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* Upgrade presets for DNNL 3.6.1, NumPy 2.1.3, OpenCL 3.0.17
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‎CHANGELOG.md

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@@ -9,7 +9,7 @@
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* Build FFmpeg with zimg to enable zscale filter ([pull #1481](https://github.com/bytedeco/javacpp-presets/pull/1481))
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* Enable PulseAudio support for FFmpeg on Linux ([pull #1472](https://github.com/bytedeco/javacpp-presets/pull/1472))
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* Virtualize `btCollisionWorld`, `btOverlapFilterCallback`, `btOverlapCallback` from Bullet Physics SDK ([pull #1475](https://github.com/bytedeco/javacpp-presets/pull/1475))
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* Upgrade presets for OpenCV 4.10.0, FFmpeg 7.1, Spinnaker 4.0.0.116 ([pull #1524](https://github.com/bytedeco/javacpp-presets/pull/1524)), MKL 2025.0, DNNL 3.6, OpenBLAS 0.3.28, CMINPACK 1.3.11, GSL 2.8, CPython 3.13.0, NumPy 2.1.2, SciPy 1.14.1, LLVM 19.1.3, LibRaw 0.21.2 ([pull #1520](https://github.com/bytedeco/javacpp-presets/pull/1520)), Leptonica 1.85.0, Tesseract 5.4.1, libffi 3.4.6, CUDA 12.6.2, cuDNN 9.5.1, NCCL 2.23.4, nvCOMP 4.1.0.6, OpenCL 3.0.16, NVIDIA Video Codec SDK 12.2.72, PyTorch 2.5.1 ([pull #1466](https://github.com/bytedeco/javacpp-presets/pull/1466)), SentencePiece 0.2.0, TensorFlow Lite 2.18.0, TensorRT 10.6.0.26, Triton Inference Server 2.51.0, ONNX 1.17.0, ONNX Runtime 1.20.0, TVM 0.18.0, and their dependencies
12+
* Upgrade presets for OpenCV 4.10.0, FFmpeg 7.1, Spinnaker 4.0.0.116 ([pull #1524](https://github.com/bytedeco/javacpp-presets/pull/1524)), MKL 2025.0, DNNL 3.6.1, OpenBLAS 0.3.28, CMINPACK 1.3.11, GSL 2.8, CPython 3.13.0, NumPy 2.1.3, SciPy 1.14.1, LLVM 19.1.3, LibRaw 0.21.2 ([pull #1520](https://github.com/bytedeco/javacpp-presets/pull/1520)), Leptonica 1.85.0, Tesseract 5.4.1, libffi 3.4.6, CUDA 12.6.2, cuDNN 9.5.1, NCCL 2.23.4, nvCOMP 4.1.0.6, OpenCL 3.0.17, NVIDIA Video Codec SDK 12.2.72, PyTorch 2.5.1 ([pull #1466](https://github.com/bytedeco/javacpp-presets/pull/1466)), SentencePiece 0.2.0, TensorFlow Lite 2.18.0, TensorRT 10.6.0.26, Triton Inference Server 2.51.0, ONNX 1.17.0, ONNX Runtime 1.20.0, TVM 0.18.0, and their dependencies
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### January 29, 2024 version 1.5.10
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* Introduce `macosx-arm64` builds for PyTorch ([pull #1463](https://github.com/bytedeco/javacpp-presets/pull/1463))

‎dnnl/README.md

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------------
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This directory contains the JavaCPP Presets module for:
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* DNNL 3.6 https://01.org/dnnl
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* DNNL 3.6.1 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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------------
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Here is a simple example of DNNL ported to Java from this C++ source file:
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* https://github.com/oneapi-src/oneDNN/blob/v3.6/examples/cnn_inference_int8.cpp
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* https://github.com/oneapi-src/oneDNN/blob/v3.6.1/examples/cnn_inference_int8.cpp
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We can use [Maven 3](http://maven.apache.org/) to download and install automatically all the class files as well as the native binaries. To run this sample code, after creating the `pom.xml` and `CpuCnnInferenceInt8.java` source files below, simply execute on the command line:
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```bash
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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>3.6-1.5.11-SNAPSHOT</version>
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<version>3.6.1-1.5.11-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_GPU_RUNTIME="OCL"
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TBB_VERSION=2020.3
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MKLDNN_VERSION=3.6
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MKLDNN_VERSION=3.6.1
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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>3.6-${project.parent.version}</version>
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<version>3.6.1-${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>3.6-${project.parent.version}</version>
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<version>3.6.1-${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>3.6-1.5.11-SNAPSHOT</version>
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<version>3.6.1-1.5.11-SNAPSHOT</version>
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</dependency>
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</dependencies>
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<build>

‎dnnl/src/gen/java/org/bytedeco/dnnl/global/dnnl.java

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public static final int DNNL_VERSION_MINOR = 6;
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/** Patch version */
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public static final int DNNL_VERSION_PATCH = 0;
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public static final int DNNL_VERSION_PATCH = 1;
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// clang-format on
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‎numpy/README.md

