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eigen: svd example, use pkg-config
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@@ -4208,7 +4208,7 @@ Header only linear algebra library supported by Buildroot:
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....
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./build -B 'BR2_PACKAGE_EIGEN=y' -k
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./run -F '/eigen.out'
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./run -F '/eigen.out;/eigen_svd.out'
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....
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===== PARSEC benchmark
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@@ -5050,7 +5050,7 @@ so which shows that the whole delay is inside our install itself.
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I put an `echo f` in `check_bin_arch`, and it just loops forever, does not stop on a particular package.
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Ignored / declied patch at: http://lists.busybox.net/pipermail/buildroot/2018-May/220662.html I might just fork Buildroot on the submodule if this keeps annoying me.
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Ignored / declined patch at: http://lists.busybox.net/pipermail/buildroot/2018-May/220662.html I might just fork Buildroot on the submodule if this keeps annoying me.
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=== Report upstream bugs
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@@ -15,6 +15,7 @@ endif
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ifeq ($(BR2_PACKAGE_EIGEN),y)
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# Header only.
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#LIBS += -leigen
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CXXFLAGS_EXTRA += $(shell $(PKG_CONFIG) --cflags --libs eigen3)
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else
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OUTS := $(filter-out eigen%$(OUT_EXT),$(OUTS))
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endif
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@@ -30,7 +30,3 @@ These programs can also be compiled and used on host.
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.. link:ioctl.c[]
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.. link:netlink.c[]
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.. link:poll.c[]
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. Buildroot libraries
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.. link:eigen.cpp[]
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.. link:openmp.c[]
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.. link:openblas.c[]
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@@ -1,14 +1,11 @@
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/* Official hello world. */
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/* Adapted from: https://eigen.tuxfamily.org/dox/GettingStarted.html */
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#include <iostream>
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#include <eigen3/Eigen/Dense>
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using Eigen::MatrixXd;
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int main()
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{
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MatrixXd m(2,2);
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m(0,0) = 3;
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m(1,0) = 2.5;
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m(0,1) = -1;
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m(1,1) = m(1,0) + m(0,1);
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std::cout << m << std::endl;
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#include <Eigen/Dense>
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int main() {
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Eigen::MatrixXd m(2,2);
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m(0,0) = 3;
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m(1,0) = 2.5;
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m(0,1) = -1;
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m(1,1) = m(1,0) + m(0,1);
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std::cout << m << std::endl;
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}
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24
kernel_module/user/eigen_svd.cpp
Normal file
24
kernel_module/user/eigen_svd.cpp
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@@ -0,0 +1,24 @@
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/* Adapted from: https://eigen.tuxfamily.org/dox/classEigen_1_1JacobiSVD.html */
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#include <iostream>
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using std::cout;
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using std::endl;
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#include <Eigen/Core>
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#include <Eigen/SVD>
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using Eigen::ComputeThinU;
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using Eigen::ComputeThinV;
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using Eigen::JacobiSVD;
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using Eigen::MatrixXf;
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using Eigen::Vector3f;
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int main() {
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MatrixXf m = MatrixXf::Random(3,2);
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JacobiSVD<MatrixXf> svd(m, ComputeThinU | ComputeThinV);
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Vector3f rhs(1, 0, 0);
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cout << "m = " << endl << m << endl << endl;
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cout << "svd.singularValues() = " << endl << svd.singularValues() << endl << endl;
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cout << "svd.MatrixU() = " << endl << svd.matrixU() << endl << endl;
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cout << "svd.MatrixV() = " << endl << svd.matrixV() << endl << endl;
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cout << "svd.solve() = " << endl << svd.solve(rhs) << endl << endl;
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}
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