occurring in the build. Github Issue 22729 (#22729) was looked at but the work around didn't work for TF 1.11 and that's what is needed. The docker file is also below. Any help you can provide would be greatly appreciated.



    System information



    OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04
    TensorFlow installed from (source or binary): Source



    TensorFlow version: TF 1.11



    Python version: 2.7



    Installed using virtualenv? pip? conda?: Docker



    Bazel version (if compiling from source): 0.15.0



    GCC/Compiler version (if compiling from source): 7.3.0



    CUDA/cuDNN version: 8.0/7



    GPU model and memory: GeForce GTX 1060 3GB



    Provide the exact sequence of commands / steps that you executed before running into the problem
    sudo docker build --no-cache . -f Dockerfile.tf-1.11-py27-gpu.txt -t tf-1.11-py27-gpu



    Thank you,
    Kyle



    Dockerfile.tf-1.11-py27-gpu



    FROM nvidia/cuda:8.0-cudnn7-devel-ubuntu16.04

    LABEL maintainer="Craig Citro <craigcitro@google.com>; Modified for Cuda 8 by Jack Harris"

    RUN apt-get update && apt-get install -y --allow-downgrades --allow-change-held-packages --no-install-recommends
    build-essential
    cuda-command-line-tools-8-0
    cuda-cublas-dev-8-0
    cuda-cudart-dev-8-0
    cuda-cufft-dev-8-0
    cuda-curand-dev-8-0
    cuda-cusolver-dev-8-0
    cuda-cusparse-dev-8-0
    curl
    git
    libcudnn7=7.2.1.38-1+cuda8.0
    libcudnn7-dev=7.2.1.38-1+cuda8.0
    libnccl2=2.2.13-1+cuda8.0
    libnccl-dev=2.2.13-1+cuda8.0
    libcurl3-dev
    libfreetype6-dev
    libhdf5-serial-dev
    libpng12-dev
    libzmq3-dev
    pkg-config
    python-dev
    rsync
    software-properties-common
    unzip
    zip
    zlib1g-dev
    wget
    &&
    rm -rf /var/lib/apt/lists/* &&
    find /usr/local/cuda-8.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete &&
    rm -f /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a

    RUN apt-get update &&
    apt-get install nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda8.0 &&
    apt-get update &&
    apt-get install libnvinfer4=4.1.2-1+cuda8.0 &&
    apt-get install libnvinfer-dev=4.1.2-1+cuda8.0

    # Link NCCL libray and header where the build script expects them.
    RUN mkdir /usr/local/cuda-8.0/lib &&
    ln -s /usr/lib/x86_64-linux-gnu/libnccl.so.2 /usr/local/cuda/lib/libnccl.so.2 &&
    ln -s /usr/include/nccl.h /usr/local/cuda/include/nccl.h

    # TODO(tobyboyd): Remove after license is excluded from BUILD file.
    #RUN gunzip /usr/share/doc/libnccl2/NCCL-SLA.txt.gz &&
    # cp /usr/share/doc/libnccl2/NCCL-SLA.txt /usr/local/cuda/

    # Add External Mount Points
    RUN mkdir -p /external_lib
    RUN mkdir -p /external_bin

    RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py &&
    python get-pip.py &&
    rm get-pip.py

    RUN pip --no-cache-dir install
    ipykernel
    jupyter
    keras_applications==1.0.5
    keras_preprocessing==1.0.3
    matplotlib
    numpy
    pandas
    scipy
    sklearn
    mock
    &&
    python -m ipykernel.kernelspec

    # Set up our notebook config.
    #COPY jupyter_notebook_config.py /root/.jupyter/

    # Jupyter has issues with being run directly:
    # https://github.com/ipython/ipython/issues/7062
    # We just add a little wrapper script.
    # COPY run_jupyter.sh /

    # Set up Bazel.

    # Running bazel inside a `docker build` command causes trouble, cf:
    # https://github.com/bazelbuild/bazel/issues/134
    # The easiest solution is to set up a bazelrc file forcing --batch.
    RUN echo "startup --batch" >>/etc/bazel.bazelrc
    # Similarly, we need to workaround sandboxing issues:
    # https://github.com/bazelbuild/bazel/issues/418
    RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone"
    >>/etc/bazel.bazelrc
    # Install the most recent bazel release.
    ENV BAZEL_VERSION 0.15.0
    WORKDIR /
    RUN mkdir /bazel &&
    cd /bazel &&
    curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh &&
    curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE &&
    chmod +x bazel-*.sh &&
    ./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh &&
    cd / &&
    rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh

