/* **************************************************************************
 * Copyright (C) 2023-2024 Advanced Micro Devices, Inc. All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *
 * 1. Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer.
 *
 * 2. Redistributions in binary form must reproduce the above copyright
 *    notice, this list of conditions and the following disclaimer in the
 *    documentation and/or other materials provided with the distribution.
 *
 * THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 * ARE DISCLAIMED.  IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE
 * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
 * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
 * OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
 * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
 * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
 * SUCH DAMAGE.
 * *************************************************************************/

#pragma once

#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"

template <bool STRIDED, typename T, typename U>
void sygvdj_hegvdj_checkBadArgs(const rocblas_handle handle,
                                const rocblas_eform itype,
                                const rocblas_evect evect,
                                const rocblas_fill uplo,
                                const rocblas_int n,
                                T dA,
                                const rocblas_int lda,
                                const rocblas_stride stA,
                                T dB,
                                const rocblas_int ldb,
                                const rocblas_stride stB,
                                U dD,
                                const rocblas_stride stD,
                                rocblas_int* dInfo,
                                const rocblas_int bc)
{
    // handle
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, nullptr, itype, evect, uplo, n, dA, lda,
                                                  stA, dB, ldb, stB, dD, stD, dInfo, bc),
                          rocblas_status_invalid_handle);

    // values
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, rocblas_eform(0), evect, uplo, n,
                                                  dA, lda, stA, dB, ldb, stB, dD, stD, dInfo, bc),
                          rocblas_status_invalid_value);
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, rocblas_evect(0), uplo, n,
                                                  dA, lda, stA, dB, ldb, stB, dD, stD, dInfo, bc),
                          rocblas_status_invalid_value);
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, rocblas_evect_tridiagonal,
                                                  uplo, n, dA, lda, stA, dB, ldb, stB, dD, stD,
                                                  dInfo, bc),
                          rocblas_status_invalid_value);
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, rocblas_fill_full,
                                                  n, dA, lda, stA, dB, ldb, stB, dD, stD, dInfo, bc),
                          rocblas_status_invalid_value);

    // sizes (only check batch_count if applicable)
    if(STRIDED)
        EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n, dA,
                                                      lda, stA, dB, ldb, stB, dD, stD, dInfo, -1),
                              rocblas_status_invalid_size);

    // pointers
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n, (T) nullptr,
                                                  lda, stA, dB, ldb, stB, dD, stD, dInfo, bc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n, dA, lda,
                                                  stA, (T) nullptr, ldb, stB, dD, stD, dInfo, bc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n, dA, lda,
                                                  stA, dB, ldb, stB, (U) nullptr, stD, dInfo, bc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n, dA, lda, stA,
                                                  dB, ldb, stB, dD, stD, (rocblas_int*)nullptr, bc),
                          rocblas_status_invalid_pointer);

    // quick return with invalid pointers
    EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, 0,
                                                  (T) nullptr, lda, stA, (T) nullptr, ldb, stB,
                                                  (U) nullptr, stD, dInfo, bc),
                          rocblas_status_success);

    // quick return with zero batch_count if applicable
    if(STRIDED)
        EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n, dA,
                                                      lda, stA, dB, ldb, stB, dD, stD,
                                                      (rocblas_int*)nullptr, 0),
                              rocblas_status_success);
}

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

    // safe arguments
    rocblas_local_handle handle;
    rocblas_int n = 1;
    rocblas_int lda = 1;
    rocblas_int ldb = 1;
    rocblas_stride stA = 1;
    rocblas_stride stB = 1;
    rocblas_stride stD = 1;
    rocblas_int bc = 1;
    rocblas_eform itype = rocblas_eform_ax;
    rocblas_evect evect = rocblas_evect_none;
    rocblas_fill uplo = rocblas_fill_upper;

    if(BATCHED)
    {
        // memory allocations
        device_batch_vector<T> dA(1, 1, 1);
        device_batch_vector<T> dB(1, 1, 1);
        device_strided_batch_vector<S> dD(1, 1, 1, 1);
        device_strided_batch_vector<rocblas_int> dInfo(1, 1, 1, 1);
        CHECK_HIP_ERROR(dA.memcheck());
        CHECK_HIP_ERROR(dB.memcheck());
        CHECK_HIP_ERROR(dD.memcheck());
        CHECK_HIP_ERROR(dInfo.memcheck());

        // check bad arguments
        sygvdj_hegvdj_checkBadArgs<STRIDED>(handle, itype, evect, uplo, n, dA.data(), lda, stA,
                                            dB.data(), ldb, stB, dD.data(), stD, dInfo.data(), bc);
    }
    else
    {
        // memory allocations
        device_strided_batch_vector<T> dA(1, 1, 1, 1);
        device_strided_batch_vector<T> dB(1, 1, 1, 1);
        device_strided_batch_vector<S> dD(1, 1, 1, 1);
        device_strided_batch_vector<rocblas_int> dInfo(1, 1, 1, 1);
        CHECK_HIP_ERROR(dA.memcheck());
        CHECK_HIP_ERROR(dB.memcheck());
        CHECK_HIP_ERROR(dD.memcheck());
        CHECK_HIP_ERROR(dInfo.memcheck());

