Before 3.4 branch

The namespace declaration for googlehash is a configurable macro that
can be disabled.  In particular, it is disabled within google, causing
compile errors since `dense_hash_map`/`sparse_hash_map` are then in
the global namespace instead of in `::google`.

Here we play a bit of gynastics to allow for both `google::*_hash_map`
and `*_hash_map`, while limiting namespace polution.  Symbols within
the `::google` namespace are imported into `Eigen::google`.

We also remove checks based on `_SPARSE_HASH_MAP_H_`, as this is
fragile, and instead require `EIGEN_GOOGLEHASH_SUPPORT` to be
defined.

.gitlab-ci.yml

@@ -8,6 +8,8 @@
 # with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 stages:
+  - buildsmoketests
+  - smoketests
   - build
   - test
 
@@ -16,5 +18,6 @@ variables:
   EIGEN_CI_CMAKE_GENEATOR: "Ninja"
 
 include:
+  - "/ci/smoketests.gitlab-ci.yml"
   - "/ci/build.gitlab-ci.yml"
   - "/ci/test.gitlab-ci.yml"

Eigen/src/Core/GenericPacketMath.h

@@ -556,7 +556,7 @@ template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 peven_mask(const Packet& /*a*/) {
   typedef typename unpacket_traits<Packet>::type Scalar;
   const size_t n = unpacket_traits<Packet>::size;
-  Scalar elements[n];
+  EIGEN_ALIGN_TO_BOUNDARY(sizeof(Packet)) Scalar elements[n];
   for(size_t i = 0; i < n; ++i) {
     memset(elements+i, ((i & 1) == 0 ? 0xff : 0), sizeof(Scalar));
   }
@@ -731,7 +731,7 @@ EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type
 predux_helper(const Packet& a, Op op) {
   typedef typename unpacket_traits<Packet>::type Scalar;
   const size_t n = unpacket_traits<Packet>::size;
-  Scalar elements[n];
+  EIGEN_ALIGN_TO_BOUNDARY(sizeof(Packet)) Scalar elements[n];
   pstoreu<Scalar>(elements, a);
   for(size_t k = n / 2; k > 0; k /= 2)  {
     for(size_t i = 0; i < k; ++i) {

Eigen/src/Core/StlIterators.h

@@ -7,6 +7,9 @@
 // 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/.
 
+#ifndef EIGEN_STLITERATORS_H
+#define EIGEN_STLITERATORS_H
+
 namespace Eigen {
 
 namespace internal {
@@ -30,10 +33,10 @@ public:
   typedef Index difference_type;
   typedef std::random_access_iterator_tag iterator_category;
 
-  indexed_based_stl_iterator_base() : mp_xpr(0), m_index(0) {}
-  indexed_based_stl_iterator_base(XprType& xpr, Index index) : mp_xpr(&xpr), m_index(index) {}
+  indexed_based_stl_iterator_base() EIGEN_NO_THROW : mp_xpr(0), m_index(0) {}
+  indexed_based_stl_iterator_base(XprType& xpr, Index index) EIGEN_NO_THROW : mp_xpr(&xpr), m_index(index) {}
 
-  indexed_based_stl_iterator_base(const non_const_iterator& other)
+  indexed_based_stl_iterator_base(const non_const_iterator& other) EIGEN_NO_THROW
     : mp_xpr(other.mp_xpr), m_index(other.m_index)
   {}
 
@@ -190,17 +193,17 @@ public:
   typedef typename internal::conditional<bool(is_lvalue), value_type&, const value_type&>::type reference;
 
 
-  pointer_based_stl_iterator() : m_ptr(0) {}
-  pointer_based_stl_iterator(XprType& xpr, Index index) : m_incr(xpr.innerStride())
+  pointer_based_stl_iterator() EIGEN_NO_THROW : m_ptr(0) {}
+  pointer_based_stl_iterator(XprType& xpr, Index index) EIGEN_NO_THROW : m_incr(xpr.innerStride())
   {
     m_ptr = xpr.data() + index * m_incr.value();
   }
 
-  pointer_based_stl_iterator(const non_const_iterator& other)
+  pointer_based_stl_iterator(const non_const_iterator& other) EIGEN_NO_THROW
     : m_ptr(other.m_ptr), m_incr(other.m_incr)
   {}
 
-  pointer_based_stl_iterator& operator=(const non_const_iterator& other)
+  pointer_based_stl_iterator& operator=(const non_const_iterator& other) EIGEN_NO_THROW
   {
     m_ptr = other.m_ptr;
     m_incr.setValue(other.m_incr);
@@ -456,3 +459,5 @@ inline typename DenseBase<Derived>::const_iterator DenseBase<Derived>::cend() co
 }
 
 } // namespace Eigen
+
+#endif // EIGEN_STLITERATORS_H

Eigen/src/Core/arch/AltiVec/Complex.h

@@ -139,8 +139,8 @@ EIGEN_STRONG_INLINE Packet2cf pload2(const std::complex<float>* from0, const std
   __asm__ ("xxpermdi %x0, %x2, %x1, 0" : "=wa" (res0) : "wa" (res0), "wa" (res1));
 #endif
 #else
-  *((std::complex<float> *)&res0[0]) = *from0;
-  *((std::complex<float> *)&res1[0]) = *from1;
+  *reinterpret_cast<std::complex<float> *>(&res0) = *from0;
+  *reinterpret_cast<std::complex<float> *>(&res1) = *from1;
   res0 = vec_perm(res0, res1, p16uc_TRANSPOSE64_HI);
 #endif
   return Packet2cf(res0);

Eigen/src/Core/arch/AltiVec/MatrixProduct.h

@@ -486,19 +486,28 @@ struct dhs_cpack {
         if(((StorageOrder == ColMajor) && UseLhs) || (((StorageOrder == RowMajor) && !UseLhs)))
         {
           if (UseLhs) {
-            cblock.packet[0] = pload<PacketC>(&lhs(j + 0, i));
-            cblock.packet[1] = pload<PacketC>(&lhs(j + 2, i));
+            cblock.packet[0] = lhs.template loadPacket<PacketC>(j + 0, i);
+            cblock.packet[1] = lhs.template loadPacket<PacketC>(j + 2, i);
           } else {
-            cblock.packet[0] = pload<PacketC>(&lhs(i, j + 0));
-            cblock.packet[1] = pload<PacketC>(&lhs(i, j + 2));
+            cblock.packet[0] = lhs.template loadPacket<PacketC>(i, j + 0);
+            cblock.packet[1] = lhs.template loadPacket<PacketC>(i, j + 2);
           }
         } else {
+          const std::complex<Scalar> *lhs0, *lhs1;
           if (UseLhs) {
-            cblock.packet[0] = pload2(&lhs(j + 0, i), &lhs(j + 1, i));
-            cblock.packet[1] = pload2(&lhs(j + 2, i), &lhs(j + 3, i));
+            lhs0 = &lhs(j + 0, i);
+            lhs1 = &lhs(j + 1, i);
+            cblock.packet[0] = pload2(lhs0, lhs1);
+            lhs0 = &lhs(j + 2, i);
+            lhs1 = &lhs(j + 3, i);
+            cblock.packet[1] = pload2(lhs0, lhs1);
           } else {
-            cblock.packet[0] = pload2(&lhs(i, j + 0), &lhs(i, j + 1));
-            cblock.packet[1] = pload2(&lhs(i, j + 2), &lhs(i, j + 3));
+            lhs0 = &lhs(i, j + 0);
+            lhs1 = &lhs(i, j + 1);
+            cblock.packet[0] = pload2(lhs0, lhs1);
+            lhs0 = &lhs(i, j + 2);
+            lhs1 = &lhs(i, j + 3);
+            cblock.packet[1] = pload2(lhs0, lhs1);
           }
         }
 
@@ -859,8 +868,8 @@ struct dhs_cpack<double, Index, DataMapper, Packet, PacketC, StorageOrder, Conju
         PacketBlock<Packet,1> blockr, blocki;
         PacketBlock<PacketC,2> cblock;
 
