TheRock/rocm-libraries/projects/rocsolver/clients/common/lapack/testing_syevx_heevx.hpp

/* **************************************************************************
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#pragma once

#include "common/matrix_utils/matrix_utils.hpp"
#include "common/misc/client_util.hpp"
#include "common/misc/clientcommon.hpp"
#include "common/misc/lapack_host_reference.hpp"
#include "common/misc/norm.hpp"
#include "common/misc/rocsolver.hpp"
#include "common/misc/rocsolver_arguments.hpp"
#include "common/misc/rocsolver_test.hpp"
#include "common/misc/rocsolver_timer.hpp"

template <bool STRIDED, typename T, typename S, typename SS, typename U>
void syevx_heevx_checkBadArgs(const rocblas_handle handle,
                              const rocblas_evect evect,
                              const rocblas_erange erange,
                              const rocblas_fill uplo,
                              const rocblas_int n,
                              T dA,
                              const rocblas_int lda,
                              const rocblas_stride stA,
                              const SS vl,
                              const SS vu,
                              const rocblas_int il,
                              const rocblas_int iu,
                              const SS abstol,
                              U dNev,
                              S dW,
                              const rocblas_stride stW,
                              T dZ,
                              const rocblas_int ldz,
                              const rocblas_stride stZ,
                              U dIfail,
                              const rocblas_stride stF,
                              U dinfo,
                              const rocblas_int bc)
{
    // handle
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, nullptr, evect, erange, uplo, n, dA, lda,
                                                stA, vl, vu, il, iu, abstol, dNev, dW, stW, dZ, ldz,
                                                stZ, dIfail, stF, dinfo, bc),
                          rocblas_status_invalid_handle);

    // values
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, rocblas_evect(0), erange, uplo, n,
                                                dA, lda, stA, vl, vu, il, iu, abstol, dNev, dW, stW,
                                                dZ, ldz, stZ, dIfail, stF, dinfo, bc),
                          rocblas_status_invalid_value);
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, rocblas_erange(0), uplo, n,
                                                dA, lda, stA, vl, vu, il, iu, abstol, dNev, dW, stW,
                                                dZ, ldz, stZ, dIfail, stF, dinfo, bc),
                          rocblas_status_invalid_value);
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, rocblas_fill_full,
                                                n, dA, lda, stA, vl, vu, il, iu, abstol, dNev, dW,
                                                stW, dZ, ldz, stZ, dIfail, stF, dinfo, bc),
                          rocblas_status_invalid_value);

    // sizes (only check batch_count if applicable)
    if(STRIDED)
        EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, dA,
                                                    lda, stA, vl, vu, il, iu, abstol, dNev, dW, stW,
                                                    dZ, ldz, stZ, dIfail, stF, dinfo, -1),
                              rocblas_status_invalid_size);

    // pointers
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n,
                                                (T) nullptr, lda, stA, vl, vu, il, iu, abstol, dNev,
                                                dW, stW, dZ, ldz, stZ, dIfail, stF, dinfo, bc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, dA, lda,
                                                stA, vl, vu, il, iu, abstol, (U) nullptr, dW, stW,
                                                dZ, ldz, stZ, dIfail, stF, dinfo, bc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, dA, lda,
                                                stA, vl, vu, il, iu, abstol, dNev, (S) nullptr, stW,
                                                dZ, ldz, stZ, dIfail, stF, dinfo, bc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, dA, lda,
                                                stA, vl, vu, il, iu, abstol, dNev, dW, stW,
                                                (T) nullptr, ldz, stZ, dIfail, stF, dinfo, bc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, dA, lda,
                                                stA, vl, vu, il, iu, abstol, dNev, dW, stW, dZ, ldz,
                                                stZ, (U) nullptr, stF, dinfo, bc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, dA, lda,
                                                stA, vl, vu, il, iu, abstol, dNev, dW, stW, dZ, ldz,
                                                stZ, dIfail, stF, (U) nullptr, bc),
                          rocblas_status_invalid_pointer);

    // quick return with invalid pointers
    EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, 0,
                                                (T) nullptr, lda, stA, vl, vu, il, iu, abstol, dNev,
                                                (S) nullptr, stW, (T) nullptr, ldz, stZ,
                                                (U) nullptr, stF, dinfo, bc),
                          rocblas_status_success);

    // quick return with zero batch_count if applicable
    if(STRIDED)
        EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, dA, lda,
                                                    stA, vl, vu, il, iu, abstol, (U) nullptr, dW,
                                                    stW, dZ, ldz, stZ, dIfail, stF, (U) nullptr, 0),
                              rocblas_status_success);
}

template <bool BATCHED, bool STRIDED, typename T>
void testing_syevx_heevx_bad_arg()
{
    using S = decltype(std::real(T{}));

