300 lines
14 KiB
Docker
300 lines
14 KiB
Docker
ARG UBUNTU_VERSION=18.04
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FROM ubuntu:${UBUNTU_VERSION}
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# Arguments for the build. UBUNTU_VERSION needs to be repeated because
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# the first usage only applies to the FROM tag.
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ARG UBUNTU_VERSION=18.04
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ARG MPI_KIND=OpenMPI
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ARG PYTHON_VERSION=3.6
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ARG GPP_VERSION=7
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# NOTE: keep versions in sync with setup.py extras_require{'dev'}:
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ARG TENSORFLOW_PACKAGE=tensorflow-cpu==1.15.0
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ARG KERAS_PACKAGE=keras==2.2.4
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ARG PYTORCH_PACKAGE=torch==1.2.0+cpu
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ARG PYTORCH_LIGHTNING_PACKAGE=pytorch_lightning==0.7.6
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ARG TORCHVISION_PACKAGE=torchvision==0.4.0+cpu
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ARG MXNET_PACKAGE=mxnet==1.5.0
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ARG PYSPARK_PACKAGE=pyspark==2.4.7
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# if SPARK_PACKAGE is set, installs Spark into /spark from the tgz archive
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# if SPARK_PACKAGE is a preview version, installs PySpark from the tgz archive
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# see https://archive.apache.org/dist/spark/ for available packages, version must match PYSPARK_PACKAGE
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ARG SPARK_PACKAGE=spark-2.4.7/spark-2.4.7-bin-hadoop2.7.tgz
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ARG CCL_PACKAGE=master
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ARG HOROVOD_BUILD_FLAGS=""
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# Set default shell to /bin/bash
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SHELL ["/bin/bash", "-cu"]
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# Prepare to install specific g++ versions
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RUN apt-get update -qq && apt-get install -y --no-install-recommends software-properties-common
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RUN add-apt-repository ppa:ubuntu-toolchain-r/test
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# Install essential packages.
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RUN apt-get update -qq && apt-get install -y --no-install-recommends \
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wget \
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ca-certificates \
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cmake \
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openssh-client \
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openssh-server \
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git \
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build-essential \
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g++-${GPP_VERSION} \
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moreutils
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# Make sure we don't get notifications we can't answer during building.
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env DEBIAN_FRONTEND noninteractive
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# Prepare scripts and configs
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add ./scripts/start /start
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# Download and install everything from the repos.
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run apt-get -q -y update; apt-get -q -y upgrade && \
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apt-get -q -y install sudo openssh-server && \
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mkdir /var/run/sshd
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# Set root password
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run echo 'root:password' >> /root/passwdfile
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# Create user and it's password
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run useradd -m -G sudo master && \
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echo 'master:password' >> /root/passwdfile
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# Apply root password
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run chpasswd -c SHA512 < /root/passwdfile && \
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rm /root/passwdfile
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# Port 22 is used for ssh
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expose 22
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# Assign /data as static volume.
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volume ["/data"]
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# Install Python.
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RUN apt-get update -qq && apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-distutils
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RUN ln -s -f /usr/bin/python${PYTHON_VERSION} /usr/bin/python
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RUN ln -s -f /usr/bin/python${PYTHON_VERSION} /usr/bin/python${PYTHON_VERSION/%.*/}
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RUN wget --progress=dot:mega https://bootstrap.pypa.io/get-pip.py && python get-pip.py && rm get-pip.py
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RUN pip install --no-cache-dir -U --force pip setuptools requests pytest mock pytest-forked parameterized
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# Add launch helper scripts
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RUN echo "env SPARK_HOME=/spark SPARK_DRIVER_MEM=512m PYSPARK_PYTHON=/usr/bin/python${PYTHON_VERSION} PYSPARK_DRIVER_PYTHON=/usr/bin/python${PYTHON_VERSION} \"\$@\"" > /spark_env.sh
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RUN echo /spark_env.sh pytest -v --capture=no --continue-on-collection-errors --junit-xml=/artifacts/junit.\$1.\${HOROVOD_RANK:-\${OMPI_COMM_WORLD_RANK:-\${PMI_RANK}}}.\$2.xml \${@:2} > /pytest.sh
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RUN echo /spark_env.sh pytest -v --capture=no --continue-on-collection-errors --junit-xml=/artifacts/junit.\$1.standalone.\$2.xml \${@:2} > /pytest_standalone.sh
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RUN chmod a+x /spark_env.sh
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RUN chmod a+x /pytest.sh
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RUN chmod a+x /pytest_standalone.sh
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# Install Spark stand-alone cluster.