-        cblock.packet[0] = pload<PacketC>(&lhs(j + 0, i));
-        cblock.packet[1] = pload<PacketC>(&lhs(j + 1, i));
+        cblock.packet[0] = lhs.template loadPacket<PacketC>(j + 0, i);
+        cblock.packet[1] = lhs.template loadPacket<PacketC>(j + 1, i);
 
         blockr.packet[0] = vec_perm(cblock.packet[0].v, cblock.packet[1].v, p16uc_GETREAL64);
         blocki.packet[0] = vec_perm(cblock.packet[0].v, cblock.packet[1].v, p16uc_GETIMAG64);
@@ -1100,7 +1109,7 @@ EIGEN_STRONG_INLINE void pgerc(PacketBlock<Packet,N>* accReal, PacketBlock<Packe
 template<typename Scalar, typename Packet>
 EIGEN_STRONG_INLINE Packet ploadLhs(const Scalar* lhs)
 {
-  return *((Packet *)lhs);
+  return *reinterpret_cast<Packet *>(const_cast<Scalar *>(lhs));
 }
 
 // Zero the accumulator on PacketBlock.
@@ -1799,24 +1808,6 @@ EIGEN_STRONG_INLINE void MICRO_COMPLEX_EXTRA_COL(
   else EIGEN_UNUSED_VARIABLE(rhs_ptr_imag);
 }
 
-template<typename Scalar, typename Packetc, typename Index, const Index accCols>
-EIGEN_STRONG_INLINE void pstore_add_half(std::complex<Scalar>* to, Packetc &from)
-{
-#ifdef __VSX__
-  Packetc from2;
-#ifndef _BIG_ENDIAN
-  __asm__ ("xxswapd %x0, %x0" : : "wa" (from.v));
-#endif
-  __asm__ ("lxsdx %x0,%y1" : "=wa" (from2.v) : "Z" (*to));
-  from2 += from;
-  __asm__ ("stxsdx %x0,%y1" : : "wa" (from2.v), "Z" (*to));
-#else
-  std::complex<Scalar> mem[accColsC];
-  pstoreu<std::complex<Scalar> >(mem, from);
-  *to += *mem;
-#endif
-}
-
 template<typename Scalar, typename Packet, typename Packetc, typename DataMapper, typename Index, const Index accRows, const Index accCols, bool ConjugateLhs, bool ConjugateRhs, bool LhsIsReal, bool RhsIsReal>
 EIGEN_STRONG_INLINE void gemm_complex_extra_col(
   const DataMapper& res,
@@ -1886,12 +1877,12 @@ EIGEN_STRONG_INLINE void gemm_complex_extra_col(
 
   if ((sizeof(Scalar) == sizeof(float)) && (remaining_rows == 1))
   {
-    pstore_add_half<Scalar, Packetc, Index, accCols>(&res(row + 0, col + 0), acc0.packet[0]);
+    res(row + 0, col + 0) += pfirst<Packetc>(acc0.packet[0]);
   } else {
     acc0.packet[0] += res.template loadPacket<Packetc>(row + 0, col + 0);
     res.template storePacketBlock<Packetc,1>(row + 0, col + 0, acc0);
     if(remaining_rows > accColsC) {
-      pstore_add_half<Scalar, Packetc, Index, accCols>(&res(row + accColsC, col + 0), acc1.packet[0]);
+      res(row + accColsC, col + 0) += pfirst<Packetc>(acc1.packet[0]);
     }
   }
 }
@@ -1997,7 +1988,7 @@ asm("#gemm_complex begin");
     if ((sizeof(Scalar) == sizeof(float)) && (remaining_rows == 1))
     {
       for(Index j = 0; j < 4; j++) {
-        pstore_add_half<Scalar, Packetc, Index, accCols>(&res(row + 0, col + j), acc0.packet[j]);
+        res(row + 0, col + j) += pfirst<Packetc>(acc0.packet[j]);
       }
     } else {
       for(Index j = 0; j < 4; j++) {
@@ -2005,7 +1996,7 @@ asm("#gemm_complex begin");
         acc2.packet[0] = res.template loadPacket<Packetc>(row + 0, col + j) + acc0.packet[j];
         res.template storePacketBlock<Packetc,1>(row + 0, col + j, acc2);
         if(remaining_rows > accColsC) {
-          pstore_add_half<Scalar, Packetc, Index, accCols>(&res(row + accColsC, col + j), acc1.packet[j]);
+          res(row + accColsC, col + j) += pfirst<Packetc>(acc1.packet[j]);
         }
       }
     }

Eigen/src/Core/arch/AltiVec/MatrixProductCommon.h

@@ -214,7 +214,7 @@ EIGEN_STRONG_INLINE void bcouple_common<Packet2d, Packet1cd>(PacketBlock<Packet2
 template<typename Scalar, typename Packet>
 EIGEN_STRONG_INLINE Packet ploadRhs(const Scalar* rhs)
 {
-  return *((Packet *)rhs);
+  return *reinterpret_cast<Packet *>(const_cast<Scalar *>(rhs));
 }
 
 } // end namespace internal

Eigen/src/Core/arch/SSE/Complex.h

@@ -113,19 +113,13 @@ template<> EIGEN_STRONG_INLINE Packet2cf ploadu<Packet2cf>(const std::complex<fl
 template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>&  from)
 {
   Packet2cf res;
-#if EIGEN_GNUC_AT_MOST(4,2)
-  // Workaround annoying "may be used uninitialized in this function" warning with gcc 4.2
-  res.v = _mm_loadl_pi(_mm_set1_ps(0.0f), reinterpret_cast<const __m64*>(&from));
-#elif EIGEN_GNUC_AT_LEAST(4,6)
-  // Suppress annoying "may be used uninitialized in this function" warning with gcc >= 4.6
-  #pragma GCC diagnostic push
-  #pragma GCC diagnostic ignored "-Wuninitialized"
-  res.v = _mm_loadl_pi(res.v, (const __m64*)&from);
-  #pragma GCC diagnostic pop
+#ifdef EIGEN_VECTORIZE_SSE3
+  res.v = _mm_castpd_ps(_mm_loaddup_pd(reinterpret_cast<double const*>(&from)));
 #else
-  res.v = _mm_loadl_pi(res.v, (const __m64*)&from);
+  res.v = _mm_castpd_ps(_mm_load_sd(reinterpret_cast<double const*>(&from)));
+  res.v = _mm_movelh_ps(res.v, res.v);
 #endif
-  return Packet2cf(_mm_movelh_ps(res.v,res.v));
+  return res;
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cf ploaddup<Packet2cf>(const std::complex<float>* from) { return pset1<Packet2cf>(*from); }

Eigen/src/Core/util/Macros.h

@@ -16,8 +16,8 @@
 //------------------------------------------------------------------------------------------
 
 #define EIGEN_WORLD_VERSION 3
-#define EIGEN_MAJOR_VERSION 4
-#define EIGEN_MINOR_VERSION 99
+#define EIGEN_MAJOR_VERSION 3
+#define EIGEN_MINOR_VERSION 90
 
 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
                                       (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
@@ -684,8 +684,7 @@
 // Does the compiler support result_of?
 // result_of was deprecated in c++17 and removed in c++ 20
 #ifndef EIGEN_HAS_STD_RESULT_OF
-#if EIGEN_MAX_CPP_VER >= 11 && \
-    (defined(__cplusplus) && __cplusplus >= 201103L && __cplusplus < 201703L)
+#if EIGEN_HAS_CXX11 && EIGEN_COMP_CXXVER < 17
 #define EIGEN_HAS_STD_RESULT_OF 1
 #else
 #define EIGEN_HAS_STD_RESULT_OF 0
@@ -704,8 +703,7 @@
 #endif  // EIGEN_HAS_STD_HASH
 
 #ifndef EIGEN_HAS_STD_INVOKE_RESULT
-#if EIGEN_MAX_CPP_VER >= 17 && \
-    (defined(__cplusplus) && __cplusplus >= 201703L)
+#if EIGEN_MAX_CPP_VER >= 17 && EIGEN_COMP_CXXVER >= 17
 #define EIGEN_HAS_STD_INVOKE_RESULT 1
 #else
 #define EIGEN_HAS_STD_INVOKE_RESULT 0