    // safe arguments
    rocblas_local_handle handle;
    rocblas_evect evect = rocblas_evect_original;
    rocblas_erange erange = rocblas_erange_value;
    rocblas_fill uplo = rocblas_fill_lower;
    rocblas_int n = 1;
    rocblas_int lda = 1;
    rocblas_int ldz = 1;
    rocblas_stride stA = 1;
    rocblas_stride stW = 1;
    rocblas_stride stZ = 1;
    rocblas_stride stF = 1;
    rocblas_int bc = 1;

    S vl = 0.0;
    S vu = 1.0;
    rocblas_int il = 0;
    rocblas_int iu = 0;
    S abstol = 0;

    if(BATCHED)
    {
        // memory allocations
        device_batch_vector<T> dA(1, 1, 1);
        device_batch_vector<T> dZ(1, 1, 1);
        device_strided_batch_vector<S> dW(1, 1, 1, 1);
        device_strided_batch_vector<rocblas_int> dNev(1, 1, 1, 1);
        device_strided_batch_vector<rocblas_int> dIfail(1, 1, 1, 1);
        device_strided_batch_vector<rocblas_int> dinfo(1, 1, 1, 1);
        CHECK_HIP_ERROR(dA.memcheck());
        CHECK_HIP_ERROR(dZ.memcheck());
        CHECK_HIP_ERROR(dW.memcheck());
        CHECK_HIP_ERROR(dNev.memcheck());
        CHECK_HIP_ERROR(dIfail.memcheck());
        CHECK_HIP_ERROR(dinfo.memcheck());

        // check bad arguments
        syevx_heevx_checkBadArgs<STRIDED>(handle, evect, erange, uplo, n, dA.data(), lda, stA, vl,
                                          vu, il, iu, abstol, dNev.data(), dW.data(), stW,
                                          dZ.data(), ldz, stZ, dIfail.data(), stF, dinfo.data(), bc);
    }
    else
    {
        // memory allocations
        device_strided_batch_vector<T> dA(1, 1, 1, 1);
        device_strided_batch_vector<T> dZ(1, 1, 1, 1);
        device_strided_batch_vector<S> dW(1, 1, 1, 1);
        device_strided_batch_vector<rocblas_int> dNev(1, 1, 1, 1);
        device_strided_batch_vector<rocblas_int> dIfail(1, 1, 1, 1);
        device_strided_batch_vector<rocblas_int> dinfo(1, 1, 1, 1);
        CHECK_HIP_ERROR(dA.memcheck());
        CHECK_HIP_ERROR(dZ.memcheck());
        CHECK_HIP_ERROR(dW.memcheck());
        CHECK_HIP_ERROR(dNev.memcheck());
        CHECK_HIP_ERROR(dIfail.memcheck());
        CHECK_HIP_ERROR(dinfo.memcheck());

        // check bad arguments
        syevx_heevx_checkBadArgs<STRIDED>(handle, evect, erange, uplo, n, dA.data(), lda, stA, vl,
                                          vu, il, iu, abstol, dNev.data(), dW.data(), stW,
                                          dZ.data(), ldz, stZ, dIfail.data(), stF, dinfo.data(), bc);
    }
}

template <bool CPU, bool GPU, typename T, typename Td, typename Th>
void syevx_heevx_initData(const rocblas_handle handle,
                          const rocblas_evect evect,
                          const rocblas_int n,
                          Td& dA,
                          const rocblas_int lda,
                          const rocblas_int bc,
                          Th& hA,
                          std::vector<T>& A,
                          bool test = true)
{
    if(CPU)
    {
        rocblas_init<T>(hA, true);

        // construct well conditioned matrix A such that all eigenvalues are in (-20, 20)
#ifdef ROCSOLVER_TESTS_USE_DEPRECATED_INITIALIZERS
        // Old matrix initialization
        for(rocblas_int b = 0; b < bc; ++b)
        {
            for(rocblas_int i = 0; i < n; i++)
            {
                for(rocblas_int j = i; j < n; j++)
                {
                    if(i == j)
                        hA[b][i + j * lda] = std::real(hA[b][i + j * lda]) + 10;
                    else
                    {
                        if(j == i + 1)
                        {
                            hA[b][i + j * lda] = (hA[b][i + j * lda] - 5) / 10;
                            hA[b][j + i * lda] = sconj(hA[b][i + j * lda]);
                        }
                        else
                            hA[b][j + i * lda] = hA[b][i + j * lda] = 0;
                    }
                }
                if(i == n / 4 || i == n / 2 || i == n - 1 || i == n / 7 || i == n / 5 || i == n / 3)
                    hA[b][i + i * lda] *= -1;
            }
#else
        // New matrix initialization
        using HMat = HostMatrix<T, rocblas_int>;
        using BDesc = typename HMat::BlockDescriptor;

