applying EIGEN_DECLARE_TEST to *gpu* tests

Also, a few minor fixes for GPU tests running in HIP mode.

1. Adding an include for hip/hip_runtime.h in the Macros.h file
   For HIP __host__ and __device__ are macros which are defined in hip headers.
   Their definitions need to be included before their use in the file.

2. Fixing the compile failure in TensorContractionGpu introduced by the commit to
   "Fuse computations into the Tensor contractions using output kernel"

3. Fixing a HIP/clang specific compile error by making the struct-member assignment explicit

1 files changed, 4 insertions, 3 deletions

diff --git a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
index fbc1ee2f6..2d1a82c57 100644
--- a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
+++ b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
@@ -610,6 +610,7 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
   static inline bool extract_kernel(MatrixType& mat, Ref<VectorType> res, Ref<VectorType> representative)
   {
     EIGEN_USING_STD_MATH(abs);
+    EIGEN_USING_STD_MATH(sqrt);
     Index i0;
     // Find non-zero column i0 (by construction, there must exist a non zero coefficient on the diagonal):
     mat.diagonal().cwiseAbs().maxCoeff(&i0);
@@ -620,8 +621,8 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
     VectorType c0, c1;
     n0 = (c0 = representative.cross(mat.col((i0+1)%3))).squaredNorm();
     n1 = (c1 = representative.cross(mat.col((i0+2)%3))).squaredNorm();
-    if(n0>n1) res = c0/std::sqrt(n0);
-    else      res = c1/std::sqrt(n1);
+    if(n0>n1) res = c0/sqrt(n0);
+    else      res = c1/sqrt(n1);
 
     return true;
   }
@@ -723,7 +724,7 @@ struct direct_selfadjoint_eigenvalues<SolverType,2,false>
   EIGEN_DEVICE_FUNC
   static inline void computeRoots(const MatrixType& m, VectorType& roots)
   {
-    using std::sqrt;
+    EIGEN_USING_STD_MATH(sqrt);
     const Scalar t0 = Scalar(0.5) * sqrt( numext::abs2(m(0,0)-m(1,1)) + Scalar(4)*numext::abs2(m(1,0)));
     const Scalar t1 = Scalar(0.5) * (m(0,0) + m(1,1));
     roots(0) = t1 - t0;