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------------
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This directory contains the JavaCPP Presets module for:
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* NumPy 2.1.2 http://www.numpy.org/
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* NumPy 2.1.3 http://www.numpy.org/
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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>numpy-platform</artifactId>
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<version>2.1.2-1.5.11-SNAPSHOT</version>
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<version>2.1.3-1.5.11-SNAPSHOT</version>
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</dependency>
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<!-- Additional dependencies to use bundled full version of MKL -->

‎numpy/cppbuild.sh

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exit
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fi
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NUMPY_VERSION=2.1.2
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NUMPY_VERSION=2.1.3
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download https://github.com/numpy/numpy/releases/download/v$NUMPY_VERSION/numpy-$NUMPY_VERSION.tar.gz numpy-$NUMPY_VERSION.tar.gz
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mkdir -p $PLATFORM

‎numpy/platform/pom.xml

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<groupId>org.bytedeco</groupId>
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<artifactId>numpy-platform</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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<name>JavaCPP Presets Platform for NumPy</name>
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<properties>

‎numpy/pom.xml

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<groupId>org.bytedeco</groupId>
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<artifactId>numpy</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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<name>JavaCPP Presets for NumPy</name>
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<dependencies>

‎numpy/samples/pom.xml

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy-platform</artifactId>
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<version>2.1.2-1.5.11-SNAPSHOT</version>
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<version>2.1.3-1.5.11-SNAPSHOT</version>
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</dependency>
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<!-- Additional dependencies to use bundled full version of MKL -->

‎numpy/src/gen/java/org/bytedeco/numpy/global/numpy.java

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@@ -179,7 +179,14 @@ public class numpy extends org.bytedeco.numpy.presets.numpy {
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// #error "NPY_TARGET_VERSION higher than NumPy headers!"
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// #elif NPY_FEATURE_VERSION < NPY_1_15_API_VERSION
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/* No support for irrelevant old targets, no need for error, but warn. */
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// #warning "Requested NumPy target lower than supported NumPy 1.15."
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// #ifndef _MSC_VER
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// #warning "Requested NumPy target lower than supported NumPy 1.15."
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// #else
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// #define _WARN___STR2__(x) #x
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// #define _WARN___STR1__(x) _WARN___STR2__(x)
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// #define _WARN___LOC__ __FILE__ "(" _WARN___STR1__(__LINE__) ") : Warning Msg: "
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// #pragma message(_WARN___LOC__"Requested NumPy target lower than supported NumPy 1.15.")
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// #endif
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// #endif
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/*

‎numpy/src/main/java/org/bytedeco/numpy/presets/numpy.java

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"NPY_FLOAT256", "NPY_COMPLEX512", "NPY_COMPLEX512_FMT",
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"NPY_SIGJMP_BUF", "_npy_signbit_f", "_npy_signbit_d", "_npy_signbit_ld",
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"npy_degrees", "npy_degreesf", "npy_degreesl", "npy_radians", "npy_radiansf", "npy_radiansl",
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"PyStringScalarObject", /*"PyUnicodeScalarObject",*/ "__COMP_NPY_UNUSED",
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"PyStringScalarObject", /*"PyUnicodeScalarObject",*/ "__COMP_NPY_UNUSED", "_WARN___LOC__",
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"PyArrayScalar_False", "PyArrayScalar_True", "PyArrayScalar_RETURN_FALSE", "PyArrayScalar_RETURN_TRUE", "NPY_NO_EXPORT",
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"PyArray_malloc", "PyArray_free", "PyArray_realloc",
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"NPY_BEGIN_THREADS_DEF", "NPY_BEGIN_ALLOW_THREADS", "NPY_END_ALLOW_THREADS", "NPY_BEGIN_THREADS", "NPY_END_THREADS",

‎onnxruntime/cppbuild.sh

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sedinplace 's:/Yucuda_pch.h /FIcuda_pch.h::g' cmake/onnxruntime_providers_cuda.cmake cmake/onnxruntime_providers.cmake
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sedinplace 's/${PROJECT_SOURCE_DIR}\/external\/cub//g' cmake/onnxruntime_providers_cuda.cmake cmake/onnxruntime_providers.cmake
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sedinplace 's/ONNXRUNTIME_PROVIDERS_SHARED)/ONNXRUNTIME_PROVIDERS_SHARED onnxruntime_providers_shared)/g' cmake/onnxruntime_providers_cpu.cmake cmake/onnxruntime_providers.cmake
98-
sedinplace 's/DNNL_TAG v.*)/DNNL_TAG v3.6)/g' cmake/external/dnnl.cmake
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sedinplace 's/DNNL_TAG v.*)/DNNL_TAG v3.6.1)/g' cmake/external/dnnl.cmake
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sedinplace 's/DNNL_SHARED_LIB libdnnl.1.dylib/DNNL_SHARED_LIB libdnnl.2.dylib/g' cmake/external/dnnl.cmake
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sedinplace 's/DNNL_SHARED_LIB libdnnl.so.1/DNNL_SHARED_LIB libdnnl.so.2/g' cmake/external/dnnl.cmake
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sedinplace 's/ CMAKE_ARGS/CMAKE_ARGS -DMKLDNN_BUILD_EXAMPLES=OFF -DMKLDNN_BUILD_TESTS=OFF -DDNNL_CPU_RUNTIME=SEQ/g' cmake/external/dnnl.cmake