Eigen/src/Core/util/XprHelper.h

@@ -136,15 +136,14 @@ template<typename T, int Value> class variable_if_dynamic
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
     operator T() const { return T(Value); }
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    void setValue(T) const {}
+    void setValue(T v) const { EIGEN_ONLY_USED_FOR_DEBUG(v); eigen_assert(v == T(Value)); }
 };
 
 template<typename T> class variable_if_dynamic<T, Dynamic>
 {
     T m_value;
-    EIGEN_DEVICE_FUNC variable_if_dynamic() { eigen_assert(false); }
   public:
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamic(T value) : m_value(value) {}
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit variable_if_dynamic(T value = 0) EIGEN_NO_THROW : m_value(value) {}
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T value() const { return m_value; }
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE operator T() const { return m_value; }
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void setValue(T value) { m_value = value; }

Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h

@@ -498,8 +498,6 @@ template<typename MatrixType, typename DiagType, typename SubDiagType>
 EIGEN_DEVICE_FUNC
 ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag, const Index maxIterations, bool computeEigenvectors, MatrixType& eivec)
 {
-  EIGEN_USING_STD(abs);
-
   ComputationInfo info;
   typedef typename MatrixType::Scalar Scalar;
 
@@ -510,15 +508,23 @@ ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag
   
   typedef typename DiagType::RealScalar RealScalar;
   const RealScalar considerAsZero = (std::numeric_limits<RealScalar>::min)();
-  const RealScalar precision = RealScalar(2)*NumTraits<RealScalar>::epsilon();
-  
+  const RealScalar precision_inv = RealScalar(1)/NumTraits<RealScalar>::epsilon();
   while (end>0)
   {
-    for (Index i = start; i<end; ++i)
-      if (internal::isMuchSmallerThan(abs(subdiag[i]),(abs(diag[i])+abs(diag[i+1])),precision) || abs(subdiag[i]) <= considerAsZero)
-        subdiag[i] = 0;
+    for (Index i = start; i<end; ++i) {
+      if (numext::abs(subdiag[i]) < considerAsZero) {
+        subdiag[i] = RealScalar(0);
+      } else {
+        // abs(subdiag[i]) <= epsilon * sqrt(abs(diag[i]) + abs(diag[i+1]))
+        // Scaled to prevent underflows.
+        const RealScalar scaled_subdiag = precision_inv * subdiag[i];
+        if (scaled_subdiag * scaled_subdiag <= (numext::abs(diag[i])+numext::abs(diag[i+1]))) {
+          subdiag[i] = RealScalar(0);
+        }
+      }
+    }
 
-    // find the largest unreduced block
+    // find the largest unreduced block at the end of the matrix.
     while (end>0 && subdiag[end-1]==RealScalar(0))
     {
       end--;
@@ -821,32 +827,38 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
 }
 
 namespace internal {
+
+// Francis implicit QR step.
 template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
 EIGEN_DEVICE_FUNC
 static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
 {
-  EIGEN_USING_STD(abs);
+  // Wilkinson Shift.
   RealScalar td = (diag[end-1] - diag[end])*RealScalar(0.5);
   RealScalar e = subdiag[end-1];
   // Note that thanks to scaling, e^2 or td^2 cannot overflow, however they can still
   // underflow thus leading to inf/NaN values when using the following commented code:
-//   RealScalar e2 = numext::abs2(subdiag[end-1]);
-//   RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * sqrt(td*td + e2));
+  //   RealScalar e2 = numext::abs2(subdiag[end-1]);
+  //   RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * sqrt(td*td + e2));
   // This explain the following, somewhat more complicated, version:
   RealScalar mu = diag[end];
-  if(td==RealScalar(0))
-    mu -= abs(e);
-  else
-  {
-    RealScalar e2 = numext::abs2(subdiag[end-1]);
-    RealScalar h = numext::hypot(td,e);
-    if(e2==RealScalar(0)) mu -= (e / (td + (td>RealScalar(0) ? RealScalar(1) : RealScalar(-1)))) * (e / h);
-    else                  mu -= e2 / (td + (td>RealScalar(0) ? h : -h));
+  if(td==RealScalar(0)) {
+    mu -= numext::abs(e);
+  } else if (e != RealScalar(0)) {
+    const RealScalar e2 = numext::abs2(e);
+    const RealScalar h = numext::hypot(td,e);
+    if(e2 == RealScalar(0)) {
+      mu -= e / ((td + (td>RealScalar(0) ? h : -h)) / e);
+    } else {
+      mu -= e2 / (td + (td>RealScalar(0) ? h : -h)); 
+    }
   }
-  
+
   RealScalar x = diag[start] - mu;
   RealScalar z = subdiag[start];
-  for (Index k = start; k < end; ++k)
+  // If z ever becomes zero, the Givens rotation will be the identity and
+  // z will stay zero for all future iterations.
+  for (Index k = start; k < end && z != RealScalar(0); ++k)
   {
     JacobiRotation<RealScalar> rot;
     rot.makeGivens(x, z);
@@ -859,12 +871,11 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta
     diag[k+1] = rot.s() * sdk + rot.c() * dkp1;
     subdiag[k] = rot.c() * sdk - rot.s() * dkp1;
     
-
     if (k > start)
       subdiag[k - 1] = rot.c() * subdiag[k-1] - rot.s() * z;
 
+    // "Chasing the bulge" to return to triangular form.
     x = subdiag[k];
-
     if (k < end - 1)
     {
       z = -rot.s() * subdiag[k+1];

Eigen/src/LU/arch/InverseSize4.h

@@ -141,8 +141,8 @@ struct compute_inverse_size4<Architecture::Target, float, MatrixType, ResultType
     iC = psub(iC, pmul(vec4f_swizzle2(A, A, 1, 0, 3, 2), vec4f_swizzle2(DC, DC, 2, 1, 2, 1)));
     iC = psub(pmul(B, vec4f_duplane(dC, 0)), iC);
 
-    const int bits[4] = {0, -2147483648, -2147483648, 0};
-    const Packet4f p4f_sign_PNNP = preinterpret<Packet4f, Packet4i>(pgather<int, Packet4i>(bits, static_cast<Eigen::Index>(1)));
+    const float sign_mask[4] = {0.0f, -0.0f, -0.0f, 0.0f};
+    const Packet4f p4f_sign_PNNP = pset<Packet4f>(sign_mask);
     rd = pxor(rd, p4f_sign_PNNP);
     iA = pmul(iA, rd);
     iB = pmul(iB, rd);
@@ -323,12 +323,12 @@ struct compute_inverse_size4<Architecture::Target, double, MatrixType, ResultTyp
     iC1 = psub(pmul(B1, dC), iC1);
     iC2 = psub(pmul(B2, dC), iC2);
 
-    const int bits1[4] = {0, -2147483648, 0, 0};
-    const int bits2[4] = {0, 0, 0, -2147483648};
-    const Packet2d _Sign_NP = preinterpret<Packet2d, Packet4i>(pgather<int, Packet4i>(bits1, static_cast<Eigen::Index>(1)));
-    const Packet2d _Sign_PN = preinterpret<Packet2d, Packet4i>(pgather<int, Packet4i>(bits2, static_cast<Eigen::Index>(1)));
-    d1 = pxor(rd, _Sign_PN);
-    d2 = pxor(rd, _Sign_NP);
+    const double sign_mask1[2] = {0.0, -0.0};
+    const double sign_mask2[2] = {-0.0, 0.0};
+    const Packet2d sign_PN = pset<Packet2d>(sign_mask1);
+    const Packet2d sign_NP = pset<Packet2d>(sign_mask2);
+    d1 = pxor(rd, sign_PN);
+    d2 = pxor(rd, sign_NP);
 
     Index res_stride = result.outerStride();
     double *res = result.data();

Eigen/src/SVD/BDCSVD.h

@@ -208,6 +208,7 @@ protected:
   using Base::m_computeThinV;
   using Base::m_matrixU;
   using Base::m_matrixV;
+  using Base::m_info;
   using Base::m_isInitialized;
   using Base::m_nonzeroSingularValues;
 