    # Download and build TensorFlow.
    RUN git clone http://github.com/tensorflow/tensorflow --branch r1.11 --depth=1

    WORKDIR /tensorflow

    RUN sed -i 's/^#if TF_HAS_.*$/#if !defined(__NVCC__)/g' tensorflow/core/platform/macros.h

    ENV TF_NCCL_VERSION=2

    #RUN /bin/echo -e "/usr/bin/pythonnnnnnnnnnnnnnnnnnnnnyn8.0n/usr/local/cudan7.0n/usr/local/cudannnnnnnnn-march=nativennn" | ./configure
    RUN /bin/echo -e "/usr/bin/pythonnnnnnnnnnnnnnnnnnnnnnnyn8.0n/usr/local/cudan7.0n/usr/local/cudannnnnnnnnnnnn-march=nativennn" | ./configure
    #RUN /bin/echo -e "nnnnnnnnnnnnnnnnnnnnnnn-march=nativennn" | ./configure

    # Configure the build for our CUDA configuration.
    ENV CI_BUILD_PYTHON python
    ENV PATH /external_bin:$PATH
    ENV LD_LIBRARY_PATH /external_lib:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
    ENV TF_NEED_CUDA 1
    ENV TF_NEED_TENSORRT 1
    ENV TF_CUDA_COMPUTE_CAPABILITIES=3.0,3.5,5.2,6.0,6.1
    ENV TF_CUDA_VERSION=8.0
    ENV TF_CUDNN_VERSION=7

    # https://github.com/tensorflow/tensorflow/issues/17801
    RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 &&
    ln -s /usr/local/cuda/nvvm/libdevice/libdevice.compute_50.10.bc /usr/local/cuda/nvvm/libdevice/libdevice.10.bc &&
    LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs:$LD_LIBRARY_PATH
    tensorflow/tools/ci_build/builds/configured GPU
    bazel build -c opt --copt=-mavx --config=cuda
    --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"
    tensorflow/tools/pip_package/build_pip_package &&
    rm /usr/local/cuda/lib64/stubs/libcuda.so.1

    RUN bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/pip

    RUN pip --no-cache-dir install --upgrade /tmp/pip/tensorflow-*.whl &&
    rm -rf /tmp/pip &&
    rm -rf /root/.cache
    # Clean up pip wheel and Bazel cache when done.

    WORKDIR /root

    # TensorBoard
    EXPOSE 6006
    # IPython
    EXPOSE 8888

    CMD [ "/bin/bash" ]


    tf11cuda8.log - Log attached to github issue (too long to post here)










    share|improve this question

























      up vote
      1
      down vote

      favorite









      up vote
      1
      down vote

      favorite











      TensorFlow 1.11 fails to build with CUDA 8. I tried opening an issue on github (Issue opened on Github #23256 [https://github.com/tensorflow/tensorflow/issues/23256]) but the tensorflow team's response is to just upgrade CUDA to 9 or downgrade Tensorflow to 1.10, which isn't an option for me. Trying to find a way to get TF1.11 to work with CUDA 8.



      Attempting to build a docker container with TF 1.11 and CUDA 8 on an GeForce 1060 3GB GPU. An error keeps occurring in the build. Github Issue 22729 (#22729) was looked at but the work around didn't work for TF 1.11 and that's what is needed. The docker file is also below. Any help you can provide would be greatly appreciated.



      System information



      OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04
      TensorFlow installed from (source or binary): Source



      TensorFlow version: TF 1.11



      Python version: 2.7



      Installed using virtualenv? pip? conda?: Docker



      Bazel version (if compiling from source): 0.15.0



      GCC/Compiler version (if compiling from source): 7.3.0



      CUDA/cuDNN version: 8.0/7



      GPU model and memory: GeForce GTX 1060 3GB



      Provide the exact sequence of commands / steps that you executed before running into the problem
      sudo docker build --no-cache . -f Dockerfile.tf-1.11-py27-gpu.txt -t tf-1.11-py27-gpu



      Thank you,
      Kyle



      Dockerfile.tf-1.11-py27-gpu



      FROM nvidia/cuda:8.0-cudnn7-devel-ubuntu16.04

      LABEL maintainer="Craig Citro <craigcitro@google.com>; Modified for Cuda 8 by Jack Harris"