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RUN if [[ -n ${SPARK_PACKAGE} ]]; then \
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wget --progress=dot:giga "https://www.apache.org/dyn/closer.lua/spark/${SPARK_PACKAGE}?action=download" -O - | tar -xzC /tmp; \
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archive=$(basename "${SPARK_PACKAGE}") bash -c "mv -v /tmp/\${archive/%.tgz/} /spark"; \
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fi
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# Install PySpark.
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RUN apt-get update -qq && apt install -y openjdk-8-jdk-headless
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RUN if [[ ${SPARK_PACKAGE} != *"-preview"* ]]; then \
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pip install --no-cache-dir ${PYSPARK_PACKAGE}; \
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else \
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apt-get update -qq && apt-get install pandoc; \
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pip install --no-cache-dir pypandoc; \
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(cd /spark/python && python setup.py sdist && pip install --no-cache-dir dist/pyspark-*.tar.gz && rm dist/pyspark-*); \
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fi
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# Install Ray.
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RUN pip install --no-cache-dir ray==1.3.0
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# Install MPI.
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RUN if [[ ${MPI_KIND} == "OpenMPI" ]]; then \
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wget --progress=dot:mega -O /tmp/openmpi-3.0.0-bin.tar.gz https://github.com/horovod/horovod/files/1596799/openmpi-3.0.0-bin.tar.gz && \
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cd /usr/local && tar -zxf /tmp/openmpi-3.0.0-bin.tar.gz && ldconfig && \
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echo "mpirun -allow-run-as-root -np 2 -H localhost:2 -bind-to none -map-by slot -mca mpi_abort_print_stack 1" > /mpirun_command; \
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elif [[ ${MPI_KIND} == "ONECCL" ]]; then \
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wget --progress=dot:mega -O /tmp/oneccl.tar.gz https://github.com/oneapi-src/oneCCL/archive/${CCL_PACKAGE}.tar.gz && \
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cd /tmp && tar -zxf oneccl.tar.gz && \
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mkdir oneCCL-${CCL_PACKAGE}/build && cd oneCCL-${CCL_PACKAGE}/build && cmake .. -DCMAKE_INSTALL_PREFIX=/usr/local/oneccl -DCMAKE_BUILD_TYPE=Release && make -j install && \
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cp /tmp/oneCCL-${CCL_PACKAGE}/mpi/include/*.h /usr/local/oneccl/include && \
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cp /tmp/oneCCL-${CCL_PACKAGE}/mpi/bin/mpicc /usr/local/oneccl/bin && \
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chmod +x /usr/local/oneccl/bin/mpicc && \
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cp /tmp/oneCCL-${CCL_PACKAGE}/mpi/bin/mpicxx /usr/local/oneccl/bin && \
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chmod +x /usr/local/oneccl/bin/mpicxx && \
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cp /tmp/oneCCL-${CCL_PACKAGE}/mpi/bin/mpigcc /usr/local/oneccl/bin && \
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chmod +x /usr/local/oneccl/bin/mpigcc && \
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cp /tmp/oneCCL-${CCL_PACKAGE}/mpi/bin/mpigxx /usr/local/oneccl/bin && \
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chmod +x /usr/local/oneccl/bin/mpigxx && \
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cp /tmp/oneCCL-${CCL_PACKAGE}/mpi/lib/libmpicxx.so /usr/local/oneccl/lib && \
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chmod +x /usr/local/oneccl/lib/libmpicxx.so && \
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cp /tmp/oneCCL-${CCL_PACKAGE}/mpi/lib/libmpifort.so /usr/local/oneccl/lib && \
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chmod +x /usr/local/oneccl/lib/libmpifort.so && \
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sed -i 's/if \[ -z \"\${I_MPI_ROOT}\" \]/if [ -z \"${I_MPI_ROOT:-}\" ]/g' /usr/local/oneccl/env/setvars.sh && \
