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diff --git a/eigen/test/eigen2/eigen2_svd.cpp b/eigen/test/eigen2/eigen2_svd.cpp
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+++ b/eigen/test/eigen2/eigen2_svd.cpp
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+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <Eigen/SVD>
+
+template<typename MatrixType> void svd(const MatrixType& m)
+{
+  /* this test covers the following files:
+     SVD.h
+  */
+  int rows = m.rows();
+  int cols = m.cols();
+
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  MatrixType a = MatrixType::Random(rows,cols);
+  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> b =
+    Matrix<Scalar, MatrixType::RowsAtCompileTime, 1>::Random(rows,1);
+  Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> x(cols,1), x2(cols,1);
+
+  RealScalar largerEps = test_precision<RealScalar>();
+  if (ei_is_same_type<RealScalar,float>::ret)
+    largerEps = 1e-3f;
+
+  {
+    SVD<MatrixType> svd(a);
+    MatrixType sigma = MatrixType::Zero(rows,cols);
+    MatrixType matU  = MatrixType::Zero(rows,rows);
+    sigma.block(0,0,cols,cols) = svd.singularValues().asDiagonal();
+    matU.block(0,0,rows,cols) = svd.matrixU();
+    VERIFY_IS_APPROX(a, matU * sigma * svd.matrixV().transpose());
+  }
+
+
+  if (rows==cols)
+  {
+    if (ei_is_same_type<RealScalar,float>::ret)
+    {
+      MatrixType a1 = MatrixType::Random(rows,cols);
+      a += a * a.adjoint() + a1 * a1.adjoint();
+    }
+    SVD<MatrixType> svd(a);
+    svd.solve(b, &x);
+    VERIFY_IS_APPROX(a * x,b);
+  }
+
+
+  if(rows==cols)
+  {
+    SVD<MatrixType> svd(a);
+    MatrixType unitary, positive;
+    svd.computeUnitaryPositive(&unitary, &positive);
+    VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows()));
+    VERIFY_IS_APPROX(positive, positive.adjoint());
+    for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity
+    VERIFY_IS_APPROX(unitary*positive, a);
+
+    svd.computePositiveUnitary(&positive, &unitary);
+    VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows()));
+    VERIFY_IS_APPROX(positive, positive.adjoint());
+    for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity
+    VERIFY_IS_APPROX(positive*unitary, a);
+  }
+}
+
+void test_eigen2_svd()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( svd(Matrix3f()) );
+    CALL_SUBTEST_2( svd(Matrix4d()) );
+    CALL_SUBTEST_3( svd(MatrixXf(7,7)) );
+    CALL_SUBTEST_4( svd(MatrixXd(14,7)) );
+    // complex are not implemented yet
+//     CALL_SUBTEST( svd(MatrixXcd(6,6)) );
+//     CALL_SUBTEST( svd(MatrixXcf(3,3)) );
+    SVD<MatrixXf> s;
+    MatrixXf m = MatrixXf::Random(10,1);
+    s.compute(m);
+  }
+}