mirror of
https://github.com/clearlinux/dockerfiles.git
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DLRS release 1390
Signed-off-by: Daniela Plascencia <daniela.plascencia@linux.intel.com>
This commit is contained in:
Daniela Plascencia
committed by
George T Kramer
George T Kramer
parent
aabf161b9b
commit
8f7119f287
@@ -14,4 +14,4 @@ docker build --no-cache -t clearlinux/stacks-dlrs-mkl .
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* `swupd_args` specifies [swupd update](https://github.com/clearlinux/swupd-client/blob/master/docs/swupd.1.rst#options) flags passed to the update during build.
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>NOTE: An empty `swupd_args` will default to Clear Linux OS latest version. Consider this when building from the Dockerfile, as an OS update will be performed. The docker image in this registry was built and validated using version 28560.
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>NOTE: An empty `swupd_args` will default to Clear Linux OS latest version. Consider this when building from the Dockerfile, as an OS update will be performed. The docker image in this registry was built and validated using version 28680.
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Executable
+20
@@ -0,0 +1,20 @@
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#!/bin/bash
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echo "Sane defaults when using MKL_DNN optimized DLRS stack."
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echo "We recommend you fine tune the exported env variables based on the workload"
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echo "More details can be found at: https://github.com/IntelAI/models/blob/master/docs/general/tensorflow_serving/GeneralBestPractices.md"
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# A good default setting for OMP theads is number of physical cores
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physical_cores=$(lscpu | grep 'Core(s)' | head -1 | awk '{print $4}')
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sockets=$(lscpu | grep 'Socket(s)' | head -1 | awk '{print $2}')
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total_physical_cores=$((physical_cores * sockets))
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export OMP_NUM_THREADS=$total_physical_cores
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# number of threads to use for a TensorFlow session, specifically
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# when used for inference
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export TENSORFLOW_SESSION_PARALLELISM=$((total_physical_cores / 4))
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export KMP_BLOCKTIME=2
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export KMP_AFFINITY=granularity=fine,verbose,compact,1,0
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# if available set intra_op and inter_op threads as well.
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export INTRA_OP_PARALLELISM_THREADS=$total_physical_cores
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export INTER_OP_PARALLELISM_THREADS=$sockets
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@@ -14,4 +14,4 @@ docker build --no-cache -t clearlinux/stacks-dlrs-oss .
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* `swupd_args` specifies [swupd update](https://github.com/clearlinux/swupd-client/blob/master/docs/swupd.1.rst#options) flags passed to the update during build.
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>NOTE: An empty `swupd_args` will default to Clear Linux OS latest version. Consider this when building from the Dockerfile, as an OS update will be performed. The docker image in this registry was built and validated using version 28560.
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>NOTE: An empty `swupd_args` will default to Clear Linux OS latest version. Consider this when building from the Dockerfile, as an OS update will be performed. The docker image in this registry was built and validated using version 28680.
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@@ -4,49 +4,34 @@ LABEL maintainer=otc-swstacks@intel.com
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ARG PYTHON_VERSION=3.7.1
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ARG MINICONDA_VERSION=4.5.12
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ARG HOROVOD_VERSION=0.16.0
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ARG MKL_VERSION=2019.1
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ARG swupd_args
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ENV PATH /opt/conda/bin:$PATH
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# update os and add pkgs
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RUN swupd update $swupd_args && \
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swupd bundle-add which git devpkg-opencv openssh-server sysadmin-basic devpkg-openmpi
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swupd bundle-add which git \
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devpkg-opencv openssh-server \
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sysadmin-basic devpkg-openmpi
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# install miniconda and necessary build packages
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ADD https://repo.continuum.io/miniconda/Miniconda3-$MINICONDA_VERSION-Linux-x86_64.sh /tmp/miniconda.sh
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RUN chmod +x /tmp/miniconda.sh && \
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/tmp/miniconda.sh -b -p /opt/conda && \
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conda install -y python=$PYTHON_VERSION \
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numpy pyyaml scipy ipython mkl=${MKL_VERSION} mkl-include=${MKL_VERSION} cython typing && \
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conda install -y gcc libgcc -c conda-forge
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RUN pip --no-cache-dir install ninja
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conda install -c anaconda -y python=$PYTHON_VERSION \
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pip=18.1 \
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setuptools=40.6.3 \
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six=1.12.0 \
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numpy=1.16.2 \
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pyyaml=5.1 \
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mkl=2019.1 \
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mkl-include=2019.1 \
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cython=0.29.6 \
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typing=3.6.4 \
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ninja=1.9.0
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# clone and build pytorch with
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RUN mv /opt/conda/compiler_compat/ld /opt/conda/compiler_compat/ld.orig
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RUN cd /tmp && git clone https://github.com/pytorch/pytorch.git
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WORKDIR /tmp/pytorch
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# includes patches for optimized ideep backend for inference
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RUN git checkout 4ac91b2 &&\
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git submodule update --init
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RUN CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" \
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BUILD_ONNX_PYTHON=ON \
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USE_OPENMP=ON \
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pip install -v .