@@ -256,16 +257,25 @@ BDCSVD<MatrixType>& BDCSVD<MatrixType>::compute(const MatrixType& matrix, unsign
   {
     // FIXME this line involves temporaries
     JacobiSVD<MatrixType> jsvd(matrix,computationOptions);
-    if(computeU()) m_matrixU = jsvd.matrixU();
-    if(computeV()) m_matrixV = jsvd.matrixV();
-    m_singularValues = jsvd.singularValues();
-    m_nonzeroSingularValues = jsvd.nonzeroSingularValues();
     m_isInitialized = true;
+    m_info = jsvd.info();
+    if (m_info == Success || m_info == NoConvergence) {
+      if(computeU()) m_matrixU = jsvd.matrixU();
+      if(computeV()) m_matrixV = jsvd.matrixV();
+      m_singularValues = jsvd.singularValues();
+      m_nonzeroSingularValues = jsvd.nonzeroSingularValues();
+    }
     return *this;
   }
   
   //**** step 0 - Copy the input matrix and apply scaling to reduce over/under-flows
-  RealScalar scale = matrix.cwiseAbs().maxCoeff();
+  RealScalar scale = matrix.cwiseAbs().template maxCoeff<PropagateNaN>();
+  if (!(numext::isfinite)(scale)) {
+    m_isInitialized = true;
+    m_info = InvalidInput;
+    return *this;
+  }
+
   if(scale==Literal(0)) scale = Literal(1);
   MatrixX copy;
   if (m_isTranspose) copy = matrix.adjoint()/scale;
@@ -282,7 +292,11 @@ BDCSVD<MatrixType>& BDCSVD<MatrixType>::compute(const MatrixType& matrix, unsign
   m_computed.topRows(m_diagSize) = bid.bidiagonal().toDenseMatrix().transpose();
   m_computed.template bottomRows<1>().setZero();
   divide(0, m_diagSize - 1, 0, 0, 0);
-
+  if (m_info != Success && m_info != NoConvergence) {
+    m_isInitialized = true;
+    return *this;
+  }
+    
   //**** step 3 - Copy singular values and vectors
   for (int i=0; i<m_diagSize; i++)
   {
@@ -394,7 +408,7 @@ void BDCSVD<MatrixType>::structured_update(Block<MatrixXr,Dynamic,Dynamic> A, co
 //@param shift : Each time one takes the left submatrix, one must add 1 to the shift. Why? Because! We actually want the last column of the U submatrix 
 // to become the first column (*coeff) and to shift all the other columns to the right. There are more details on the reference paper.
 template<typename MatrixType>
-void BDCSVD<MatrixType>::divide (Eigen::Index firstCol, Eigen::Index lastCol, Eigen::Index firstRowW, Eigen::Index firstColW, Eigen::Index shift)
+void BDCSVD<MatrixType>::divide(Eigen::Index firstCol, Eigen::Index lastCol, Eigen::Index firstRowW, Eigen::Index firstColW, Eigen::Index shift)
 {
   // requires rows = cols + 1;
   using std::pow;
@@ -414,6 +428,8 @@ void BDCSVD<MatrixType>::divide (Eigen::Index firstCol, Eigen::Index lastCol, Ei
   {
     // FIXME this line involves temporaries
     JacobiSVD<MatrixXr> b(m_computed.block(firstCol, firstCol, n + 1, n), ComputeFullU | (m_compV ? ComputeFullV : 0));
+    m_info = b.info();
+    if (m_info != Success && m_info != NoConvergence) return;
     if (m_compU)
       m_naiveU.block(firstCol, firstCol, n + 1, n + 1).real() = b.matrixU();
     else 
@@ -433,7 +449,9 @@ void BDCSVD<MatrixType>::divide (Eigen::Index firstCol, Eigen::Index lastCol, Ei
   // and the divide of the right submatrice reads one column of the left submatrice. That's why we need to treat the 
   // right submatrix before the left one. 
   divide(k + 1 + firstCol, lastCol, k + 1 + firstRowW, k + 1 + firstColW, shift);
+  if (m_info != Success && m_info != NoConvergence) return;
   divide(firstCol, k - 1 + firstCol, firstRowW, firstColW + 1, shift + 1);
+  if (m_info != Success && m_info != NoConvergence) return;
 
   if (m_compU)
   {

Eigen/src/SVD/JacobiSVD.h

@@ -585,6 +585,7 @@ template<typename _MatrixType, int QRPreconditioner> class JacobiSVD
     using Base::m_matrixU;
     using Base::m_matrixV;
     using Base::m_singularValues;
+    using Base::m_info;
     using Base::m_isInitialized;
     using Base::m_isAllocated;
     using Base::m_usePrescribedThreshold;
@@ -625,6 +626,7 @@ void JacobiSVD<MatrixType, QRPreconditioner>::allocate(Eigen::Index rows, Eigen:
 
   m_rows = rows;
   m_cols = cols;
+  m_info = Success;
   m_isInitialized = false;
   m_isAllocated = true;
   m_computationOptions = computationOptions;
@@ -674,7 +676,12 @@ JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsig
   const RealScalar considerAsZero = (std::numeric_limits<RealScalar>::min)();
 
   // Scaling factor to reduce over/under-flows
-  RealScalar scale = matrix.cwiseAbs().maxCoeff();
+  RealScalar scale = matrix.cwiseAbs().template maxCoeff<PropagateNaN>();
+  if (!(numext::isfinite)(scale)) {
+    m_isInitialized = true;
+    m_info = InvalidInput;
+    return *this;
+  }
   if(scale==RealScalar(0)) scale = RealScalar(1);
   
   /*** step 1. The R-SVD step: we use a QR decomposition to reduce to the case of a square matrix */

Eigen/src/SVD/SVDBase.h

@@ -51,8 +51,11 @@ template<typename Derived> struct traits<SVDBase<Derived> >
  * smaller value among \a n and \a p, there are only \a m singular vectors; the remaining columns of \a U and \a V do not correspond to actual
  * singular vectors. Asking for \em thin \a U or \a V means asking for only their \a m first columns to be formed. So \a U is then a n-by-m matrix,
  * and \a V is then a p-by-m matrix. Notice that thin \a U and \a V are all you need for (least squares) solving.
+ * 
+ * The status of the computation can be retrived using the \a info() method. Unless \a info() returns \a Success, the results should be not
+ * considered well defined.
  *  
- * If the input matrix has inf or nan coefficients, the result of the computation is undefined, but the computation is guaranteed to
+ * If the input matrix has inf or nan coefficients, the result of the computation is undefined, and \a info() will return \a InvalidInput, but the computation is guaranteed to
  * terminate in finite (and reasonable) time.
  * \sa class BDCSVD, class JacobiSVD
  */
@@ -97,7 +100,7 @@ public:
    */
   const MatrixUType& matrixU() const
   {
-    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    _check_compute_assertions();
     eigen_assert(computeU() && "This SVD decomposition didn't compute U. Did you ask for it?");
     return m_matrixU;
   }
@@ -113,7 +116,7 @@ public:
    */
   const MatrixVType& matrixV() const
   {
-    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    _check_compute_assertions();
     eigen_assert(computeV() && "This SVD decomposition didn't compute V. Did you ask for it?");
     return m_matrixV;
   }
@@ -125,14 +128,14 @@ public:
    */
   const SingularValuesType& singularValues() const
   {
-    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    _check_compute_assertions();
     return m_singularValues;
   }
 
   /** \returns the number of singular values that are not exactly 0 */
   Index nonzeroSingularValues() const
   {
-    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    _check_compute_assertions();
     return m_nonzeroSingularValues;
   }
   
@@ -145,7 +148,7 @@ public:
   inline Index rank() const
   {
     using std::abs;
-    eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
+    _check_compute_assertions();
     if(m_singularValues.size()==0) return 0;
     RealScalar premultiplied_threshold = numext::maxi<RealScalar>(m_singularValues.coeff(0) * threshold(), (std::numeric_limits<RealScalar>::min)());
     Index i = m_nonzeroSingularValues-1;
@@ -224,6 +227,18 @@ public:
   solve(const MatrixBase<Rhs>& b) const;
   #endif
 
+
+  /** \brief Reports whether previous computation was successful.
+   *
+   * \returns \c Success if computation was successful.
+   */
+  EIGEN_DEVICE_FUNC
+  ComputationInfo info() const
+  {
+    eigen_assert(m_isInitialized && "SVD is not initialized.");
+    return m_info;
+  }
+
   #ifndef EIGEN_PARSED_BY_DOXYGEN
   template<typename RhsType, typename DstType>
   void _solve_impl(const RhsType &rhs, DstType &dst) const;
@@ -233,26 +248,31 @@ public:
   #endif
 
 protected:
-  
+
   static void check_template_parameters()
   {
     EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
   }
 