        for(rocblas_int b = 0; b < bc; ++b)
        {
            auto hAw = HMat::Wrap(hA[b], lda, n);
            if(hAw) // update matrix hA if n >= 1
            {
                rocblas_int half_n = n / 2;
                // create half_n eigenvalues from -20 to -1, and n - half_n eigenvalues from 1 to 20
                // (for the time being, avoid using -20 and 20, otherwise some tests will fail with hNev != hNevRes)
                auto eigs = cat(HMat::FromRange(-20.1, -1.0, half_n),
                                HMat::FromRange(1.0, 20.1, n - half_n));
                auto [Q, _] = qr((*hAw).block(BDesc().nrows(n).ncols(n)));
                hAw->set_to_zero();

                hAw->copy_data_from(Q * HMat::Zeros(n).diag(eigs) * adjoint(Q));
            }
#endif
            // make copy of original data to test vectors if required
            if(test && evect == rocblas_evect_original)
            {
                for(rocblas_int i = 0; i < n; i++)
                {
                    for(rocblas_int j = 0; j < n; j++)
                        A[b * lda * n + i + j * lda] = hA[b][i + j * lda];
                }
            }
        }
    }

    if(GPU)
    {
        // now copy to the GPU
        CHECK_HIP_ERROR(dA.transfer_from(hA));
    }
}

template <bool STRIDED, typename T, typename S, typename Sd, typename Td, typename Id, typename Sh, typename Th, typename Ih>
void syevx_heevx_getError(const rocblas_handle handle,
                          const rocblas_evect evect,
                          const rocblas_erange erange,
                          const rocblas_fill uplo,
                          const rocblas_int n,
                          Td& dA,
                          const rocblas_int lda,
                          const rocblas_stride stA,
                          const S vl,
                          const S vu,
                          const rocblas_int il,
                          const rocblas_int iu,
                          const S abstol,
                          Id& dNev,
                          Sd& dW,
                          const rocblas_stride stW,
                          Td& dZ,
                          const rocblas_int ldz,
                          const rocblas_stride stZ,
                          Id& dIfail,
                          const rocblas_stride stF,
                          Id& dinfo,
                          const rocblas_int bc,
                          Th& hA,
                          Ih& hNev,
                          Ih& hNevRes,
                          Sh& hW,
                          Sh& hWRes,
                          Th& hZ,
                          Th& hZRes,
                          Ih& hIfail,
                          Ih& hIfailRes,
                          Ih& hinfo,
                          Ih& hinfoRes,
                          double* max_err,
                          size_t& hashA,
                          size_t& hashW,
                          size_t& hashZ)
{
    using HMat = HostMatrix<T, rocblas_int>;
    using BDesc = typename HMat::BlockDescriptor;
    constexpr bool COMPLEX = rocblas_is_complex<T>;

    int lwork = !COMPLEX ? 35 * n : 33 * n;
    int lrwork = !COMPLEX ? 0 : 7 * n;
    int liwork = 5 * n;

    std::vector<T> work(lwork);
    std::vector<S> rwork(lrwork);
    std::vector<int> iwork(liwork);
    std::vector<T> A(lda * n * bc);

    // input data initialization
    syevx_heevx_initData<true, true, T>(handle, evect, n, dA, lda, bc, hA, A);

    // hash inputs
    hashA = deterministic_hash(hA, bc);

    // execute computations
    // GPU lapack
    CHECK_ROCBLAS_ERROR(rocsolver_syevx_heevx(
        STRIDED, handle, evect, erange, uplo, n, dA.data(), lda, stA, vl, vu, il, iu, abstol,
        dNev.data(), dW.data(), stW, dZ.data(), ldz, stZ, dIfail.data(), stF, dinfo.data(), bc));

    CHECK_HIP_ERROR(hNevRes.transfer_from(dNev));
    CHECK_HIP_ERROR(hWRes.transfer_from(dW));
    CHECK_HIP_ERROR(hinfoRes.transfer_from(dinfo));
    if(evect == rocblas_evect_original)
    {
        CHECK_HIP_ERROR(hZRes.transfer_from(dZ));
        CHECK_HIP_ERROR(hIfailRes.transfer_from(dIfail));
    }

    // hash outputs
    hashW = deterministic_hash(hWRes, bc);
    if(evect == rocblas_evect_original)
        hashZ = deterministic_hash(hZRes, bc);

