updated openvino version to 2019.1

SeldonIO · May 16, 2019 · 0e0ce34 · 0e0ce34
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diff --git a/wrappers/s2i/python_openvino/Dockerfile_openvino_base b/wrappers/s2i/python_openvino/Dockerfile_openvino_base
@@ -1,52 +1,59 @@
 FROM intelpython/intelpython3_core as DEV
 RUN apt-get update && apt-get install -y \
-            curl \
-            ca-certificates \
-            libgfortran3 \
-            vim \
+            autoconf \
+            automake \
             build-essential \
-            cmake \
-            curl \
-            wget \
-            libssl-dev \
             ca-certificates \
+            curl \
             git \
+            gstreamer1.0-plugins-base \
+            libavcodec-dev \
+            libavformat-dev \
             libboost-regex-dev \
-            gcc-multilib \
-            g++-multilib \
-            libgtk2.0-dev \
-            pkg-config \
-            unzip \
-            automake \
-            libtool \
-            autoconf \
-            libpng-dev \
             libcairo2-dev \
-            libpango1.0-dev \
+            libgfortran3 \
             libglib2.0-dev \
+            libgstreamer1.0-0 \
             libgtk2.0-dev \
+            libopenblas-dev \
+            libpango1.0-dev \
+            libpng-dev \
+            libssl-dev \
             libswscale-dev \
-            libavcodec-dev \
-            libavformat-dev \
-            libgstreamer1.0-0 \
-            gstreamer1.0-plugins-base \
+            libtool \
             libusb-1.0-0-dev \
-            libopenblas-dev
+            pkg-config \
+            unzip \
+            vim \
+            wget
 
-ARG DLDT_DIR=/dldt-2018_R5
-RUN git clone --depth=1 -b 2018_R5 https://github.com/opencv/dldt.git ${DLDT_DIR} && \
+RUN wget https://cmake.org/files/v3.14/cmake-3.14.3.tar.gz && \
+    tar -xvzf cmake-3.14.3.tar.gz && \
+    cd cmake-3.14.3/  && \
+    ./configure && \
+    make -j$(nproc) && \
+    make install
+
+RUN echo "deb http://ftp.us.debian.org/debian/ jessie main contrib non-free" >> /etc/apt/sources.list && \
+    echo "deb-src http://ftp.us.debian.org/debian/ jessie main contrib non-free" >> /etc/apt/sources.list && \
+    apt update && \
+    apt-get install -y g++-4.9
+ENV CXX=/usr/bin/g++-4.9
+RUN pip install cython numpy
+ARG DLDT_DIR=/dldt-2019_R1.0.1
+RUN git clone --depth=1 -b 2019_R1.0.1 https://github.com/opencv/dldt.git ${DLDT_DIR} && \
     cd ${DLDT_DIR} && git submodule init && git submodule update --recursive && \
     rm -Rf .git && rm -Rf model-optimizer
 
 WORKDIR ${DLDT_DIR}
-RUN curl -L -o ${DLDT_DIR}/mklml_lnx_2019.0.1.20180928.tgz https://github.com/intel/mkl-dnn/releases/download/v0.17.2/mklml_lnx_2019.0.1.20180928.tgz && \
-    tar -xzf ${DLDT_DIR}/mklml_lnx_2019.0.1.20180928.tgz && rm ${DLDT_DIR}/mklml_lnx_2019.0.1.20180928.tgz
-WORKDIR ${DLDT_DIR}/inference-engine
-RUN mkdir build && cd build && cmake -DGEMM=MKL  -DMKLROOT=${DLDT_DIR}/mklml_lnx_2019.0.1.20180928 -DENABLE_MKL_DNN=ON  -DCMAKE_BUILD_TYPE=Release ..
-RUN cd build && make -j4
-RUN pip install cython numpy && mkdir ie_bridges/python/build && cd ie_bridges/python/build && \
-    cmake -DInferenceEngine_DIR=${DLDT_DIR}/inference-engine/build -DPYTHON_EXECUTABLE=`which python` -DPYTHON_LIBRARY=/opt/conda/lib/libpython3.6m.so -DPYTHON_INCLUDE_DIR=/opt/conda/include/python3.6m .. && \
-    make -j4
+RUN curl -L https://github.com/intel/mkl-dnn/releases/download/v0.18/mklml_lnx_2019.0.3.20190220.tgz | tar -xz
+WORKDIR ${DLDT_DIR}/inference-engine/build
+RUN cmake -DGEMM=MKL  -DMKLROOT=${DLDT_DIR}/mklml_lnx_2019.0.3.20190220 -DENABLE_MKL_DNN=ON -DTHREADING=OMP -DCMAKE_BUILD_TYPE=Release ..
+RUN make -j$(nproc)
+WORKDIR ${DLDT_DIR}/inference-engine/ie_bridges/python/build
+RUN cmake -DInferenceEngine_DIR=${DLDT_DIR}/inference-engine/build -DPYTHON_EXECUTABLE=$(which python) -DPYTHON_LIBRARY=/opt/conda/lib/libpython3.6m.so -DPYTHON_INCLUDE_DIR=/opt/conda/include/python3.6m ${DLDT_DIR}/inference-engine/ie_bridges/python && \
+    make -j$(nproc)
+
 