+  void _check_compute_assertions() const {
+    eigen_assert(m_isInitialized && "SVD is not initialized.");
+  }
+
   template<bool Transpose_, typename Rhs>
   void _check_solve_assertion(const Rhs& b) const {
       EIGEN_ONLY_USED_FOR_DEBUG(b);
-      eigen_assert(m_isInitialized && "SVD is not initialized.");
+      _check_compute_assertions();
       eigen_assert(computeU() && computeV() && "SVDBase::solve(): Both unitaries U and V are required to be computed (thin unitaries suffice).");
       eigen_assert((Transpose_?cols():rows())==b.rows() && "SVDBase::solve(): invalid number of rows of the right hand side matrix b");
   }
-  
+
   // return true if already allocated
   bool allocate(Index rows, Index cols, unsigned int computationOptions) ;
 
   MatrixUType m_matrixU;
   MatrixVType m_matrixV;
   SingularValuesType m_singularValues;
+  ComputationInfo m_info;
   bool m_isInitialized, m_isAllocated, m_usePrescribedThreshold;
   bool m_computeFullU, m_computeThinU;
   bool m_computeFullV, m_computeThinV;
@@ -265,7 +285,8 @@ protected:
    * Default constructor of SVDBase
    */
   SVDBase()
-    : m_isInitialized(false),
+    : m_info(Success),
+      m_isInitialized(false),
       m_isAllocated(false),
       m_usePrescribedThreshold(false),
       m_computeFullU(false),
@@ -327,6 +348,7 @@ bool SVDBase<MatrixType>::allocate(Index rows, Index cols, unsigned int computat
 
   m_rows = rows;
   m_cols = cols;
+  m_info = Success;
   m_isInitialized = false;
   m_isAllocated = true;
   m_computationOptions = computationOptions;

bench/sparse_randomsetter.cpp

@@ -1,6 +1,7 @@
 
 #define NOGMM
 #define NOMTL
+#define EIGEN_GOOGLEHASH_SUPPORT 1
 
 #include <map>
 #include <ext/hash_map>

ci/smoketests.gitlab-ci.yml

@@ -0,0 +1,107 @@
+.buildsmoketests:linux:base:
+  stage: buildsmoketests
+  image: ubuntu:18.04
+  before_script:
+    - apt-get update -y
+    - apt-get install -y --no-install-recommends software-properties-common
+    - add-apt-repository -y  ppa:ubuntu-toolchain-r/test
+    - apt-get update
+    - apt-get install --no-install-recommends -y ${EIGEN_CI_CXX_COMPILER}
+      ${EIGEN_CI_CC_COMPILER} cmake ninja-build
+  script:
+    - mkdir -p ${BUILDDIR} && cd ${BUILDDIR}
+    - CXX=${EIGEN_CI_CXX_COMPILER} CC=${EIGEN_CI_CC_COMPILER} cmake -G
+      ${EIGEN_CI_CMAKE_GENEATOR} -DEIGEN_TEST_CXX11=${EIGEN_TEST_CXX11}
+      ${EIGEN_CI_ADDITIONAL_ARGS} ..
+    - cmake --build . --target buildsmoketests
+  artifacts:
+    name: "$CI_JOB_NAME-$CI_COMMIT_REF_NAME"
+    paths:
+      - ${BUILDDIR}/
+    expire_in: 5 days
+  only:
+    - merge_requests
+
+buildsmoketests:x86-64:linux:gcc-10:cxx11-off:
+  extends: .buildsmoketests:linux:base
+  variables:
+    EIGEN_CI_CXX_COMPILER: "g++-10"
+    EIGEN_CI_CC_COMPILER: "gcc-10"
+    EIGEN_TEST_CXX11: "off"
+
+buildsmoketests:x86-64:linux:gcc-10:cxx11-on:
+  extends: .buildsmoketests:linux:base
+  variables:
+    EIGEN_CI_CXX_COMPILER: "g++-10"
+    EIGEN_CI_CC_COMPILER: "gcc-10"
+    EIGEN_TEST_CXX11: "on"
+
+buildsmoketests:x86-64:linux:clang-10:cxx11-off:
+  extends: .buildsmoketests:linux:base
+  variables:
+    EIGEN_CI_CXX_COMPILER: "clang++-10"
+    EIGEN_CI_CC_COMPILER: "clang-10"
+    EIGEN_TEST_CXX11: "off"
+
+buildsmoketests:x86-64:linux:clang-10:cxx11-on:
+  extends: .buildsmoketests:linux:base
+  variables:
+    EIGEN_CI_CXX_COMPILER: "clang++-10"
+    EIGEN_CI_CC_COMPILER: "clang-10"
+    EIGEN_TEST_CXX11: "on"
+
+.smoketests:linux:base:
+  stage: smoketests
+  image: ubuntu:18.04
+  before_script:
+    - apt-get update -y
+    - apt-get install -y --no-install-recommends software-properties-common
+    - add-apt-repository -y ppa:ubuntu-toolchain-r/test
+    - apt-get update
+    - apt-get install --no-install-recommends -y ${EIGEN_CI_CXX_COMPILER}
+      ${EIGEN_CI_CC_COMPILER} cmake ninja-build xsltproc
+  script:
+    - export CXX=${EIGEN_CI_CXX_COMPILER}
+    - export CC=${EIGEN_CI_CC_COMPILER}
+    - cd ${BUILDDIR} && ctest --output-on-failure --no-compress-output
+      --build-no-clean -T test -L smoketest
+  after_script:
+    - apt-get update -y
+    - apt-get install --no-install-recommends -y xsltproc
+    - cd ${BUILDDIR}
+    - xsltproc ../ci/CTest2JUnit.xsl Testing/`head -n 1 < Testing/TAG`/Test.xml > "JUnitTestResults_$CI_JOB_ID.xml"
+  artifacts:
+    reports:
+      junit:
+        - ${BUILDDIR}/JUnitTestResults_$CI_JOB_ID.xml
+    expire_in: 5 days
+  only:
+    - merge_requests
+
+smoketests:x86-64:linux:gcc-10:cxx11-off:
+  extends: .smoketests:linux:base
+  variables:
+    EIGEN_CI_CXX_COMPILER: g++-10
+    EIGEN_CI_CC_COMPILER: gcc-10
+  needs: [ "buildsmoketests:x86-64:linux:gcc-10:cxx11-off" ]
+
+smoketests:x86-64:linux:gcc-10:cxx11-on:
+  extends: .smoketests:linux:base
+  variables:
+    EIGEN_CI_CXX_COMPILER: g++-10
+    EIGEN_CI_CC_COMPILER: gcc-10
+  needs: [ "buildsmoketests:x86-64:linux:gcc-10:cxx11-on" ]
+
+smoketests:x86-64:linux:clang-10:cxx11-off:
+  extends: .smoketests:linux:base
+  variables:
+    EIGEN_CI_CXX_COMPILER: clang++-10
+    EIGEN_CI_CC_COMPILER: clang-10
+  needs: [ "buildsmoketests:x86-64:linux:clang-10:cxx11-off" ]
+
+smoketests:x86-64:linux:clang-10:cxx11-on:
+  extends: .smoketests:linux:base
+  variables:
+    EIGEN_CI_CXX_COMPILER: clang++-10
+    EIGEN_CI_CC_COMPILER: clang-10
+  needs: [ "buildsmoketests:x86-64:linux:clang-10:cxx11-on" ]

