title: Unable to compile the example for Eigen SVD
body: <p>I am trying to compile the example provided for <a href="https://eigen.tuxfamily.org/dox/classEigen_1_1JacobiSVD.html" rel="nofollow noreferrer">Eigen::JacobiSVD</a> and I am getting the following error,</p>
  <pre><code>/usr/local/include/eigen3/Eigen/src/SVD/JacobiSVD.h: In instantiation of ‘Eigen::JacobiSVD&lt;MatrixType, QRPreconditioner&gt;&amp; Eigen::JacobiSVD&lt;MatrixType, QRPreconditioner&gt;::compute(const MatrixType&amp;, unsigned int) [with _MatrixType = Eigen::Matrix&lt;float, -1, -1&gt;; int QRPreconditioner = 40; Eigen::JacobiSVD&lt;MatrixType, QRPreconditioner&gt;::MatrixType = Eigen::Matrix&lt;float, -1, -1&gt;]’:
  /usr/local/include/eigen3/Eigen/src/SVD/JacobiSVD.h:549:14:   required from ‘Eigen::JacobiSVD&lt;MatrixType, QRPreconditioner&gt;::JacobiSVD(const MatrixType&amp;, unsigned int) [with _MatrixType = Eigen::Matrix&lt;float, -1, -1&gt;; int QRPreconditioner = 40; Eigen::JacobiSVD&lt;MatrixType, QRPreconditioner&gt;::MatrixType = Eigen::Matrix&lt;float, -1, -1&gt;]’
  demo.cpp:9:55:   required from here
  /usr/local/include/eigen3/Eigen/src/SVD/JacobiSVD.h:692:27: error: ‘struct Eigen::internal::qr_preconditioner_impl&lt;Eigen::Matrix&lt;float, -1, -1&gt;, 40, 0, true&gt;’ has no member named ‘run’
       m_qr_precond_morecols.run(*this, m_scaledMatrix);
       ~~~~~~~~~~~~~~~~~~~~~~^~~
  /usr/local/include/eigen3/Eigen/src/SVD/JacobiSVD.h:693:27: error: ‘struct Eigen::internal::qr_preconditioner_impl&lt;Eigen::Matrix&lt;float, -1, -1&gt;, 40, 1, true&gt;’ has no member named ‘run’
       m_qr_precond_morerows.run(*this, m_scaledMatrix);
  </code></pre>
  <p>Could you please help me with this? Thanks</p>
  <p>Code :</p>
  <pre><code>#include &lt;Eigen/Core&gt;
  #include &lt;Eigen/SVD&gt;
  #include &lt;iostream&gt;
  using namespace std;
  using namespace Eigen;
  int main () {
      MatrixXf m = MatrixXf::Random(3,2);
      cout &lt;&lt; &quot;Here is the matrix m:&quot; &lt;&lt; endl &lt;&lt; m &lt;&lt; endl;
      JacobiSVD&lt;MatrixXf, ComputeThinU | ComputeThinV&gt; svd(m);
      cout &lt;&lt; &quot;Its singular values are:&quot; &lt;&lt; endl &lt;&lt; svd.singularValues() &lt;&lt; endl;
      cout &lt;&lt; &quot;Its left singular vectors are the columns of the thin U matrix:&quot; &lt;&lt; endl &lt;&lt; svd.matrixU() &lt;&lt; endl;
      cout &lt;&lt; &quot;Its right singular vectors are the columns of the thin V matrix:&quot; &lt;&lt; endl &lt;&lt; svd.matrixV() &lt;&lt; endl;
      Vector3f rhs(1, 0, 0);
      cout &lt;&lt; &quot;Now consider this rhs vector:&quot; &lt;&lt; endl &lt;&lt; rhs &lt;&lt; endl;
      cout &lt;&lt; &quot;A least-squares solution of m*x = rhs is:&quot; &lt;&lt; endl &lt;&lt; svd.solve(rhs) &lt;&lt; endl;
  }
  </code></pre>
  <p><strong>g++ : 7.5</strong></p>
  <p><strong>Eigen : 3.4.0</strong></p>