      RUN apt-get update && apt-get install -y --allow-downgrades --allow-change-held-packages --no-install-recommends
      build-essential
      cuda-command-line-tools-8-0
      cuda-cublas-dev-8-0
      cuda-cudart-dev-8-0
      cuda-cufft-dev-8-0
      cuda-curand-dev-8-0
      cuda-cusolver-dev-8-0
      cuda-cusparse-dev-8-0
      curl
      git
      libcudnn7=7.2.1.38-1+cuda8.0
      libcudnn7-dev=7.2.1.38-1+cuda8.0
      libnccl2=2.2.13-1+cuda8.0
      libnccl-dev=2.2.13-1+cuda8.0
      libcurl3-dev
      libfreetype6-dev
      libhdf5-serial-dev
      libpng12-dev
      libzmq3-dev
      pkg-config
      python-dev
      rsync
      software-properties-common
      unzip
      zip
      zlib1g-dev
      wget
      &&
      rm -rf /var/lib/apt/lists/* &&
      find /usr/local/cuda-8.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete &&
      rm -f /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a

      RUN apt-get update &&
      apt-get install nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda8.0 &&
      apt-get update &&
      apt-get install libnvinfer4=4.1.2-1+cuda8.0 &&
      apt-get install libnvinfer-dev=4.1.2-1+cuda8.0

      # Link NCCL libray and header where the build script expects them.
      RUN mkdir /usr/local/cuda-8.0/lib &&
      ln -s /usr/lib/x86_64-linux-gnu/libnccl.so.2 /usr/local/cuda/lib/libnccl.so.2 &&
      ln -s /usr/include/nccl.h /usr/local/cuda/include/nccl.h

      # TODO(tobyboyd): Remove after license is excluded from BUILD file.
      #RUN gunzip /usr/share/doc/libnccl2/NCCL-SLA.txt.gz &&
      # cp /usr/share/doc/libnccl2/NCCL-SLA.txt /usr/local/cuda/

      # Add External Mount Points
      RUN mkdir -p /external_lib
      RUN mkdir -p /external_bin

      RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py &&
      python get-pip.py &&
      rm get-pip.py

      RUN pip --no-cache-dir install
      ipykernel
      jupyter
      keras_applications==1.0.5
      keras_preprocessing==1.0.3
      matplotlib
      numpy
      pandas
      scipy
      sklearn
      mock
      &&
      python -m ipykernel.kernelspec

      # Set up our notebook config.
      #COPY jupyter_notebook_config.py /root/.jupyter/

      # Jupyter has issues with being run directly:
      # https://github.com/ipython/ipython/issues/7062
      # We just add a little wrapper script.
      # COPY run_jupyter.sh /

      # Set up Bazel.

      # Running bazel inside a `docker build` command causes trouble, cf:
      # https://github.com/bazelbuild/bazel/issues/134
      # The easiest solution is to set up a bazelrc file forcing --batch.
      RUN echo "startup --batch" >>/etc/bazel.bazelrc
      # Similarly, we need to workaround sandboxing issues:
      # https://github.com/bazelbuild/bazel/issues/418
      RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone"
      >>/etc/bazel.bazelrc
      # Install the most recent bazel release.
      ENV BAZEL_VERSION 0.15.0
      WORKDIR /
      RUN mkdir /bazel &&
      cd /bazel &&
      curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh &&
      curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE &&
      chmod +x bazel-*.sh &&
      ./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh &&
      cd / &&
      rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh

      # Download and build TensorFlow.
      RUN git clone http://github.com/tensorflow/tensorflow --branch r1.11 --depth=1

      WORKDIR /tensorflow

      RUN sed -i 's/^#if TF_HAS_.*$/#if !defined(__NVCC__)/g' tensorflow/core/platform/macros.h

      ENV TF_NCCL_VERSION=2

      #RUN /bin/echo -e "/usr/bin/pythonnnnnnnnnnnnnnnnnnnnnyn8.0n/usr/local/cudan7.0n/usr/local/cudannnnnnnnn-march=nativennn" | ./configure
      RUN /bin/echo -e "/usr/bin/pythonnnnnnnnnnnnnnnnnnnnnnnyn8.0n/usr/local/cudan7.0n/usr/local/cudannnnnnnnnnnnn-march=nativennn" | ./configure
      #RUN /bin/echo -e "nnnnnnnnnnnnnnnnnnnnnnn-march=nativennn" | ./configure

      # Configure the build for our CUDA configuration.
      ENV CI_BUILD_PYTHON python
      ENV PATH /external_bin:$PATH
      ENV LD_LIBRARY_PATH /external_lib:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
      ENV TF_NEED_CUDA 1
      ENV TF_NEED_TENSORRT 1
      ENV TF_CUDA_COMPUTE_CAPABILITIES=3.0,3.5,5.2,6.0,6.1
      ENV TF_CUDA_VERSION=8.0
      ENV TF_CUDNN_VERSION=7

