mirror of
https://github.com/saymrwulf/onnxruntime.git
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* add HSA_NO_SCRATCH_RECLAIM=1 to dockerfile It is to work around an issue in AMD compiler which generates poor GPU ISA when the type of kernel parameter is a structure and “pass-by-value” is used * update BUILD.md * add dockerfile for rocm3.10
207 lines
7.8 KiB
Groff
207 lines
7.8 KiB
Groff
# docker build --network=host --file Dockerfile.rocm3.9 --tag ort:rocm3.9-ort-dev .
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FROM rocm/tensorflow:rocm3.9-tf2.3-dev
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RUN wget -q -O - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add -
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RUN echo 'deb [arch=amd64] http://repo.radeon.com/rocm/apt/3.9/ xenial main' | tee /etc/apt/sources.list.d/rocm.list
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RUN apt-get -y update
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RUN apt-get -y install apt-utils
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RUN apt-get -y install build-essential autotools-dev \
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make git curl vim wget rsync jq openssh-server openssh-client sudo \
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iputils-ping net-tools ethtool libcap2 \
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automake autoconf libtool flex doxygen \
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perl lsb-release iproute2 pciutils graphviz \
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bc tar git bash pbzip2 pv bzip2 cabextract \
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g++ gcc \
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&& apt-get autoremove
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# sh
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RUN rm /bin/sh && ln -s /bin/bash /bin/sh
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# Labels for the docker
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LABEL description="This docker sets up the environment to run ORT Training with AMD GPU"
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# CMake
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ENV CMAKE_VERSION=3.18.2
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RUN cd /usr/local && \
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wget -q -O - https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}-Linux-x86_64.tar.gz | tar zxf -
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ENV PATH=/usr/local/cmake-${CMAKE_VERSION}-Linux-x86_64/bin:${PATH}
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# WORKSPACE_DIR
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ENV WORKSPACE_DIR=/workspace
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RUN mkdir -p $WORKSPACE_DIR
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WORKDIR $WORKSPACE_DIR
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# Infiniband setup, openmpi installed under /usr/mpi/gcc/openmpi-4.0.4rc3 doesn't support multi-thread
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ENV MOFED_VERSION=5.1-0.6.6.0
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ENV MOFED_OS=ubuntu18.04
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ENV MOFED_FILENAME=MLNX_OFED_LINUX-${MOFED_VERSION}-${MOFED_OS}-x86_64
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RUN curl -fSsL https://www.mellanox.com/downloads/ofed/MLNX_OFED-${MOFED_VERSION}/${MOFED_FILENAME}.tgz | tar -zxpf -
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RUN cd MLNX_OFED_LINUX-${MOFED_VERSION}-${MOFED_OS}-x86_64 && \
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./mlnxofedinstall --force --user-space-only --without-fw-update --hpc && \
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cd .. && \
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rm -r MLNX_OFED_LINUX-${MOFED_VERSION}-${MOFED_OS}-x86_64
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# install miniconda (comes with python 3.9 default)
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ARG CONDA_VERSION=4.7.10
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ARG CONDA_URL=https://repo.anaconda.com/miniconda/Miniconda3-${CONDA_VERSION}-Linux-x86_64.sh
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RUN curl -fSsL --insecure ${CONDA_URL} -o install-conda.sh &&\
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/bin/bash ./install-conda.sh -b -p /opt/conda &&\
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/opt/conda/bin/conda clean -ya
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ENV PATH=/opt/conda/bin:${PATH}
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ARG NUMPY_VERSION=1.18.5
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ARG ONNX_VERSION=1.7.0
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RUN conda install -y \
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numpy=${NUMPY_VERSION} \
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cmake \
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ninja \
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pyyaml \
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cffi \
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setuptools \
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&& pip install --no-cache-dir wheel tqdm boto3 requests six ipdb h5py html2text nltk progressbar \
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git+https://github.com/NVIDIA/dllogger \
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onnx=="${ONNX_VERSION}"
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# GITHUB_DIR
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ENV GITHUB_DIR=$WORKSPACE_DIR/github