‎onnxruntime/platform/gpu/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>3.6-${project.parent.version}</version>
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<version>3.6.1-${project.parent.version}</version>
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</dependency>
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<dependency>
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<groupId>${project.groupId}</groupId>

‎onnxruntime/platform/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>3.6-${project.parent.version}</version>
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<version>3.6.1-${project.parent.version}</version>
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</dependency>
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<dependency>
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<groupId>${project.groupId}</groupId>

‎onnxruntime/pom.xml

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>dnnl</artifactId>
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<version>3.6-${project.parent.version}</version>
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<version>3.6.1.1-${project.parent.version}</version>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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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>3.6-${project.parent.version}</version>
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<version>3.6.1.1-${project.parent.version}</version>
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</dependency>
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</dependencies>
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<configuration>

‎opencl/README.md

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------------
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This directory contains the JavaCPP Presets module for:
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* OpenCL 3.0.16 https://www.khronos.org/registry/OpenCL/
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* OpenCL 3.0.17 https://www.khronos.org/registry/OpenCL/
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‎opencl/cppbuild.sh

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exit
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fi
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OPENCL_VERSION=2024.05.08
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CLHPP_VERSION=2024.05.08
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OPENCL_VERSION=2024.10.24
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CLHPP_VERSION=2024.10.24
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download https://github.com/KhronosGroup/OpenCL-Headers/archive/v$OPENCL_VERSION.tar.gz OpenCL-Headers-$OPENCL_VERSION.tar.gz
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download https://github.com/KhronosGroup/OpenCL-ICD-Loader/archive/v$OPENCL_VERSION.tar.gz OpenCL-ICD-Loader-$OPENCL_VERSION.tar.gz
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download https://github.com/KhronosGroup/OpenCL-CLHPP/archive/v$CLHPP_VERSION.tar.gz OpenCL-CLHPP-$CLHPP_VERSION.tar.gz

‎opencv/README.md

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy-platform</artifactId>
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<version>2.1.2-1.5.11-SNAPSHOT</version>
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<version>2.1.3-1.5.11-SNAPSHOT</version>
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</dependencies>

‎opencv/pom.xml

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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<optional>true</optional>
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</dependency>
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<dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy-platform</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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</dependency>
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</dependencies>
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<configuration>

‎opencv/samples/pom.xml

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy-platform</artifactId>
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<version>2.1.2-1.5.11-SNAPSHOT</version>
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<version>2.1.3-1.5.11-SNAPSHOT</version>
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</dependency>
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</dependencies>

‎platform/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>3.6-${project.version}</version>
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<version>3.6.1-${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy-platform</artifactId>
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<version>2.1.2-${project.version}</version>
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<version>2.1.3-${project.version}</version>
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<dependency>
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<groupId>org.bytedeco</groupId>

‎pytorch/pom.xml

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy-platform</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>

‎scipy/cppbuild.sh

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echo "extra_link_args = -lgfortran" >> site.cfg
125125
chmod +x "$CPYTHON_HOST_PATH/bin/python3.13"
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export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$CPYTHON_HOST_PATH/lib/:$CPYTHON_HOST_PATH"
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"$CPYTHON_HOST_PATH/bin/python3.13" -m pip install --no-deps --target="$CPYTHON_HOST_PATH/lib/python3.13/" crossenv==1.4 numpy==2.1.2 $TOOLS
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"$CPYTHON_HOST_PATH/bin/python3.13" -m pip install --no-deps --target="$CPYTHON_HOST_PATH/lib/python3.13/" crossenv==1.4 numpy==2.1.3 $TOOLS
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"$CPYTHON_HOST_PATH/bin/python3.13" -m crossenv "$PYTHON_BIN_PATH" crossenv
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cp -a "$NUMPY_PATH/python/numpy" "$CPYTHON_HOST_PATH/lib/python3.13/"
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‎scipy/platform/pom.xml

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy-platform</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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</dependency>
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<dependency>
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<groupId>${project.groupId}</groupId>

‎scipy/pom.xml

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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>numpy</artifactId>
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<version>2.1.2-${project.parent.version}</version>
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<version>2.1.3-${project.parent.version}</version>
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<classifier>${javacpp.platform}</classifier>
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</dependency>
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</dependencies>

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