    // CPU lapack
    // abstol = 0 ensures max accuracy in rocsolver; for lapack we should use 2*safemin
    S atol = (abstol == 0) ? 2 * get_safemin<S>() : abstol;
    for(rocblas_int b = 0; b < bc; ++b)
        cpu_syevx_heevx(evect, erange, uplo, n, hA[b], lda, vl, vu, il, iu, atol, hNev[b], hW[b],
                        hZ[b], ldz, work.data(), lwork, rwork.data(), iwork.data(), hIfail[b],
                        hinfo[b]);

    // Check info for non-convergence
    *max_err = 0;
    for(rocblas_int b = 0; b < bc; ++b)
    {
        EXPECT_EQ(hinfo[b][0], hinfoRes[b][0]) << "where b = " << b;
        if(hinfo[b][0] != hinfoRes[b][0])
            *max_err += 1;
    }

    // Check number of returned eigenvalues
    double err = 0;
    for(rocblas_int b = 0; b < bc; ++b)
    {
        EXPECT_EQ(hNev[b][0], hNevRes[b][0]) << "where b = " << b;
        if(hNev[b][0] != hNevRes[b][0])
            err++;
    }
    *max_err = err > *max_err ? err : *max_err;

    // (We expect the used input matrices to always converge. Testing
    // implicitly the equivalent non-converged matrix is very complicated and it boils
    // down to essentially run the algorithm again and until convergence is achieved).

    for(rocblas_int b = 0; b < bc; ++b)
    {
        // Number of eigenvalues
        auto num_eigs = hNev[b][0];

        if((hinfo[b][0] != 0) || (num_eigs <= 0))
        {
            if(evect == rocblas_evect_original)
            {
                // check ifail
                err = 0;
                for(int j = 0; j < hinfo[b][0]; j++)
                {
                    EXPECT_NE(hIfailRes[b][j], 0) << "where b = " << b << ", j = " << j;
                    if(hIfailRes[b][j] == 0)
                        err++;
                }
                *max_err = err > *max_err ? err : *max_err;
            }

            continue;
        }

        // Get reference eigenvalues (will be updated in a subsequent commit)
        auto eigs_ref = *HMat::Convert(hW[b], 1, num_eigs);

        // Get computed eigenvalues
        auto eigs_b = *HMat::Convert(
            hWRes[b], 1, num_eigs); // convert eigenvalues from type S to type T, if required

        if(evect != rocblas_evect_original)
        {
            // only eigenvalues needed; can compare with LAPACK

            err = (eigs_ref - eigs_b).max_coeff_norm() / eigs_ref.max_coeff_norm();
            *max_err = err > *max_err ? err : *max_err;
        }
        else
        {
            // both eigenvalues and eigenvectors needed; need to implicitly test
            // eigenvectors due to non-uniqueness of eigenvectors under scaling
            // check ifail
            err = 0;
            for(int j = 0; j < hNev[b][0]; j++)
            {
                EXPECT_EQ(hIfailRes[b][j], 0) << "where b = " << b << ", j = " << j;
                if(hIfailRes[b][j] != 0)
                    err++;
            }
            *max_err = err > *max_err ? err : *max_err;

            // Create a thin wrapper of input matrix A (bc * lda * n), of size lda * n starting at b * lda * n
            auto AWrap_b = HMat::Wrap(A.data() + b * lda * n, lda, n);

            // Since `lda`, `ldz` and `n` can differ, we must extract submatrices of the correct size from
            // `A`, `hZRes` and `hWRes`.
            //
            // We want the sub-block starting from row 0, col 0 and with size n x n of A
            auto block_A = BDesc().from_row(0).from_col(0).nrows(n).ncols(
                n); // the `from_row(0)` and `from_col(0)` calls can be omitted
            auto A_b = (*AWrap_b).block(block_A);

            // Get computed eigenvectors
            auto V_b = (*HMat::Wrap(hZRes[b], ldz, n)).block(BDesc().nrows(n).ncols(num_eigs));

            // Check orthogonality of computed eigenvectors
            auto OE = adjoint(V_b) * V_b - HMat::Eye(num_eigs);
            S ortho_err = OE.norm();
            *max_err = ortho_err > *max_err ? ortho_err : *max_err;