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sed -i 's/ \$1/ \${1:-}/g' /usr/local/oneccl/env/setvars.sh && \
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echo ". /usr/local/oneccl/env/setvars.sh" > /oneccl_env && \
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chmod +x /oneccl_env && \
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echo "export CCL_ATL_TRANSPORT=ofi; \
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export HOROVOD_CCL_CACHE=1; \
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echo \"\$(env)\"; \
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echo \"mpirun is \$(which mpirun)\"; \
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echo \"LD_LIBRARY_PATH is \$(echo \$LD_LIBRARY_PATH)\"; \
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echo \"oneCCL links with \$(ldd /usr/local/oneccl/lib/libccl.so)\"; \
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mpirun -np 2 -hosts localhost \$@" > /mpirun_command_ofi && \
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chmod +x /mpirun_command_ofi && \
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cp /mpirun_command_ofi /mpirun_command_mpi && \
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sed -i 's/export CCL_ATL_TRANSPORT=ofi;/export CCL_ATL_TRANSPORT=mpi;/g' /mpirun_command_mpi && \
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sed -i 's/export HOROVOD_CCL_CACHE=1;/export HOROVOD_CCL_CACHE=0;/g' /mpirun_command_mpi && \
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echo "/mpirun_command_mpi" > /mpirun_command && \
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echo "-L/usr/local/oneccl/lib -lmpi -I/usr/local/oneccl/include" > /mpicc_oneccl && \
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chmod +x /mpicc_oneccl; \
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elif [[ ${MPI_KIND} == "MPICH" ]]; then \
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apt-get update -qq && apt-get install -y mpich && \
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echo "mpirun -np 2" > /mpirun_command; \
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fi
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# Install mpi4py.
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RUN if [[ ${MPI_KIND} != "None" ]]; then \
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if [[ ${MPI_KIND} == "ONECCL" ]]; then \
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export I_MPI_ROOT=/usr/local/oneccl; \
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export MPICC=/usr/local/oneccl/bin/mpicc; \
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fi; \
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pip install --no-cache-dir mpi4py; \
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fi
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# Install TensorFlow and Keras (releases).
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# Pin h5py only for tensorflow<2.5: https://github.com/h5py/h5py/issues/1732
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# Pin scipy!=1.4.0: https://github.com/scipy/scipy/issues/11237
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RUN if [[ ${TENSORFLOW_PACKAGE} != "tf-nightly" ]]; then \
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pip install --no-cache-dir ${TENSORFLOW_PACKAGE}; \
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if [[ ${KERAS_PACKAGE} != "None" ]]; then \
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if [[ ${TENSORFLOW_PACKAGE} == tensorflow*==1.* ]] || [[ ${TENSORFLOW_PACKAGE} == tensorflow*==2.[01234].* ]]; then \
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h5py="h5py<3"; \
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fi; \
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pip install --no-cache-dir ${KERAS_PACKAGE} ${h5py:-} "scipy!=1.4.0" "pandas<1.1.0"; \
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fi; \
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mkdir -p ~/.keras; \
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python -c "import tensorflow as tf; tf.keras.datasets.mnist.load_data()"; \
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fi
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# Install PyTorch (releases).