 FROM intelpython/intelpython3_core as PROD
 
@@ -59,9 +66,9 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
             python3-setuptools \
             vim
 
-COPY --from=DEV /dldt-2018_R5/inference-engine/bin/intel64/Release/lib/*.so /usr/local/lib/
-COPY --from=DEV /dldt-2018_R5/inference-engine/ie_bridges/python/bin/intel64/Release/python_api/python3.6/openvino/ /usr/local/lib/openvino/
-COPY --from=DEV /dldt-2018_R5/mklml_lnx_2019.0.1.20180928/lib/lib*.so /usr/local/lib/
+COPY --from=DEV /dldt-2019_R1.0.1/inference-engine/bin/intel64/Release/lib/*.so /usr/local/lib/
+COPY --from=DEV /dldt-2019_R1.0.1/inference-engine/ie_bridges/python/bin/intel64/Release/python_api/python3.6/openvino/ /usr/local/lib/openvino/
+COPY --from=DEV /dldt-2019_R1.0.1/mklml_lnx_2019.0.3.20190220/lib/lib*.so /usr/local/lib/
 ENV LD_LIBRARY_PATH=/usr/local/lib
 ENV PYTHONPATH=/usr/local/lib
 
@@ -70,10 +77,11 @@ ENV PATH /opt/conda/envs/myenv/bin:$PATH
 RUN conda install -y tensorflow opencv && conda clean -a -y
 WORKDIR /microservice
 
-RUN pip install wheel
-RUN pip install seldon-core
+RUN pip install jaeger-client==3.13.0 seldon-core
 RUN pip install --upgrade setuptools
 
+RUN sed -i "s/max_workers=10/max_workers=1/g" /opt/conda/lib/python3.6/site-packages/seldon_core/wrapper.py
+# set the workers to 1 - it avoids conflicts in reusing the IE model object in parallel calls
 COPY ./s2i/bin/ /s2i/bin
 
 EXPOSE 5000
diff --git a/wrappers/s2i/python_openvino/README.md b/wrappers/s2i/python_openvino/README.md
@@ -33,7 +33,7 @@ Use s2i tool like documented [here](https://github.com/SeldonIO/seldon-core/blob
 An example is presented below:
 
 ```bash
-s2i build . seldonio/seldon-core-s2i-openvino:0.1 {target_component_image_name}
+s2i build . seldonio/seldon-core-s2i-openvino:0.2 {target_component_image_name}
 ```
 
 ## Examples
@@ -57,11 +57,13 @@ This Seldon base image contains, beside OpenVINO inference execution engine pyth
 - Intel optimized TensorFlow with MKL engine
 - Configured conda package manager
 
-In case you would use this compoment to run inference operations using TensorFlow with MKL, make sure you configure 
-also the following environment variables:
+OpenVINO and TensorFlow in this docker image, employs [MKL-DNN](https://github.com/intel/mkl-dnn) library
+with [OpenMP](https://www.openmp.org/) threading control.
+Make sure you configure optimal values for MKL related environment variables in the containers.
+Recommendations are listed below:
 
 `KMP_AFFINITY`=granularity=fine,verbose,compact,1,0
 
 `KMP_BLOCKTIME`=1
 
-`OMP_NUM_THREADS`={number of CPU cores}
+`OMP_NUM_THREADS`={number of physical CPU cores to allocate}