cmake/EigenSmokeTestList.cmake

@@ -0,0 +1,131 @@
+# List of tests that will be build and run during Eigen's smoke testing. If one
+# of these tests doesn't exists or cannot be build with the current configuration
+# it will just be skipped.
+set(ei_smoke_test_list
+  adjoint_1
+  alignedvector3
+  array_cwise_7
+  array_cwise_8
+  array_for_matrix_1
+  array_of_string
+  array_replicate_1
+  array_reverse_1
+  autodiff_1
+  autodiff_scalar_1
+  bandmatrix
+  bdcsvd_9
+  bessel_functions_1
+  bfloat16_float
+  blasutil_1
+  block_5
+  BVH
+  cholesky_1
+  cholmod_support_23
+  cholmod_support_24
+  conservative_resize_1
+  constructor_1
+  corners_1
+  ctorleakmiscmatrices_4
+  dense_storage
+  determinant_1
+  diagonal_1
+  diagonal_2
+  diagonalmatrices_1
+  dynalloc
+  eigensolver_complex_1
+  eigensolver_selfadjoint_8
+  EulerAngles_1
+  exceptions
+  fastmath
+  first_aligned
+  geo_alignedbox_2
+  geo_eulerangles_1
+  geo_homogeneous_1
+  geo_hyperplane_1
+  geo_orthomethods_1
+  geo_parametrizedline_1
+  geo_transformations_7
+  half_float
+  hessenberg_1
+  hessenberg_6qr_10
+  householder_8
+  indexed_view_1
+  inplace_decomposition_1
+  integer_types_1
+  inverse_1
+  is_same_dense
+  jacobi_1
+  jacobisvd_1
+  kronecker_product
+  linearstructure_1
+  mapped_matrix_1
+  mapstaticmethods_1
+  mapstride_1
+  matrix_square_root_1
+  meta
+  minres_2
+  miscmatrices_1
+  mixingtypes_7
+  nestbyvalue
+  nesting_ops_1
+  nomalloc_1
+  nullary_1
+  num_dimensions
+  NumericalDiff
+  numext
+  packetmath
+  permutationmatrices_1
+  polynomialsolver_1
+  prec_inverse_4x4_1
+  product_extra_5
+  product_selfadjoint_1
+  product_small_7
+  product_symm_1
+  product_syrk_1
+  product_trmm_1
+  product_trmv_1
+  product_trsolve_5
+  qr_1
+  qr_colpivoting_7
+  qr_fullpivoting_4
+  rand
+  real_qz_1
+  redux_1
+  ref_1
+  resize
+  rvalue_types_1
+  schur_complex_1
+  schur_real_1
+  selfadjoint_1
+  sizeof
+  sizeoverflow
+  smallvectors
+  sparse_basic_3
+  sparse_block_1
+  sparse_extra_4
+  sparse_permutations_2
+  sparse_product_4
+  sparse_ref_1
+  sparse_solvers_1
+  sparse_vector_1
+  special_functions_1
+  special_numbers_1
+  special_packetmath_1
+  spqr_support_2
+  stable_norm_1
+  stddeque_1
+  stddeque_overload_1
+  stdlist_1
+  stdlist_overload_1
+  stdvector_1
+  stdvector_overload_1
+  stl_iterators_1
+  swap_1
+  symbolic_index_1
+  triangular_1
+  type_aliaslu_9
+  umeyama_3
+  unalignedassert
+  unalignedcount
+  vectorwiseop_1
+  visitor_1)

cmake/EigenTesting.cmake

@@ -18,6 +18,11 @@ macro(ei_add_test_internal testname testname_with_suffix)
     set(filename ${testname}.cpp)
   endif()
 
+  # Add the current target to the list of subtest targets
+  get_property(EIGEN_SUBTESTS_LIST GLOBAL PROPERTY EIGEN_SUBTESTS_LIST)
+  set(EIGEN_SUBTESTS_LIST "${EIGEN_SUBTESTS_LIST}${targetname}\n")
+  set_property(GLOBAL PROPERTY EIGEN_SUBTESTS_LIST "${EIGEN_SUBTESTS_LIST}")
+
   if(EIGEN_ADD_TEST_FILENAME_EXTENSION STREQUAL cu)
     if(EIGEN_TEST_HIP)
       hip_reset_flags()
@@ -413,11 +418,13 @@ macro(ei_init_testing)
   define_property(GLOBAL PROPERTY EIGEN_MISSING_BACKENDS BRIEF_DOCS " " FULL_DOCS " ")
   define_property(GLOBAL PROPERTY EIGEN_TESTING_SUMMARY BRIEF_DOCS " " FULL_DOCS " ")
   define_property(GLOBAL PROPERTY EIGEN_TESTS_LIST BRIEF_DOCS " " FULL_DOCS " ")
+  define_property(GLOBAL PROPERTY EIGEN_SUBTESTS_LIST BRIEF_DOCS " " FULL_DOCS " ")
 
   set_property(GLOBAL PROPERTY EIGEN_TESTED_BACKENDS "")
   set_property(GLOBAL PROPERTY EIGEN_MISSING_BACKENDS "")
   set_property(GLOBAL PROPERTY EIGEN_TESTING_SUMMARY "")
   set_property(GLOBAL PROPERTY EIGEN_TESTS_LIST "")
+  set_property(GLOBAL PROPERTY EIGEN_SUBTESTS_LIST "")
 
   define_property(GLOBAL PROPERTY EIGEN_FAILTEST_FAILURE_COUNT BRIEF_DOCS " " FULL_DOCS " ")
   define_property(GLOBAL PROPERTY EIGEN_FAILTEST_COUNT BRIEF_DOCS " " FULL_DOCS " ")
@@ -708,3 +715,56 @@ macro(ei_split_testsuite num_splits)
     add_dependencies("${current_target}" "${curr_test}")
   endforeach()
 endmacro(ei_split_testsuite num_splits)
+
+# Defines the custom command buildsmoketests to build a number of tests
+# specified in smoke_test_list.
+# 
+# Test in smoke_test_list can be either test targets (e.g. packetmath) or
+# subtests targets (e.g. packetmath_2). If any of the test are not available
+# in the current configuration they are just skipped. 
+#
+# All tests added via this macro are labeled with the smoketest label. This
+# allows running smoketests only using ctest.
+#
+# Smoke tests are intended to be run before the whole test suite is invoked,
+# e.g., to smoke test patches.
+macro(ei_add_smoke_tests smoke_test_list)
+  # Set the build target to build smoketests
+  set(buildtarget "buildsmoketests")
+  add_custom_target("${buildtarget}")
+
+  # Get list of all tests and translate it into a CMake list
+  get_property(EIGEN_TESTS_LIST GLOBAL PROPERTY EIGEN_TESTS_LIST)
+  string(REGEX REPLACE "\n" " " EIGEN_TESTS_LIST "${EIGEN_TESTS_LIST}")
+  set(EIGEN_TESTS_LIST "${EIGEN_TESTS_LIST}")
+  separate_arguments(EIGEN_TESTS_LIST)
+
+  # Check if the test in smoke_test_list is a currently valid test target
+  foreach(test IN ITEMS ${smoke_test_list})
+    # Add tests in smoke_test_list to our smoke test target but only if the test
+    # is currently available, i.e., is in EIGEN_SUBTESTS_LIST
+    if ("${test}" IN_LIST EIGEN_TESTS_LIST)
+      add_dependencies("${buildtarget}" "${test}")
+      # In the case of a test we match all subtests
+      set(ctest_regex "${ctest_regex}^${test}_[0-9]+$$|")
+    endif()
+  endforeach()
+
+  # Get list of all subtests and translate it into a CMake list
+  get_property(EIGEN_SUBTESTS_LIST GLOBAL PROPERTY EIGEN_SUBTESTS_LIST)
+  string(REGEX REPLACE "\n" " " EIGEN_SUBTESTS_LIST "${EIGEN_SUBTESTS_LIST}")
+  set(EIGEN_SUBTESTS_LIST "${EIGEN_SUBTESTS_LIST}")
+  separate_arguments(EIGEN_SUBTESTS_LIST)
+
+  # Check if the test in smoke_test_list is a currently valid subtest target
+  foreach(test IN ITEMS ${smoke_test_list})
+    # Add tests in smoke_test_list to our smoke test target but only if the test
+    # is currently available, i.e., is in EIGEN_SUBTESTS_LIST
+    if ("${test}" IN_LIST EIGEN_SUBTESTS_LIST)
+      add_dependencies("${buildtarget}" "${test}")
+      # Add label smoketest to be able to run smoketests using ctest
+      get_property(test_labels TEST ${test} PROPERTY LABELS)
+      set_property(TEST ${test} PROPERTY LABELS "${test_labels};smoketest")
+    endif()
+  endforeach()
+endmacro(ei_add_smoke_tests)