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# Pin Pillow<7.0 for torchvision < 0.5.0: https://github.com/pytorch/vision/issues/1718
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RUN if [[ ${PYTORCH_PACKAGE} != "torch-nightly" ]]; then \
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pip install --no-cache-dir ${PYTORCH_PACKAGE} ${TORCHVISION_PACKAGE} -f https://download.pytorch.org/whl/torch_stable.html; \
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if [[ "${TORCHVISION_PACKAGE/%+*/}" == torchvision==0.[1234].* ]]; then \
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pip install --no-cache-dir "Pillow<7.0" --no-deps; \
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fi; \
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fi
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RUN pip install ${PYTORCH_LIGHTNING_PACKAGE}
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# Install MXNet (releases).
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RUN if [[ ${MXNET_PACKAGE} != "mxnet-nightly" ]]; then \
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pip install --no-cache-dir ${MXNET_PACKAGE} ; \
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fi
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# Prefetch Spark MNIST dataset.
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RUN mkdir -p /work
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RUN mkdir -p /data && wget --progress=dot:mega https://horovod-datasets.s3.amazonaws.com/mnist.bz2 -O /data/mnist.bz2
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# Prefetch Spark Rossmann dataset.
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RUN mkdir -p /work
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RUN mkdir -p /data && wget --progress=dot:mega https://horovod-datasets.s3.amazonaws.com/rossmann.tgz -O - | tar -xzC /data
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# Prefetch PyTorch datasets.
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RUN wget --progress=dot:mega https://horovod-datasets.s3.amazonaws.com/pytorch_datasets.tgz -O - | tar -xzC /data
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### END OF CACHE ###
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COPY . /horovod
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# Install nightly packages here so they do not get cached
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# Install TensorFlow and Keras (nightly).
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# Do not pin h5py since tf>=2.5 requires h5py~=3.1
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# Pin scipy!=1.4.0: https://github.com/scipy/scipy/issues/11237
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RUN if [[ ${TENSORFLOW_PACKAGE} == "tf-nightly" ]]; then \
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pip install --no-cache-dir ${TENSORFLOW_PACKAGE}; \
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if [[ ${KERAS_PACKAGE} != "None" ]]; then \
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pip install --no-cache-dir ${KERAS_PACKAGE} "scipy!=1.4.0" "pandas<1.1.0"; \
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fi; \
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mkdir -p ~/.keras; \
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python -c "import tensorflow as tf; tf.keras.datasets.mnist.load_data()"; \
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fi
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# Install PyTorch (nightly).
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# Pin Pillow<7.0 for torchvision < 0.5.0: https://github.com/pytorch/vision/issues/1718
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RUN if [[ ${PYTORCH_PACKAGE} == "torch-nightly" ]]; then \
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pip install --no-cache-dir --pre torch ${TORCHVISION_PACKAGE} -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html; \
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if [[ "${TORCHVISION_PACKAGE/%+*/}" == torchvision==0.[1234].* ]]; then \
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pip install --no-cache-dir "Pillow<7.0" --no-deps; \
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fi; \
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fi
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# Install MXNet (nightly).
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RUN if [[ ${MXNET_PACKAGE} == "mxnet-nightly" ]]; then \
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pip install --no-cache-dir --pre mxnet -f https://dist.mxnet.io/python/all; \
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fi
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# Install Horovod.
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RUN if [[ ${MPI_KIND} == "ONECCL" ]]; then \
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if [ -z "${LD_LIBRARY_PATH:-}" ]; then \
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export LD_LIBRARY_PATH=""; \
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fi; \
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if [ -z "${PYTHONPATH:-}" ]; then \
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export PYTHONPATH=""; \
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fi; \
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. /usr/local/oneccl/env/setvars.sh; \
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export I_MPI_ROOT=/usr/local/oneccl; \
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echo "horovod python setup.py sdist, mpicxx is $(which mpicxx)"; \
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fi; \
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cd /horovod && \
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python setup.py sdist && \
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bash -c "${HOROVOD_BUILD_FLAGS} HOROVOD_WITH_TENSORFLOW=1 HOROVOD_WITH_PYTORCH=1 HOROVOD_WITH_MXNET=1 pip install --no-cache-dir -v $(ls /horovod/dist/horovod-*.tar.gz)[spark,ray]"
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# Hack for compatibility of MNIST example with TensorFlow 1.1.0.
