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* Upgrade presets for MKL 2020.3, DNNL 1.6.2
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‎CHANGELOG.md‎

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* Add support for Windows to presets for Qt ([issue #862](https://github.com/bytedeco/javacpp-presets/issues/862))
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* Fix JPMS modules for CUDA, ARPACK-NG, GSL, SciPy, Gym, MXNet ([pull #880](https://github.com/bytedeco/javacpp-presets/pull/880) and [pull #881](https://github.com/bytedeco/javacpp-presets/pull/881)), OpenCV, CPython, LLVM, Tesseract, Qt ([pull #928](https://github.com/bytedeco/javacpp-presets/pull/928))
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* Build OpenBLAS with a `TARGET` even for `DYNAMIC_ARCH` to avoid SIGILL ([issue eclipse/deeplearning4j#8747](https://github.com/eclipse/deeplearning4j/issues/8747))
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* Upgrade presets for OpenCV 4.4.0, FFmpeg 4.3.1 ([pull #891](https://github.com/bytedeco/javacpp-presets/pull/891)), Arrow 1.0.1, Hyperscan 5.3.0, MKL 2020.2, MKL-DNN 0.21.5, DNNL 1.6.1, OpenBLAS 0.3.10, CPython 3.7.9, NumPy 1.19.1, SciPy 1.5.2, Gym 0.17.2, LLVM 10.0.1, Leptonica 1.80.0, CUDA 11.0.3, cuDNN 8.0.3, NCCL 2.7.8, MXNet 1.7.0, TensorFlow 1.15.3, TensorRT 7.1, ONNX 1.7.0 ([pull #882](https://github.com/bytedeco/javacpp-presets/pull/882)), ONNX Runtime 1.4.0 ([pull #887](https://github.com/bytedeco/javacpp-presets/pull/887)), Qt 5.15.0, Skia 2.80.1, and their dependencies
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* Upgrade presets for OpenCV 4.4.0, FFmpeg 4.3.1 ([pull #891](https://github.com/bytedeco/javacpp-presets/pull/891)), Arrow 1.0.1, Hyperscan 5.3.0, MKL 2020.3, MKL-DNN 0.21.5, DNNL 1.6.2, OpenBLAS 0.3.10, CPython 3.7.9, NumPy 1.19.1, SciPy 1.5.2, Gym 0.17.2, LLVM 10.0.1, Leptonica 1.80.0, CUDA 11.0.3, cuDNN 8.0.3, NCCL 2.7.8, MXNet 1.7.0, TensorFlow 1.15.3, TensorRT 7.1, ONNX 1.7.0 ([pull #882](https://github.com/bytedeco/javacpp-presets/pull/882)), ONNX Runtime 1.4.0 ([pull #887](https://github.com/bytedeco/javacpp-presets/pull/887)), Qt 5.15.0, Skia 2.80.1, and their dependencies
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* Add `FullOptimization.h` allowing users to fully optimize LLVM modules ([pull #869](https://github.com/bytedeco/javacpp-presets/pull/869))
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### April 14, 2020 version 1.5.3