            // Check accuracy of eigenpairs
            auto AE = adjoint(V_b) * A_b * V_b - HMat::Zeros(num_eigs).diag(eigs_b);
            err = AE.max_col_norm() / eigs_ref.max_coeff_norm();
            /* err *= std::numeric_limits<S>::epsilon() / ortho_err; // Use "relative Weyl" error bound */
            *max_err = err > *max_err ? err : *max_err;
        }
    }
}

template <bool STRIDED, typename T, typename S, typename Sd, typename Td, typename Id, typename Sh, typename Th, typename Ih>
void syevx_heevx_getPerfData(const rocblas_handle handle,
                             const rocblas_evect evect,
                             const rocblas_erange erange,
                             const rocblas_fill uplo,
                             const rocblas_int n,
                             Td& dA,
                             const rocblas_int lda,
                             const rocblas_stride stA,
                             const S vl,
                             const S vu,
                             const rocblas_int il,
                             const rocblas_int iu,
                             const S abstol,
                             Id& dNev,
                             Sd& dW,
                             const rocblas_stride stW,
                             Td& dZ,
                             const rocblas_int ldz,
                             const rocblas_stride stZ,
                             Id& dIfail,
                             const rocblas_stride stF,
                             Id& dinfo,
                             const rocblas_int bc,
                             Th& hA,
                             Ih& hNev,
                             Sh& hW,
                             Th& hZ,
                             Ih& hIfail,
                             Ih& hinfo,
                             double* gpu_time_used,
                             double* cpu_time_used,
                             const rocblas_int hot_calls,
                             const int profile,
                             const bool profile_kernels,
                             const bool perf)
{
    constexpr bool COMPLEX = rocblas_is_complex<T>;

    int lwork = !COMPLEX ? 35 * n : 33 * n;
    int lrwork = !COMPLEX ? 0 : 7 * n;
    int liwork = 5 * n;

    std::vector<T> work(lwork);
    std::vector<S> rwork(lrwork);
    std::vector<int> iwork(liwork);
    std::vector<T> A;

    // abstol = 0 ensures max accuracy in rocsolver; for lapack we should use 2*safemin
    S atol = (abstol == 0) ? 2 * get_safemin<S>() : abstol;

    if(!perf)
    {
        syevx_heevx_initData<true, false, T>(handle, evect, n, dA, lda, bc, hA, A, 0);

        // cpu-lapack performance (only if not in perf mode)
        *cpu_time_used = get_time_us_no_sync();
        for(rocblas_int b = 0; b < bc; ++b)
            cpu_syevx_heevx(evect, erange, uplo, n, hA[b], lda, vl, vu, il, iu, atol, hNev[b],
                            hW[b], hZ[b], ldz, work.data(), lwork, rwork.data(), iwork.data(),
                            hIfail[b], hinfo[b]);
        *cpu_time_used = get_time_us_no_sync() - *cpu_time_used;
    }

    syevx_heevx_initData<true, false, T>(handle, evect, n, dA, lda, bc, hA, A, 0);

    // cold calls
    for(int iter = 0; iter < 2; iter++)
    {
        syevx_heevx_initData<false, true, T>(handle, evect, n, dA, lda, bc, hA, A, 0);

        CHECK_ROCBLAS_ERROR(rocsolver_syevx_heevx(
            STRIDED, handle, evect, erange, uplo, n, dA.data(), lda, stA, vl, vu, il, iu, abstol,
            dNev.data(), dW.data(), stW, dZ.data(), ldz, stZ, dIfail.data(), stF, dinfo.data(), bc));
    }

    // gpu-lapack performance
    hipStream_t stream;
    CHECK_ROCBLAS_ERROR(rocblas_get_stream(handle, &stream));
    rocsolver_timer timer;

    if(profile > 0)
    {
        if(profile_kernels)
            rocsolver_log_set_layer_mode(rocblas_layer_mode_log_profile
                                         | rocblas_layer_mode_ex_log_kernel);
        else
            rocsolver_log_set_layer_mode(rocblas_layer_mode_log_profile);
        rocsolver_log_set_max_levels(profile);
    }

    for(rocblas_int iter = 0; iter < hot_calls; iter++)
    {
        syevx_heevx_initData<false, true, T>(handle, evect, n, dA, lda, bc, hA, A, 0);

        timer.start(stream);
        rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, dA.data(), lda, stA, vl, vu,
                              il, iu, abstol, dNev.data(), dW.data(), stW, dZ.data(), ldz, stZ,
                              dIfail.data(), stF, dinfo.data(), bc);
        timer.end(stream);
    }
    *gpu_time_used = timer.get_combined();
}

template <bool BATCHED, bool STRIDED, typename T>
void testing_syevx_heevx(Arguments& argus)
{
    using S = decltype(std::real(T{}));

    // get arguments
    rocblas_local_handle handle;
    char evectC = argus.get<char>("evect");
    char erangeC = argus.get<char>("erange");
    char uploC = argus.get<char>("uplo");
    rocblas_int n = argus.get<rocblas_int>("n");
    rocblas_int lda = argus.get<rocblas_int>("lda", n);
    rocblas_int ldz = argus.get<rocblas_int>("ldz", n);
    rocblas_stride stA = argus.get<rocblas_stride>("strideA", lda * n);
    rocblas_stride stW = argus.get<rocblas_stride>("strideW", n);
    rocblas_stride stZ = argus.get<rocblas_stride>("strideZ", ldz * n);
    rocblas_stride stF = argus.get<rocblas_stride>("strideF", n);