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RUN if [[ ${TENSORFLOW_PACKAGE} == "tensorflow==1.1.0" ]]; then \
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sed -i "s/from tensorflow import keras/from tensorflow.contrib import keras/" /horovod/examples/tensorflow/tensorflow_mnist.py; \
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fi
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# Hack TensorFlow MNIST example to be smaller.
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RUN sed -i "s/last_step=20000/last_step=100/" /horovod/examples/tensorflow/tensorflow_mnist.py
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# Hack TensorFlow Eager MNIST example to be smaller.
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RUN sed -i "s/dataset.take(20000/dataset.take(100/" /horovod/examples/tensorflow/tensorflow_mnist_eager.py
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# Hack TensorFlow 2.0 example to be smaller.
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RUN sed -i "s/dataset.take(10000/dataset.take(100/" /horovod/examples/tensorflow2/tensorflow2_mnist.py
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# Hack Keras MNIST advanced example to be smaller.
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RUN sed -i "s/'--epochs', type=int, default=24,/'--epochs', type=int, default=9,/" /horovod/examples/keras/keras_mnist_advanced.py
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RUN sed -i "s/model.add(Conv2D(32, kernel_size=(3, 3),/model.add(Conv2D(1, kernel_size=(3, 3),/" /horovod/examples/keras/keras_mnist_advanced.py
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RUN sed -i "s/model.add(Conv2D(64, (3, 3), activation='relu'))//" /horovod/examples/keras/keras_mnist_advanced.py
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# Hack TensorFlow 2.0 Keras MNIST advanced example to be smaller.
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RUN sed -i "s/epochs = .*/epochs = 9/" /horovod/examples/tensorflow2/tensorflow2_keras_mnist.py
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RUN sed -i "s/tf.keras.layers.Conv2D(32, \\[3, 3\\],/tf.keras.layers.Conv2D(1, [3, 3],/" /horovod/examples/tensorflow2/tensorflow2_keras_mnist.py
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RUN sed -i "s/tf.keras.layers.Conv2D(64, \\[3, 3\\], activation='relu')),//" /horovod/examples/tensorflow2/tensorflow2_keras_mnist.py
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# Hack PyTorch MNIST example to be smaller.
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RUN sed -i "s/'--epochs', type=int, default=10,/'--epochs', type=int, default=2,/" /horovod/examples/pytorch/pytorch_mnist.py
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RUN sed -i "s/self.fc1 = nn.Linear(320, 50)/self.fc1 = nn.Linear(784, 50)/" /horovod/examples/pytorch/pytorch_mnist.py
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RUN sed -i "s/x = F.relu(F.max_pool2d(self.conv1(x), 2))//" /horovod/examples/pytorch/pytorch_mnist.py
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RUN sed -i "s/x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))//" /horovod/examples/pytorch/pytorch_mnist.py
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RUN sed -i "s/x = x.view(-1, 320)/x = x.view(-1, 784)/" /horovod/examples/pytorch/pytorch_mnist.py
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# Hack Keras Spark Rossmann Run example to be smaller.
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RUN sed -i "s/x = Dense(1000,/x = Dense(100,/g" /horovod/examples/spark/keras/keras_spark_rossmann_run.py
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RUN sed -i "s/x = Dense(500,/x = Dense(50,/g" /horovod/examples/spark/keras/keras_spark_rossmann_run.py
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# Hack Keras Spark Rossmann Estimator example to be smaller.
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RUN sed -i "s/x = Dense(1000,/x = Dense(100,/g" /horovod/examples/spark/keras/keras_spark_rossmann_estimator.py
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RUN sed -i "s/x = Dense(500,/x = Dense(50,/g" /horovod/examples/spark/keras/keras_spark_rossmann_estimator.py
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# Fix all permissions
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run chmod +x /start
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# Starting sshd
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cmd ["/start"]
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