Upgrade eigen to 3.4.0

Steps:
 * Removed common files between Android copy and the matching upstream copy
 * Obtained latest upstream tarball (see README.version)
 * Extracted over the directory

Bug: 148287349
Test: presubmit
Change-Id: Iee2744719075fdf000b315e973645923da766111

1 files changed, 10 insertions, 5 deletions

diff --git a/test/redux.cpp b/test/redux.cpp
index 989e1057b..fdbab7714 100644
--- a/test/redux.cpp
+++ b/test/redux.cpp
@@ -9,12 +9,13 @@
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #define TEST_ENABLE_TEMPORARY_TRACKING
+#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 8
+// ^^ see bug 1449
 
 #include "main.h"
 
 template<typename MatrixType> void matrixRedux(const MatrixType& m)
 {
-  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
 
@@ -27,6 +28,9 @@ template<typename MatrixType> void matrixRedux(const MatrixType& m)
   // failures if we underflow into denormals. Thus, we scale so that entries are close to 1.
   MatrixType m1_for_prod = MatrixType::Ones(rows, cols) + RealScalar(0.2) * m1;
 
+  Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> m2(rows,rows);
+  m2.setRandom();
+
   VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
   VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy
   Scalar s(0), p(1), minc(numext::real(m1.coeff(0))), maxc(numext::real(m1.coeff(0)));
@@ -45,6 +49,10 @@ template<typename MatrixType> void matrixRedux(const MatrixType& m)
   VERIFY_IS_APPROX(m1_for_prod.prod(), p);
   VERIFY_IS_APPROX(m1.real().minCoeff(), numext::real(minc));
   VERIFY_IS_APPROX(m1.real().maxCoeff(), numext::real(maxc));
+  
+  // test that partial reduction works if nested expressions is forced to evaluate early
+  VERIFY_IS_APPROX((m1.matrix() * m1.matrix().transpose())       .cwiseProduct(m2.matrix()).rowwise().sum().sum(), 
+                   (m1.matrix() * m1.matrix().transpose()).eval().cwiseProduct(m2.matrix()).rowwise().sum().sum());
 
   // test slice vectorization assuming assign is ok
   Index r0 = internal::random<Index>(0,rows-1);
@@ -71,15 +79,12 @@ template<typename MatrixType> void matrixRedux(const MatrixType& m)
 
   // test nesting complex expression
   VERIFY_EVALUATION_COUNT( (m1.matrix()*m1.matrix().transpose()).sum(), (MatrixType::IsVectorAtCompileTime && MatrixType::SizeAtCompileTime!=1 ? 0 : 1) );
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> m2(rows,rows);
-  m2.setRandom();
   VERIFY_EVALUATION_COUNT( ((m1.matrix()*m1.matrix().transpose())+m2).sum(),(MatrixType::IsVectorAtCompileTime && MatrixType::SizeAtCompileTime!=1 ? 0 : 1));
 }
 
 template<typename VectorType> void vectorRedux(const VectorType& w)
 {
   using std::abs;
-  typedef typename VectorType::Index Index;
   typedef typename VectorType::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
   Index size = w.size();
@@ -146,7 +151,7 @@ template<typename VectorType> void vectorRedux(const VectorType& w)
   VERIFY_RAISES_ASSERT(v.head(0).maxCoeff());
 }
 
-void test_redux()
+EIGEN_DECLARE_TEST(redux)
 {
   // the max size cannot be too large, otherwise reduxion operations obviously generate large errors.
   int maxsize = (std::min)(100,EIGEN_TEST_MAX_SIZE);