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# install horovod and additional python packages for vision an notebook
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RUN pip --no-cache-dir install torchvision
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RUN pip --no-cache-dir install ipython ipykernel jupyter && \
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python -m ipykernel.kernelspec
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RUN HOROVOD_WITH_TORCH=1 pip install --no-cache-dir horovod==${HOROVOD_VERSION}
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RUN mv /opt/conda/compiler_compat/ld.orig /opt/conda/compiler_compat/ld
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# setup onnx and helper packages for caffe2
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RUN conda install -y -c conda-forge onnx && \
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conda install libgcc=5.2.0 && \
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pip install --no-cache-dir future \
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hypothesis protobuf networkx opencv-python
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RUN conda install -c conda-forge -y \
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gcc=4.8.5 \
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libgcc=7.2.0
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#fix from:https://github.com/ContinuumIO/anaconda-issues/issues/5191
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RUN \
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@@ -54,10 +39,45 @@ RUN \
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ln -sf libstdc++.so.6.0.25 libstdc++.so && \
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ln -sf libstdc++.so.6.0.25 libstdc++.so.6
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# clone and build pytorch with
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RUN mv /opt/conda/compiler_compat/ld /opt/conda/compiler_compat/ld.orig
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RUN cd /tmp && git clone https://github.com/pytorch/pytorch.git
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WORKDIR /tmp/pytorch
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RUN git checkout 4ac91b2 &&\
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git submodule update --init
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RUN CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" \
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BUILD_ONNX_PYTHON=ON \
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USE_OPENMP=ON \
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pip install -v .
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# torchvision and jupyter
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RUN pip --no-cache-dir install \
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torchvision==0.2.2 \
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jupyterlab==0.35.4 \
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jupyterhub==0.9.4 \
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ipython==7.4.0 \
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ipykernel==5.1.0 && \
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python -m ipykernel install --user
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# install horovod
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RUN HOROVOD_WITH_TORCH=1 pip install --no-cache-dir horovod==0.16.0
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RUN mv /opt/conda/compiler_compat/ld.orig /opt/conda/compiler_compat/ld
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# setup onnx and helper packages for caffe2
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RUN conda install -c conda-forge -c anaconda -y \
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onnx=1.4.1
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RUN pip --no-cache-dir install \
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future==0.17.1 \
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hypothesis==4.14.0 \
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protobuf==3.7.0 \
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networkx==2.2 \
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opencv-python==4.0.0.21
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# clean up and init
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RUN conda clean -typsy
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RUN rm -fr /tmp/*
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RUN conda clean -typsy &&\
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rm -fr /tmp/*
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WORKDIR /workspace
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RUN chmod -R a+w /workspace
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RUN echo "export PATH=$PATH" >> ~/.bashrc
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RUN chmod -R a+w /workspace &&\
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echo "export PATH=$PATH" >> ~/.bashrc
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CMD /bin/bash && source ~/.bashrc
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@@ -14,4 +14,4 @@ docker build --no-cache -t clearlinux/stacks-pytorch-mkl .
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* `swupd_args` specifies [swupd update](https://github.com/clearlinux/swupd-client/blob/master/docs/swupd.1.rst#options) flags passed to the update during build.
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>NOTE: An empty `swupd_args` will default to Clear Linux OS latest version. Consider this when building from the Dockerfile, as an OS update will be performed. The docker image in this registry was built and validated using version 28560.
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>NOTE: An empty `swupd_args` will default to Clear Linux OS latest version. Consider this when building from the Dockerfile, as an OS update will be performed. The docker image in this registry was built and validated using version 28680.
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@@ -14,4 +14,4 @@ docker build --no-cache -t clearlinux/stacks-pytorch-oss .
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* `swupd_args` specifies [swupd update](https://github.com/clearlinux/swupd-client/blob/master/docs/swupd.1.rst#options) flags passed to the update during build.
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>NOTE: An empty `swupd_args` will default to Clear Linux OS latest version. Consider this when building from the Dockerfile, as an OS update will be performed. The docker image in this registry was built and validated using version 28560.
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>NOTE: An empty `swupd_args` will default to Clear Linux OS latest version. Consider this when building from the Dockerfile, as an OS update will be performed. The docker image in this registry was built and validated using version 28680.
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@@ -9,7 +9,7 @@ To offer more flexibility, we are releasing multiple versions of the Deep Learni
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> **Note:**
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Clear Linux will be automatically updated to the latest release version in the container. The minimum validated version of Clear Linux for this stack is 28560.
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Clear Linux will be automatically updated to the latest release version in the container. The minimum validated version of Clear Linux for this stack is 28680.
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> **Note:**
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> For multi-node support, we include a registry with a set of jsonnet files to show integration with Kubeflow for deployment.
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