      # https://github.com/tensorflow/tensorflow/issues/17801
      RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 &&
      ln -s /usr/local/cuda/nvvm/libdevice/libdevice.compute_50.10.bc /usr/local/cuda/nvvm/libdevice/libdevice.10.bc &&
      LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs:$LD_LIBRARY_PATH
      tensorflow/tools/ci_build/builds/configured GPU
      bazel build -c opt --copt=-mavx --config=cuda
      --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"
      tensorflow/tools/pip_package/build_pip_package &&
      rm /usr/local/cuda/lib64/stubs/libcuda.so.1

      RUN bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/pip

      RUN pip --no-cache-dir install --upgrade /tmp/pip/tensorflow-*.whl &&
      rm -rf /tmp/pip &&
      rm -rf /root/.cache
      # Clean up pip wheel and Bazel cache when done.

      WORKDIR /root

      # TensorBoard
      EXPOSE 6006
      # IPython
      EXPOSE 8888

      CMD [ "/bin/bash" ]


      tf11cuda8.log - Log attached to github issue (too long to post here)










      share|improve this question















      TensorFlow 1.11 fails to build with CUDA 8. I tried opening an issue on github (Issue opened on Github #23256 [https://github.com/tensorflow/tensorflow/issues/23256]) but the tensorflow team's response is to just upgrade CUDA to 9 or downgrade Tensorflow to 1.10, which isn't an option for me. Trying to find a way to get TF1.11 to work with CUDA 8.



      Attempting to build a docker container with TF 1.11 and CUDA 8 on an GeForce 1060 3GB GPU. An error keeps occurring in the build. Github Issue 22729 (#22729) was looked at but the work around didn't work for TF 1.11 and that's what is needed. The docker file is also below. Any help you can provide would be greatly appreciated.



      System information



      OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04
      TensorFlow installed from (source or binary): Source



      TensorFlow version: TF 1.11



      Python version: 2.7



      Installed using virtualenv? pip? conda?: Docker



      Bazel version (if compiling from source): 0.15.0



      GCC/Compiler version (if compiling from source): 7.3.0



      CUDA/cuDNN version: 8.0/7



      GPU model and memory: GeForce GTX 1060 3GB



      Provide the exact sequence of commands / steps that you executed before running into the problem
      sudo docker build --no-cache . -f Dockerfile.tf-1.11-py27-gpu.txt -t tf-1.11-py27-gpu



      Thank you,
      Kyle



      Dockerfile.tf-1.11-py27-gpu



      FROM nvidia/cuda:8.0-cudnn7-devel-ubuntu16.04

      LABEL maintainer="Craig Citro <craigcitro@google.com>; Modified for Cuda 8 by Jack Harris"

      RUN apt-get update && apt-get install -y --allow-downgrades --allow-change-held-packages --no-install-recommends
      build-essential
      cuda-command-line-tools-8-0
      cuda-cublas-dev-8-0
      cuda-cudart-dev-8-0
      cuda-cufft-dev-8-0
      cuda-curand-dev-8-0
      cuda-cusolver-dev-8-0
      cuda-cusparse-dev-8-0
      curl
      git
      libcudnn7=7.2.1.38-1+cuda8.0
      libcudnn7-dev=7.2.1.38-1+cuda8.0
      libnccl2=2.2.13-1+cuda8.0
      libnccl-dev=2.2.13-1+cuda8.0
      libcurl3-dev
      libfreetype6-dev
      libhdf5-serial-dev
      libpng12-dev
      libzmq3-dev
      pkg-config
      python-dev
      rsync
      software-properties-common
      unzip
      zip
      zlib1g-dev
      wget
      &&
      rm -rf /var/lib/apt/lists/* &&
      find /usr/local/cuda-8.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete &&
      rm -f /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a

      RUN apt-get update &&
      apt-get install nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda8.0 &&
      apt-get update &&
      apt-get install libnvinfer4=4.1.2-1+cuda8.0 &&
      apt-get install libnvinfer-dev=4.1.2-1+cuda8.0

      # Link NCCL libray and header where the build script expects them.
      RUN mkdir /usr/local/cuda-8.0/lib &&
      ln -s /usr/lib/x86_64-linux-gnu/libnccl.so.2 /usr/local/cuda/lib/libnccl.so.2 &&
      ln -s /usr/include/nccl.h /usr/local/cuda/include/nccl.h