test/AnnoyingScalar.h

@@ -76,20 +76,20 @@ class AnnoyingScalar
 
     AnnoyingScalar operator/(const AnnoyingScalar& other) const
     { return AnnoyingScalar((*v)/(*other.v)); }
-    
+
     AnnoyingScalar& operator+=(const AnnoyingScalar& other) { *v += *other.v; return *this; }
     AnnoyingScalar& operator-=(const AnnoyingScalar& other) { *v -= *other.v; return *this; }
     AnnoyingScalar& operator*=(const AnnoyingScalar& other) { *v *= *other.v; return *this; }
     AnnoyingScalar& operator/=(const AnnoyingScalar& other) { *v /= *other.v; return *this; }
     AnnoyingScalar& operator= (const AnnoyingScalar& other) { *v  = *other.v; return *this; }
-  
+
     bool operator==(const AnnoyingScalar& other) const { return *v == *other.v; }
     bool operator!=(const AnnoyingScalar& other) const { return *v != *other.v; }
     bool operator<=(const AnnoyingScalar& other) const { return *v <= *other.v; }
     bool operator< (const AnnoyingScalar& other) const { return *v <  *other.v; }
     bool operator>=(const AnnoyingScalar& other) const { return *v >= *other.v; }
     bool operator> (const AnnoyingScalar& other) const { return *v >  *other.v; }
-    
+  
     float* v;
     float data;
     static int instances;
@@ -136,12 +136,23 @@ struct NumTraits<AnnoyingScalar> : NumTraits<float>
 
 template<> inline AnnoyingScalar test_precision<AnnoyingScalar>() { return test_precision<float>(); }
 
-namespace internal {
-  template<> double cast(const AnnoyingScalar& x) { return double(*x.v); }
-  template<> float  cast(const AnnoyingScalar& x) { return *x.v; }
+namespace numext {
+template<>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
+bool (isfinite)(const AnnoyingScalar& x) {
+  return (numext::isfinite)(*x.v);
+}
 }
 
+namespace internal {
+  template<> EIGEN_STRONG_INLINE AnnoyingScalar pcmp_eq(const AnnoyingScalar& a, const AnnoyingScalar& b)
+  { return AnnoyingScalar(pcmp_eq(*a.v, *b.v)); }
+  template<> EIGEN_STRONG_INLINE AnnoyingScalar pselect(const AnnoyingScalar& mask, const AnnoyingScalar& a, const AnnoyingScalar& b)
+  { return numext::equal_strict(*mask.v, 0.f) ? b : a; }
+  template<> EIGEN_STRONG_INLINE double cast(const AnnoyingScalar& x) { return double(*x.v); }
+  template<> EIGEN_STRONG_INLINE float  cast(const AnnoyingScalar& x) { return *x.v; }
 }
+}  // namespace Eigen
 
 AnnoyingScalar get_test_precision(const AnnoyingScalar&)
 { return Eigen::test_precision<AnnoyingScalar>(); }

test/CMakeLists.txt

@@ -460,3 +460,7 @@ cmake_dependent_option(EIGEN_TEST_BUILD_DOCUMENTATION "Test building the doxygen
 if(EIGEN_TEST_BUILD_DOCUMENTATION)
   add_dependencies(buildtests doc)
 endif()
+
+# Register all smoke tests
+include("EigenSmokeTestList")
+ei_add_smoke_tests("${ei_smoke_test_list}")

test/geo_quaternion.cpp

@@ -332,7 +332,9 @@ EIGEN_DECLARE_TEST(geo_quaternion)
     CALL_SUBTEST_2(( quaternionAlignment<double>() ));
     CALL_SUBTEST_2( mapQuaternion<double>() );
 
+#ifndef EIGEN_TEST_ANNOYING_SCALAR_DONT_THROW
     AnnoyingScalar::dont_throw = true;
+#endif
     CALL_SUBTEST_3(( quaternion<AnnoyingScalar,AutoAlign>() ));
   }
 }

test/sparse.h

@@ -29,10 +29,6 @@
 
 #endif
 
-#ifdef EIGEN_GOOGLEHASH_SUPPORT
-  #include <google/sparse_hash_map>
-#endif
-
 #include <Eigen/Cholesky>
 #include <Eigen/LU>
 #include <Eigen/Sparse>

test/stl_iterators.cpp

@@ -7,9 +7,9 @@
 // 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 <iterator>
 #include <numeric>
-#include "main.h"
 
 template< class Iterator >
 std::reverse_iterator<Iterator>
@@ -47,6 +47,18 @@ bool is_pointer_based_stl_iterator(const internal::pointer_based_stl_iterator<Xp
 template<typename XprType>
 bool is_generic_randaccess_stl_iterator(const internal::generic_randaccess_stl_iterator<XprType> &) { return true; }
 
+template<typename Iter>
+bool is_default_constructible_and_assignable(const Iter& it)
+{
+#if EIGEN_HAS_CXX11
+  VERIFY(std::is_default_constructible<Iter>::value);
+  VERIFY(std::is_nothrow_default_constructible<Iter>::value);
+#endif
+  Iter it2;
+  it2 = it;
+  return (it==it2);
+}
+
 template<typename Xpr>
 void check_begin_end_for_loop(Xpr xpr)
 {
@@ -124,6 +136,22 @@ void test_stl_iterators(int rows=Rows, int cols=Cols)
   
   Index i, j;
 
+  // Verify that iterators are default constructible (See bug #1900)
+  {
+    VERIFY( is_default_constructible_and_assignable(v.begin()));
+    VERIFY( is_default_constructible_and_assignable(v.end()));
+    VERIFY( is_default_constructible_and_assignable(cv.begin()));
+    VERIFY( is_default_constructible_and_assignable(cv.end()));
+
+    VERIFY( is_default_constructible_and_assignable(A.row(0).begin()));
+    VERIFY( is_default_constructible_and_assignable(A.row(0).end()));
+    VERIFY( is_default_constructible_and_assignable(cA.row(0).begin()));
+    VERIFY( is_default_constructible_and_assignable(cA.row(0).end()));
+
+    VERIFY( is_default_constructible_and_assignable(B.row(0).begin()));
+    VERIFY( is_default_constructible_and_assignable(B.row(0).end()));
+  }
+
   // Check we got a fast pointer-based iterator when expected
   {
     VERIFY( is_pointer_based_stl_iterator(v.begin()) );

test/svd_common.h

@@ -298,7 +298,8 @@ EIGEN_DONT_INLINE Scalar zero() { return Scalar(0); }
 // workaround aggressive optimization in ICC
 template<typename T> EIGEN_DONT_INLINE  T sub(T a, T b) { return a - b; }
 
-// all this function does is verify we don't iterate infinitely on nan/inf values
+// This function verifies we don't iterate infinitely on nan/inf values,
+// and that info() returns InvalidInput.
 template<typename SvdType, typename MatrixType>
 void svd_inf_nan()
 {
@@ -307,18 +308,22 @@ void svd_inf_nan()
   Scalar some_inf = Scalar(1) / zero<Scalar>();
   VERIFY(sub(some_inf, some_inf) != sub(some_inf, some_inf));
   svd.compute(MatrixType::Constant(10,10,some_inf), ComputeFullU | ComputeFullV);
+  VERIFY(svd.info() == InvalidInput);
 
   Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
   VERIFY(nan != nan);
   svd.compute(MatrixType::Constant(10,10,nan), ComputeFullU | ComputeFullV);
+  VERIFY(svd.info() == InvalidInput);  
 
   MatrixType m = MatrixType::Zero(10,10);
   m(internal::random<int>(0,9), internal::random<int>(0,9)) = some_inf;
   svd.compute(m, ComputeFullU | ComputeFullV);
+  VERIFY(svd.info() == InvalidInput);
 
   m = MatrixType::Zero(10,10);
   m(internal::random<int>(0,9), internal::random<int>(0,9)) = nan;
   svd.compute(m, ComputeFullU | ComputeFullV);
+  VERIFY(svd.info() == InvalidInput);
   
   // regression test for bug 791
   m.resize(3,3);
@@ -326,6 +331,7 @@ void svd_inf_nan()
        0,   -0.5,                             0,
        nan,  0,                               0;
   svd.compute(m, ComputeFullU | ComputeFullV);
+  VERIFY(svd.info() == InvalidInput);
   
   m.resize(4,4);
   m <<  1, 0, 0, 0,
@@ -333,6 +339,7 @@ void svd_inf_nan()
         1, 0, 1, nan,
         0, nan, nan, 0;
   svd.compute(m, ComputeFullU | ComputeFullV);
+  VERIFY(svd.info() == InvalidInput);
 }
 