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RUN mkdir -p $GITHUB_DIR
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# UCX
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WORKDIR $GITHUB_DIR
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RUN apt-get -y update && apt-get -y --no-install-recommends install libnuma-dev
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ARG UCX_VERSION=1.9.0-rc3
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ENV UCX_DIR=$WORKSPACE_DIR/ucx-$UCX_VERSION
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RUN git clone https://github.com/openucx/ucx.git \
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&& cd ucx \
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&& git checkout v$UCX_VERSION \
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&& ./autogen.sh \
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&& mkdir build \
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&& cd build \
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&& ../contrib/configure-opt --prefix=$UCX_DIR --without-rocm --without-knem --without-cuda \
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&& make -j"$(nproc)" \
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&& make install
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# OpenMPI
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# note: require --enable-orterun-prefix-by-default for Azure machine learning compute
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# note: disable verbs as we use ucx middleware and don't want btl openib warnings
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WORKDIR $GITHUB_DIR
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ARG OPENMPI_BASEVERSION=4.0
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ARG OPENMPI_VERSION=${OPENMPI_BASEVERSION}.5
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ENV OPENMPI_DIR=$WORKSPACE_DIR/openmpi-${OPENMPI_VERSION}
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RUN git clone --recursive https://github.com/open-mpi/ompi.git \
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&& cd ompi \
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&& git checkout v$OPENMPI_VERSION \
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&& ./autogen.pl \
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&& mkdir build \
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&& cd build \
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&& ../configure --prefix=$OPENMPI_DIR --with-ucx=$UCX_DIR --without-verbs \
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--enable-mpirun-prefix-by-default --enable-orterun-prefix-by-default \
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--enable-mca-no-build=btl-uct --disable-mpi-fortran \
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&& make -j"$(nproc)" \
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&& make install \
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&& ldconfig \
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&& test -f ${OPENMPI_DIR}/bin/mpic++
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ENV PATH=$OPENMPI_DIR/bin:${PATH}
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ENV LD_LIBRARY_PATH=$OPENMPI_DIR/lib:${LD_LIBRARY_PATH}
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# Create a wrapper for OpenMPI to allow running as root by default
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RUN mv $OPENMPI_DIR/bin/mpirun $OPENMPI_DIR/bin/mpirun.real && \
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echo '#!/bin/bash' > $OPENMPI_DIR/bin/mpirun && \
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echo 'mpirun.real --allow-run-as-root "$@"' >> $OPENMPI_DIR/bin/mpirun && \
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chmod a+x $OPENMPI_DIR/bin/mpirun
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# install mpi4py (be sure to link existing /opt/openmpi-xxx)
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RUN CC=mpicc MPICC=mpicc pip install mpi4py --no-binary mpi4py
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ARG CACHE_DATA=2020-12-06
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# ONNX Runtime
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WORKDIR $GITHUB_DIR
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ENV ORT_DIR=$GITHUB_DIR/onnxruntime
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RUN git clone --recursive https://github.com/microsoft/onnxruntime.git \
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&& cd onnxruntime \
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&& python3 tools/ci_build/build.py \
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--cmake_extra_defines ONNXRUNTIME_VERSION=`cat ./VERSION_NUMBER` \
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--build_dir build \
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--config RelWithDebInfo \
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--parallel \
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--skip_tests \
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--build_wheel \
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--use_rocm --rocm_home /opt/rocm \
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--mpi_home $OPENMPI_DIR \
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--nccl_home /opt/rocm \
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--enable_training \
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&& test -f $ORT_DIR/build/RelWithDebInfo/onnxruntime_training_bert \
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&& pip install $ORT_DIR/build/RelWithDebInfo/dist/*.whl \
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&& ldconfig
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# Instructions to pull and install the nightly ROCm3.8 PyTorch whl pacakge