‎ci/install-travis.sh‎

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fi
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if [[ "$PROJ" == "mkl" ]] && [[ "$OS" =~ linux ]]; then
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#don't put in download dir as will be cached and we can use direct url instead
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curl -L http://registrationcenter-download.intel.com/akdlm/irc_nas/tec/16849/l_mkl_2020.2.254.tgz -o $HOME/mkl.tgz
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curl -L http://registrationcenter-download.intel.com/akdlm/irc_nas/tec/16903/l_mkl_2020.3.279.tgz -o $HOME/mkl.tgz
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tar xzvf $HOME/mkl.tgz -C $TRAVIS_BUILD_DIR/../
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sed -i -e 's/decline/accept/g' $TRAVIS_BUILD_DIR/../l_mkl_2020.2.254/silent.cfg
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docker exec -ti $DOCKER_CONTAINER_ID /bin/bash -xec "$HOME/build/l_mkl_2020.2.254/install.sh -s $HOME/build/l_mkl_2020.2.254/silent.cfg"
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sed -i -e 's/decline/accept/g' $TRAVIS_BUILD_DIR/../l_mkl_2020.3.279/silent.cfg
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docker exec -ti $DOCKER_CONTAINER_ID /bin/bash -xec "$HOME/build/l_mkl_2020.3.279/install.sh -s $HOME/build/l_mkl_2020.3.279/silent.cfg"
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fi
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if [ "$PROJ" == "tensorflow" ]; then
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echo "adding bazel for tensorflow"
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if [ "$PROJ" == "mkl" ]; then
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#don't put in download dir as will be cached and we can use direct url instead
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curl -L http://registrationcenter-download.intel.com/akdlm/irc_nas/tec/16851/m_mkl_2020.2.258.dmg -o $HOME/mkl.dmg
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curl -L http://registrationcenter-download.intel.com/akdlm/irc_nas/tec/16902/m_mkl_2020.3.279.dmg -o $HOME/mkl.dmg
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echo "Mount mkl dmg"
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hdiutil mount $HOME/mkl.dmg
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sleep 10
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cp /Volumes/m_mkl_2020.2.258/m_mkl_2020.2.258.app/Contents/MacOS/silent.cfg $HOME/silent.cfg
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cp /Volumes/m_mkl_2020.3.279/m_mkl_2020.3.279.app/Contents/MacOS/silent.cfg $HOME/silent.cfg
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sed -i -e 's/decline/accept/g' $HOME/silent.cfg
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sudo /Volumes/m_mkl_2020.2.258/m_mkl_2020.2.258.app/Contents/MacOS/install.sh -s $HOME/silent.cfg; export BREW_STATUS=$?
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sudo /Volumes/m_mkl_2020.3.279/m_mkl_2020.3.279.app/Contents/MacOS/install.sh -s $HOME/silent.cfg; export BREW_STATUS=$?
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echo "mkl status $BREW_STATUS"
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if [ $BREW_STATUS -ne 0 ]; then
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echo "mkl Failed"

‎ci/install-windows.sh‎

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if [ "$PROJ" == "mkl" ]; then
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echo Installing mkl
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curl -L -o mkl.exe "http://registrationcenter-download.intel.com/akdlm/irc_nas/tec/16850/w_mkl_2020.2.254.exe"
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curl -L -o mkl.exe "http://registrationcenter-download.intel.com/akdlm/irc_nas/tec/16896/w_mkl_2020.3.279.exe"
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./mkl.exe --s --x --f .
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./install.exe install --output=mkllog.txt -eula=accept
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sleep 60

‎dnnl/README.md‎

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------------
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This directory contains the JavaCPP Presets module for:
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* DNNL 1.6.1 https://01.org/dnnl
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* DNNL 1.6.2 https://01.org/dnnl
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Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>dnnl-platform</artifactId>
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<version>1.6.1-1.5.4-SNAPSHOT</version>
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<version>1.6.2-1.5.4-SNAPSHOT</version>
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</dependency>
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</dependencies>
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<build>

‎dnnl/cppbuild.sh‎

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export DNNL_CPU_RUNTIME="OMP" # or TBB
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TBB_VERSION=2020.3
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MKLDNN_VERSION=1.6.1
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MKLDNN_VERSION=1.6.2
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download https://github.com/oneapi-src/oneTBB/archive/v$TBB_VERSION.tar.gz oneTBB-$TBB_VERSION.tar.bz2
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download https://github.com/oneapi-src/oneDNN/archive/v$MKLDNN_VERSION.tar.gz oneDNN-$MKLDNN_VERSION.tar.bz2
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‎dnnl/platform/pom.xml‎

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<groupId>org.bytedeco</groupId>
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<artifactId>dnnl-platform</artifactId>
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<version>1.6.1-${project.parent.version}</version>
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<version>1.6.2-${project.parent.version}</version>
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<name>JavaCPP Presets Platform for DNNL</name>
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<properties>

‎dnnl/pom.xml‎

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<groupId>org.bytedeco</groupId>
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<artifactId>dnnl</artifactId>
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<version>1.6.1-${project.parent.version}</version>
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<version>1.6.2-${project.parent.version}</version>
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<name>JavaCPP Presets for DNNL</name>
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<dependencies>

‎dnnl/samples/pom.xml‎

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>dnnl-platform</artifactId>
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<version>1.6.1-1.5.4-SNAPSHOT</version>
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<version>1.6.2-1.5.4-SNAPSHOT</version>
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</dependency>
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</dependencies>
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<build>

‎gsl/README.md‎

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>mkl-platform-redist</artifactId>
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<version>2020.2-1.5.4-SNAPSHOT</version>
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<version>2020.3-1.5.4-SNAPSHOT</version>
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</dependency>
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</dependencies>

‎gsl/samples/pom.xml‎

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>mkl-platform-redist</artifactId>
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<version>2020.2-1.5.4-SNAPSHOT</version>
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<version>2020.3-1.5.4-SNAPSHOT</version>
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</dependency>
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</dependencies>

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