 // Regression test for bug 286: JacobiSVD loops indefinitely with some

unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h

@@ -466,7 +466,7 @@ struct sizes_match_below_dim {
 template <typename Dims1, typename Dims2, ptrdiff_t n>
 struct sizes_match_below_dim<Dims1, Dims2, n, n> {
   static EIGEN_DEVICE_FUNC  EIGEN_STRONG_INLINE bool run(Dims1& dims1, Dims2& dims2) {
-    return (array_get<n-1>(dims1) == array_get<n-1>(dims2)) &
+    return (array_get<n-1>(dims1) == array_get<n-1>(dims2)) &&
         sizes_match_below_dim<Dims1, Dims2, n-1, n-1>::run(dims1, dims2);
   }
 };

unsupported/Eigen/CXX11/src/Tensor/TensorScan.h

@@ -357,8 +357,8 @@ __global__ EIGEN_HIP_LAUNCH_BOUNDS_1024 void ScanKernel(Self self, Index total_s
 
 }
 
-template <typename Self, typename Reducer>
-struct ScanLauncher<Self, Reducer, GpuDevice, false> {
+template <typename Self, typename Reducer, bool Vectorize>
+struct ScanLauncher<Self, Reducer, GpuDevice, Vectorize> {
   void operator()(const Self& self, typename Self::CoeffReturnType* data) {
      Index total_size = internal::array_prod(self.dimensions());
      Index num_blocks = (total_size / self.size() + 63) / 64;

unsupported/Eigen/IterativeSolvers

@@ -14,6 +14,7 @@
 #include "../../Eigen/Jacobi"
 #include "../../Eigen/Householder"
 
+
 /**
   * \defgroup IterativeLinearSolvers_Module Iterative solvers module
   * This module aims to provide various iterative linear and non linear solver algorithms.
@@ -23,11 +24,12 @@
   *  - an IDR(s) implementation
   *  - a DGMRES implementation
   *  - a MINRES implementation
+  *
   * \code
   * #include <unsupported/Eigen/IterativeSolvers>
   * \endcode
   */
-//@{
+
 
 #include "../../Eigen/src/Core/util/DisableStupidWarnings.h"
 
@@ -45,6 +47,5 @@
 
 #include "../../Eigen/src/Core/util/ReenableStupidWarnings.h"
 
-//@}
 
 #endif // EIGEN_ITERATIVE_SOLVERS_MODULE_H

unsupported/Eigen/SparseExtra

@@ -24,6 +24,7 @@
 
 #ifdef EIGEN_GOOGLEHASH_SUPPORT
   #include <google/dense_hash_map>
+  #include <google/sparse_hash_map>
 #endif
 
 /**

unsupported/Eigen/src/SparseExtra/RandomSetter.h

@@ -10,7 +10,13 @@
 #ifndef EIGEN_RANDOMSETTER_H
 #define EIGEN_RANDOMSETTER_H
 
-namespace Eigen { 
+#if defined(EIGEN_GOOGLEHASH_SUPPORT)
+// Ensure the ::google namespace exists, required for checking existence of 
+// ::google::dense_hash_map and ::google::sparse_hash_map.
+namespace google {}
+#endif
+
+namespace Eigen {
 
 /** Represents a std::map
   *
@@ -56,7 +62,26 @@ template<typename Scalar> struct StdUnorderedMapTraits
 };
 #endif // EIGEN_UNORDERED_MAP_SUPPORT
 
-#ifdef _DENSE_HASH_MAP_H_
+#if defined(EIGEN_GOOGLEHASH_SUPPORT)
+
+namespace google {
+  
+// Namespace work-around, since sometimes dense_hash_map and sparse_hash_map
+// are in the global namespace, and other times they are under ::google.
+using namespace ::google;
+
+template<typename KeyType, typename Scalar>
+struct DenseHashMap {
+  typedef dense_hash_map<KeyType, Scalar> type;
+};
+
+template<typename KeyType, typename Scalar>
+struct SparseHashMap {
+  typedef sparse_hash_map<KeyType, Scalar> type;
+};
+
+} // namespace google
+
 /** Represents a google::dense_hash_map
   *
   * \see RandomSetter
@@ -64,7 +89,7 @@ template<typename Scalar> struct StdUnorderedMapTraits
 template<typename Scalar> struct GoogleDenseHashMapTraits
 {
   typedef int KeyType;
-  typedef google::dense_hash_map<KeyType,Scalar> Type;
+  typedef typename google::DenseHashMap<KeyType,Scalar>::type Type;
   enum {
     IsSorted = 0
   };
@@ -72,9 +97,7 @@ template<typename Scalar> struct GoogleDenseHashMapTraits
   static void setInvalidKey(Type& map, const KeyType& k)
   { map.set_empty_key(k); }
 };
-#endif
 
-#ifdef _SPARSE_HASH_MAP_H_
 /** Represents a google::sparse_hash_map
   *
   * \see RandomSetter
@@ -82,7 +105,7 @@ template<typename Scalar> struct GoogleDenseHashMapTraits
 template<typename Scalar> struct GoogleSparseHashMapTraits
 {
   typedef int KeyType;
-  typedef google::sparse_hash_map<KeyType,Scalar> Type;
+  typedef typename google::SparseHashMap<KeyType,Scalar>::type Type;
   enum {
     IsSorted = 0
   };
@@ -134,18 +157,17 @@ template<typename Scalar> struct GoogleSparseHashMapTraits
   * GoogleSparseHashMapTraits, GnuHashMapTraits, and finally StdMapTraits.
   *
   * For performance and memory consumption reasons it is highly recommended to use one of
-  * the Google's hash_map implementation. To enable the support for them, you have two options:
-  *  - \#include <google/dense_hash_map> yourself \b before Eigen/Sparse header
-  *  - define EIGEN_GOOGLEHASH_SUPPORT
-  * In the later case the inclusion of <google/dense_hash_map> is made for you.
+  * Google's hash_map implementations. To enable the support for them, you must define
+  * EIGEN_GOOGLEHASH_SUPPORT. This will include both <google/dense_hash_map> and
+  * <google/sparse_hash_map> for you.
   *
-  * \see http://code.google.com/p/google-sparsehash/
+  * \see https://github.com/sparsehash/sparsehash
   */
 template<typename SparseMatrixType,
          template <typename T> class MapTraits =
-#if defined _DENSE_HASH_MAP_H_
+#if defined(EIGEN_GOOGLEHASH_SUPPORT)
           GoogleDenseHashMapTraits
-#elif defined _HASH_MAP
+#elif defined(_HASH_MAP)
           GnuHashMapTraits
 #else
           StdMapTraits

unsupported/test/cxx11_tensor_of_float16_gpu.cu

@@ -444,7 +444,7 @@ void test_gpu_forced_evals() {
       d_float, num_elem);
   Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_half1(
       d_res_half1, num_elem);
- Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Unaligned> gpu_res_half2(
+  Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Unaligned> gpu_res_half2(
       d_res_half2, num_elem);
   Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_float(
       d_res_float, num_elem);
@@ -461,7 +461,7 @@ void test_gpu_forced_evals() {
   Tensor<float, 1> half_prec2(num_elem);
   Tensor<float, 1> full_prec(num_elem);
   gpu_device.memcpyDeviceToHost(half_prec1.data(), d_res_half1, num_elem*sizeof(float));
-  gpu_device.memcpyDeviceToHost(half_prec2.data(), d_res_half1, num_elem*sizeof(float));
+  gpu_device.memcpyDeviceToHost(half_prec2.data(), d_res_half2, num_elem*sizeof(float));
   gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(float));
   gpu_device.synchronize();
 

unsupported/test/sparse_extra.cpp

@@ -123,10 +123,8 @@ template<typename SparseMatrixType> void sparse_extra(const SparseMatrixType& re
     #ifdef EIGEN_UNORDERED_MAP_SUPPORT
     VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
     #endif
-    #ifdef _DENSE_HASH_MAP_H_
+    #ifdef EIGEN_GOOGLEHASH_SUPPORT
     VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-    #ifdef _SPARSE_HASH_MAP_H_
     VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
     #endif