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RUN pip3 install --pre torch -f https://download.pytorch.org/whl/nightly/rocm3.9/torch_nightly.html
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# ONNX Runtime Training Examples
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WORKDIR $GITHUB_DIR
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ARG GPT2_DATASET=wikitext-103
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RUN git clone -b wezhan/amdgpu https://github.com/microsoft/onnxruntime-training-examples.git \
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&& cd onnxruntime-training-examples \
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# Nvidia BERT
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&& git clone --no-checkout https://github.com/NVIDIA/DeepLearningExamples.git \
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&& cd DeepLearningExamples \
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&& git checkout cf54b787 \
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&& cd .. \
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&& mv DeepLearningExamples/PyTorch/LanguageModeling/BERT ${WORKSPACE_DIR} \
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&& rm -rf DeepLearningExamples \
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&& cp -r ./nvidia-bert/ort_addon/* ${WORKSPACE_DIR}/BERT \
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# GPT2 fine-tuning
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&& cd huggingface-gpt2 \
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&& git clone https://github.com/huggingface/transformers.git \
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&& cd transformers \
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&& git checkout 9a0a8c1c6f4f2f0c80ff07d36713a3ada785eec5 \
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&& cd .. \
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&& mkdir -p ${WORKSPACE_DIR}/GPT2 \
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&& cp -r transformers ${WORKSPACE_DIR}/GPT2 \
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&& cd ${WORKSPACE_DIR}/GPT2/transformers \
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&& git apply $GITHUB_DIR/onnxruntime-training-examples/huggingface-gpt2/ort_addon/src_changes.patch \
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&& cp -r $GITHUB_DIR/onnxruntime-training-examples/huggingface-gpt2/ort_addon/ort_supplement/* ./ \
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&& python3 -m pip install --no-cache-dir -e . \
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&& python3 -m pip install --no-cache-dir -r examples/requirements.txt \
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&& python3 -m pip install cerberus sympy packaging \
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&& cd .. \
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&& wget https://s3.amazonaws.com/research.metamind.io/wikitext/${GPT2_DATASET}-v1.zip \
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&& unzip ${GPT2_DATASET}-v1.zip
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ENV BERT_DIR=${WORKSPACE_DIR}/BERT
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ENV GPT2_DIR=${WORKSPACE_DIR}/GPT2
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ENV TRAIN_FILE=${WORKSPACE_DIR}/GPT2/${GPT2_DATASET}/wiki.train.tokens
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ENV TEST_FILE=${WORKSPACE_DIR}/GPT2/${GPT2_DATASET}/wiki.test.tokens
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# Enable ssh access without password needed
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RUN sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/g' /etc/ssh/sshd_config
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RUN sed -i 's/#StrictModes yes/StrictModes no/g' /etc/ssh/sshd_config
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RUN sed -i 's/#PubkeyAuthentication yes/PubkeyAuthentication yes/g' /etc/ssh/sshd_config
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RUN sed -i 's/#PermitEmptyPasswords no/PermitEmptyPasswords yes/g' /etc/ssh/sshd_config
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# Start or Restart sshd service
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ENTRYPOINT service ssh restart && /bin/bash
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# Add model and scripts
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ADD model ${WORKSPACE_DIR}/model
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ADD script ${WORKSPACE_DIR}/script
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RUN chmod a+x ${WORKSPACE_DIR}/script/run_bert.sh
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# add locale en_US.UTF-8
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RUN apt-get install -y locales
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RUN locale-gen en_US.UTF-8
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# Workaround an issue in AMD compiler which generates poor GPU ISA
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# when the type of kernel parameter is a structure and “pass-by-value” is used
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ENV HSA_NO_SCRATCH_RECLAIM=1
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# Distributed training related environment variables
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ENV HSA_FORCE_FINE_GRAIN_PCIE=1
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ENV NCCL_DEBUG=INFO
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# ENV NCCL_DEBUG_SUBSYS=INIT,COLL
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WORKDIR ${WORKSPACE_DIR}/script
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