    S vl = S(argus.get<double>("vl", 0));
    S vu = S(argus.get<double>("vu", erangeC == 'V' ? 1 : 0));
    rocblas_int il = argus.get<rocblas_int>("il", erangeC == 'I' ? 1 : 0);
    rocblas_int iu = argus.get<rocblas_int>("iu", erangeC == 'I' ? 1 : 0);
    S abstol = S(argus.get<double>("abstol", 0));

    rocblas_evect evect = char2rocblas_evect(evectC);
    rocblas_erange erange = char2rocblas_erange(erangeC);
    rocblas_fill uplo = char2rocblas_fill(uploC);
    rocblas_int bc = argus.batch_count;
    rocblas_int hot_calls = argus.iters;

    // check non-supported values
    if(uplo == rocblas_fill_full || evect == rocblas_evect_tridiagonal)
    {
        if(BATCHED)
            EXPECT_ROCBLAS_STATUS(
                rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, (T* const*)nullptr,
                                      lda, stA, vl, vu, il, iu, abstol, (rocblas_int*)nullptr,
                                      (S*)nullptr, stW, (T* const*)nullptr, ldz, stZ,
                                      (rocblas_int*)nullptr, stF, (rocblas_int*)nullptr, bc),
                rocblas_status_invalid_value);
        else
            EXPECT_ROCBLAS_STATUS(
                rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, (T*)nullptr, lda,
                                      stA, vl, vu, il, iu, abstol, (rocblas_int*)nullptr,
                                      (S*)nullptr, stW, (T*)nullptr, ldz, stZ,
                                      (rocblas_int*)nullptr, stF, (rocblas_int*)nullptr, bc),
                rocblas_status_invalid_value);

        if(argus.timing)
            rocsolver_bench_inform(inform_invalid_args);

        return;
    }

    // determine sizes
    size_t size_A = size_t(lda) * n;
    size_t size_W = n;
    size_t size_Z = size_t(ldz) * n;
    size_t size_ifail = n;
    size_t size_WRes = (argus.unit_check || argus.norm_check || argus.hash_check) ? size_W : 0;
    size_t size_ZRes = (argus.unit_check || argus.norm_check || argus.hash_check) ? size_Z : 0;
    size_t size_ifailRes
        = (argus.unit_check || argus.norm_check || argus.hash_check) ? size_ifail : 0;

    double max_error = 0, gpu_time_used = 0, cpu_time_used = 0;
    size_t hashA = 0, hashW = 0, hashZ = 0;

    // check invalid sizes
    bool invalid_size = (n < 0 || lda < n || (evect != rocblas_evect_none && ldz < n) || bc < 0
                         || (erange == rocblas_erange_value && vl >= vu)
                         || (erange == rocblas_erange_index && (il < 1 || iu < 0))
                         || (erange == rocblas_erange_index && (iu > n || (n > 0 && il > iu))));
    if(invalid_size)
    {
        if(BATCHED)
            EXPECT_ROCBLAS_STATUS(
                rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, (T* const*)nullptr,
                                      lda, stA, vl, vu, il, iu, abstol, (rocblas_int*)nullptr,
                                      (S*)nullptr, stW, (T* const*)nullptr, ldz, stZ,
                                      (rocblas_int*)nullptr, stF, (rocblas_int*)nullptr, bc),
                rocblas_status_invalid_size);
        else
            EXPECT_ROCBLAS_STATUS(
                rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n, (T*)nullptr, lda,
                                      stA, vl, vu, il, iu, abstol, (rocblas_int*)nullptr,
                                      (S*)nullptr, stW, (T*)nullptr, ldz, stZ,
                                      (rocblas_int*)nullptr, stF, (rocblas_int*)nullptr, bc),
                rocblas_status_invalid_size);

        if(argus.timing)
            rocsolver_bench_inform(inform_invalid_size);

        return;
    }

    // memory size query is necessary
    if(argus.mem_query)
    {
        CHECK_ROCBLAS_ERROR(rocblas_start_device_memory_size_query(handle));
        if(BATCHED)
            CHECK_ALLOC_QUERY(rocsolver_syevx_heevx(
                STRIDED, handle, evect, erange, uplo, n, (T* const*)nullptr, lda, stA, vl, vu, il,
                iu, abstol, (rocblas_int*)nullptr, (S*)nullptr, stW, (T* const*)nullptr, ldz, stZ,
                (rocblas_int*)nullptr, stF, (rocblas_int*)nullptr, bc));
        else
            CHECK_ALLOC_QUERY(rocsolver_syevx_heevx(
                STRIDED, handle, evect, erange, uplo, n, (T*)nullptr, lda, stA, vl, vu, il, iu,
                abstol, (rocblas_int*)nullptr, (S*)nullptr, stW, (T*)nullptr, ldz, stZ,
                (rocblas_int*)nullptr, stF, (rocblas_int*)nullptr, bc));