      # TODO(tobyboyd): Remove after license is excluded from BUILD file.
      #RUN gunzip /usr/share/doc/libnccl2/NCCL-SLA.txt.gz &&
      # cp /usr/share/doc/libnccl2/NCCL-SLA.txt /usr/local/cuda/

      # Add External Mount Points
      RUN mkdir -p /external_lib
      RUN mkdir -p /external_bin

      RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py &&
      python get-pip.py &&
      rm get-pip.py

      RUN pip --no-cache-dir install
      ipykernel
      jupyter
      keras_applications==1.0.5
      keras_preprocessing==1.0.3
      matplotlib
      numpy
      pandas
      scipy
      sklearn
      mock
      &&
      python -m ipykernel.kernelspec

      # Set up our notebook config.
      #COPY jupyter_notebook_config.py /root/.jupyter/

      # Jupyter has issues with being run directly:
      # https://github.com/ipython/ipython/issues/7062
      # We just add a little wrapper script.
      # COPY run_jupyter.sh /

      # Set up Bazel.

      # Running bazel inside a `docker build` command causes trouble, cf:
      # https://github.com/bazelbuild/bazel/issues/134
      # The easiest solution is to set up a bazelrc file forcing --batch.
      RUN echo "startup --batch" >>/etc/bazel.bazelrc
      # Similarly, we need to workaround sandboxing issues:
      # https://github.com/bazelbuild/bazel/issues/418
      RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone"
      >>/etc/bazel.bazelrc
      # Install the most recent bazel release.
      ENV BAZEL_VERSION 0.15.0
      WORKDIR /
      RUN mkdir /bazel &&
      cd /bazel &&
      curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh &&
      curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE &&
      chmod +x bazel-*.sh &&
      ./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh &&
      cd / &&
      rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh

      # Download and build TensorFlow.
      RUN git clone http://github.com/tensorflow/tensorflow --branch r1.11 --depth=1

      WORKDIR /tensorflow

      RUN sed -i 's/^#if TF_HAS_.*$/#if !defined(__NVCC__)/g' tensorflow/core/platform/macros.h

      ENV TF_NCCL_VERSION=2

      #RUN /bin/echo -e "/usr/bin/pythonnnnnnnnnnnnnnnnnnnnnyn8.0n/usr/local/cudan7.0n/usr/local/cudannnnnnnnn-march=nativennn" | ./configure
      RUN /bin/echo -e "/usr/bin/pythonnnnnnnnnnnnnnnnnnnnnnnyn8.0n/usr/local/cudan7.0n/usr/local/cudannnnnnnnnnnnn-march=nativennn" | ./configure
      #RUN /bin/echo -e "nnnnnnnnnnnnnnnnnnnnnnn-march=nativennn" | ./configure

      # Configure the build for our CUDA configuration.
      ENV CI_BUILD_PYTHON python
      ENV PATH /external_bin:$PATH
      ENV LD_LIBRARY_PATH /external_lib:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
      ENV TF_NEED_CUDA 1
      ENV TF_NEED_TENSORRT 1
      ENV TF_CUDA_COMPUTE_CAPABILITIES=3.0,3.5,5.2,6.0,6.1
      ENV TF_CUDA_VERSION=8.0
      ENV TF_CUDNN_VERSION=7

      # https://github.com/tensorflow/tensorflow/issues/17801
      RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 &&
      ln -s /usr/local/cuda/nvvm/libdevice/libdevice.compute_50.10.bc /usr/local/cuda/nvvm/libdevice/libdevice.10.bc &&
      LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs:$LD_LIBRARY_PATH
      tensorflow/tools/ci_build/builds/configured GPU
      bazel build -c opt --copt=-mavx --config=cuda
      --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"
      tensorflow/tools/pip_package/build_pip_package &&
      rm /usr/local/cuda/lib64/stubs/libcuda.so.1

      RUN bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/pip

      RUN pip --no-cache-dir install --upgrade /tmp/pip/tensorflow-*.whl &&
      rm -rf /tmp/pip &&
      rm -rf /root/.cache
      # Clean up pip wheel and Bazel cache when done.

      WORKDIR /root

      # TensorBoard
      EXPOSE 6006
      # IPython
      EXPOSE 8888

      CMD [ "/bin/bash" ]


      tf11cuda8.log - Log attached to github issue (too long to post here)







      python-2.7 docker tensorflow






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 10 at 20:05









      talonmies

      58.8k17126192




      58.8k17126192










      asked Nov 10 at 19:14









      healykys

      61




      61



























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