        size_t size;
        CHECK_ROCBLAS_ERROR(rocblas_stop_device_memory_size_query(handle, &size));

        rocsolver_bench_inform(inform_mem_query, size);
        return;
    }

    // memory allocations (all cases)
    // host
    host_strided_batch_vector<rocblas_int> hNev(1, 1, 1, bc);
    host_strided_batch_vector<rocblas_int> hNevRes(1, 1, 1, bc);
    host_strided_batch_vector<S> hW(size_W, 1, stW, bc);
    host_strided_batch_vector<S> hWres(size_WRes, 1, stW, bc);
    host_strided_batch_vector<rocblas_int> hIfail(size_ifail, 1, stF, bc);
    host_strided_batch_vector<rocblas_int> hIfailRes(size_ifailRes, 1, stF, bc);
    host_strided_batch_vector<rocblas_int> hinfo(1, 1, 1, bc);
    host_strided_batch_vector<rocblas_int> hinfoRes(1, 1, 1, bc);
    // device
    device_strided_batch_vector<rocblas_int> dNev(1, 1, 1, bc);
    device_strided_batch_vector<S> dW(size_W, 1, stW, bc);
    device_strided_batch_vector<rocblas_int> dIfail(size_ifail, 1, stF, bc);
    device_strided_batch_vector<rocblas_int> dinfo(1, 1, 1, bc);
    CHECK_HIP_ERROR(dNev.memcheck());
    if(size_W)
        CHECK_HIP_ERROR(dW.memcheck());
    if(size_ifail)
        CHECK_HIP_ERROR(dIfail.memcheck());
    CHECK_HIP_ERROR(dinfo.memcheck());

    if(BATCHED)
    {
        // memory allocations
        host_batch_vector<T> hA(size_A, 1, bc);
        host_batch_vector<T> hZ(size_Z, 1, bc);
        host_batch_vector<T> hZRes(size_ZRes, 1, bc);
        device_batch_vector<T> dA(size_A, 1, bc);
        device_batch_vector<T> dZ(size_Z, 1, bc);
        if(size_A)
            CHECK_HIP_ERROR(dA.memcheck());
        if(size_Z)
            CHECK_HIP_ERROR(dZ.memcheck());

        // check quick return
        if(n == 0 || bc == 0)
        {
            EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n,
                                                        dA.data(), lda, stA, vl, vu, il, iu, abstol,
                                                        dNev.data(), dW.data(), stW, dZ.data(), ldz,
                                                        stZ, dIfail.data(), stF, dinfo.data(), bc),
                                  rocblas_status_success);
            if(argus.timing)
                rocsolver_bench_inform(inform_quick_return);

            return;
        }

        // check computations
        if(argus.unit_check || argus.norm_check || argus.hash_check)
        {
            syevx_heevx_getError<STRIDED, T>(
                handle, evect, erange, uplo, n, dA, lda, stA, vl, vu, il, iu, abstol, dNev, dW, stW,
                dZ, ldz, stZ, dIfail, stF, dinfo, bc, hA, hNev, hNevRes, hW, hWres, hZ, hZRes,
                hIfail, hIfailRes, hinfo, hinfoRes, &max_error, hashA, hashW, hashZ);
        }

        // collect performance data
        if(argus.timing && hot_calls > 0)
        {
            syevx_heevx_getPerfData<STRIDED, T>(handle, evect, erange, uplo, n, dA, lda, stA, vl,
                                                vu, il, iu, abstol, dNev, dW, stW, dZ, ldz, stZ,
                                                dIfail, stF, dinfo, bc, hA, hNev, hW, hZ, hIfail,
                                                hinfo, &gpu_time_used, &cpu_time_used, hot_calls,
                                                argus.profile, argus.profile_kernels, argus.perf);
        }
    }

    else
    {
        // memory allocations
        host_strided_batch_vector<T> hA(size_A, 1, stA, bc);
        host_strided_batch_vector<T> hZ(size_Z, 1, stZ, bc);
        host_strided_batch_vector<T> hZRes(size_ZRes, 1, stZ, bc);
        device_strided_batch_vector<T> dA(size_A, 1, stA, bc);
        device_strided_batch_vector<T> dZ(size_Z, 1, stZ, bc);
        if(size_A)
            CHECK_HIP_ERROR(dA.memcheck());
        if(size_Z)
            CHECK_HIP_ERROR(dZ.memcheck());

        // check quick return
        if(n == 0 || bc == 0)
        {
            EXPECT_ROCBLAS_STATUS(rocsolver_syevx_heevx(STRIDED, handle, evect, erange, uplo, n,
                                                        dA.data(), lda, stA, vl, vu, il, iu, abstol,
                                                        dNev.data(), dW.data(), stW, dZ.data(), ldz,
                                                        stZ, dIfail.data(), stF, dinfo.data(), bc),
                                  rocblas_status_success);
            if(argus.timing)
                rocsolver_bench_inform(inform_quick_return);

            return;
        }

        // check computations
        if(argus.unit_check || argus.norm_check || argus.hash_check)
        {
            syevx_heevx_getError<STRIDED, T>(
                handle, evect, erange, uplo, n, dA, lda, stA, vl, vu, il, iu, abstol, dNev, dW, stW,
                dZ, ldz, stZ, dIfail, stF, dinfo, bc, hA, hNev, hNevRes, hW, hWres, hZ, hZRes,
                hIfail, hIfailRes, hinfo, hinfoRes, &max_error, hashA, hashW, hashZ);
        }

        // collect performance data
        if(argus.timing && hot_calls > 0)
        {
            syevx_heevx_getPerfData<STRIDED, T>(handle, evect, erange, uplo, n, dA, lda, stA, vl,
                                                vu, il, iu, abstol, dNev, dW, stW, dZ, ldz, stZ,
                                                dIfail, stF, dinfo, bc, hA, hNev, hW, hZ, hIfail,
                                                hinfo, &gpu_time_used, &cpu_time_used, hot_calls,
                                                argus.profile, argus.profile_kernels, argus.perf);
        }
    }

    // validate results for rocsolver-test
    // using 2 * n * machine_precision as tolerance
    if(argus.unit_check)
        ROCSOLVER_TEST_CHECK(T, max_error, 2 * n);

    // output results for rocsolver-bench
    if(argus.timing)
    {
        if(!argus.perf)
        {
            rocsolver_bench_header("Arguments:");
            if(BATCHED)
            {
                rocsolver_bench_output("evect", "erange", "uplo", "n", "lda", "vl", "vu", "il",
                                       "iu", "abstol", "strideW", "ldz", "strideF", "batch_c");
                rocsolver_bench_output(evectC, erangeC, uploC, n, lda, vl, vu, il, iu, abstol, stW,
                                       ldz, stF, bc);
            }
            else if(STRIDED)
            {
                rocsolver_bench_output("evect", "erange", "uplo", "n", "lda", "strideA", "vl", "vu",
                                       "il", "iu", "abstol", "strideW", "ldz", "strideZ", "strideF",
                                       "batch_c");
                rocsolver_bench_output(evectC, erangeC, uploC, n, lda, stA, vl, vu, il, iu, abstol,
                                       stW, ldz, stZ, stF, bc);
            }
            else
            {
                rocsolver_bench_output("evect", "erange", "uplo", "n", "lda", "vl", "vu", "il",
                                       "iu", "abstol", "ldz");
                rocsolver_bench_output(evectC, erangeC, uploC, n, lda, vl, vu, il, iu, abstol, ldz);
            }
            rocsolver_bench_header("Results:");
            if(argus.norm_check)
            {
                rocsolver_bench_output("cpu_time_us", "gpu_time_us", "error");
                rocsolver_bench_output(cpu_time_used, gpu_time_used, max_error);
            }
            else
            {
                rocsolver_bench_output("cpu_time_us", "gpu_time_us");
                rocsolver_bench_output(cpu_time_used, gpu_time_used);
            }
            rocsolver_bench_endl();
            if(argus.hash_check)
            {
                rocsolver_bench_output("hash(A)", "hash(W)", "hash(Z)");
                rocsolver_bench_output(ROCSOLVER_FORMAT_HASH(hashA), ROCSOLVER_FORMAT_HASH(hashW),
                                       ROCSOLVER_FORMAT_HASH(hashZ));
                rocsolver_bench_endl();
            }
        }
        else
        {
            if(argus.norm_check)
                rocsolver_bench_output(gpu_time_used, max_error);
            else
                rocsolver_bench_output(gpu_time_used);
        }
    }

    // ensure all arguments were consumed
    argus.validate_consumed();
}

#define EXTERN_TESTING_SYEVX_HEEVX(...) \
    extern template void testing_syevx_heevx<__VA_ARGS__>(Arguments&);

INSTANTIATE(EXTERN_TESTING_SYEVX_HEEVX, FOREACH_MATRIX_DATA_LAYOUT, FOREACH_SCALAR_TYPE, APPLY_STAMP)