        // check bad arguments
        sygvdj_hegvdj_checkBadArgs<STRIDED>(handle, itype, evect, uplo, n, dA.data(), lda, stA,
                                            dB.data(), ldb, stB, dD.data(), stD, dInfo.data(), bc);
    }
}

template <bool CPU, bool GPU, typename T, typename Td, typename Th>
void sygvdj_hegvdj_initData(const rocblas_handle handle,
                            const rocblas_eform itype,
                            const rocblas_evect evect,
                            const rocblas_int n,
                            Td& dA,
                            const rocblas_int lda,
                            const rocblas_stride stA,
                            Td& dB,
                            const rocblas_int ldb,
                            const rocblas_stride stB,
                            const rocblas_int bc,
                            Th& hA,
                            Th& hB,
                            host_strided_batch_vector<T>& A,
                            host_strided_batch_vector<T>& B,
                            const bool test,
                            const bool singular)
{
    if(CPU)
    {
        rocblas_int info;
        rocblas_init<T>(hA, true);
        rocblas_init<T>(hB, false);

        for(rocblas_int b = 0; b < bc; ++b)
        {
            for(rocblas_int i = 0; i < n; i++)
            {
                for(rocblas_int j = 0; j < n; j++)
                {
                    if(i == j)
                    {
                        hA[b][i + j * lda] = std::real(hA[b][i + j * lda]) + 400;
                        hB[b][i + j * ldb] = std::real(hB[b][i + j * ldb]) + 400;
                    }
                    else
                    {
                        hA[b][i + j * lda] -= 4;
                    }
                }
            }

            if(singular && (b == bc / 4 || b == bc / 2 || b == bc - 1))
            {
                // make some matrices B not positive definite
                // always the same elements for debugging purposes
                // the algorithm must detect the lower order of the principal minors <= 0
                // in those matrices in the batch that are non positive definite
                rocblas_int i = n / 4 + b;
                i -= (i / n) * n;
                hB[b][i + i * ldb] = 0;
                i = n / 2 + b;
                i -= (i / n) * n;
                hB[b][i + i * ldb] = 0;
                i = n - 1 + b;
                i -= (i / n) * n;
                hB[b][i + i * ldb] = 0;
            }

            // store A and B for testing purposes
            if(test && evect != rocblas_evect_none)
            {
                for(rocblas_int i = 0; i < n; i++)
                {
                    for(rocblas_int j = 0; j < n; j++)
                    {
                        if(itype != rocblas_eform_bax)
                        {
                            A[b][i + j * lda] = hA[b][i + j * lda];
                            B[b][i + j * ldb] = hB[b][i + j * ldb];
                        }
                        else
                        {
                            A[b][i + j * lda] = hB[b][i + j * ldb];
                            B[b][i + j * ldb] = hA[b][i + j * lda];
                        }
                    }
                }
            }
        }
    }

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

template <bool STRIDED, typename T, typename Td, typename Ud, typename Vd, typename Th, typename Uh, typename Vh>
void sygvdj_hegvdj_getError(const rocblas_handle handle,
                            const rocblas_eform itype,
                            const rocblas_evect evect,
                            const rocblas_fill uplo,
                            const rocblas_int n,
                            Td& dA,
                            const rocblas_int lda,
                            const rocblas_stride stA,
                            Td& dB,
                            const rocblas_int ldb,
                            const rocblas_stride stB,
                            Ud& dD,
                            const rocblas_stride stD,
                            Vd& dInfo,
                            const rocblas_int bc,
                            Th& hA,
                            Th& hARes,
                            Th& hB,
                            Uh& hD,
                            Uh& hDRes,
                            Vh& hInfo,
                            Vh& hInfoRes,
                            double* max_err,
                            const bool singular)
{
    constexpr bool COMPLEX = rocblas_is_complex<T>;
    using S = decltype(std::real(T{}));

    rocblas_int lwork = (COMPLEX ? 2 * n - 1 : 3 * n - 1);
    rocblas_int lrwork = (COMPLEX ? 3 * n - 2 : 0);
    std::vector<T> work(lwork);
    std::vector<S> rwork(lrwork);
    host_strided_batch_vector<T> A(lda * n, 1, lda * n, bc);
    host_strided_batch_vector<T> B(ldb * n, 1, ldb * n, bc);

    // input data initialization
    sygvdj_hegvdj_initData<true, true, T>(handle, itype, evect, n, dA, lda, stA, dB, ldb, stB, bc,
                                          hA, hB, A, B, true, singular);

    // execute computations
    // GPU lapack
    CHECK_ROCBLAS_ERROR(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n, dA.data(),
                                                lda, stA, dB.data(), ldb, stB, dD.data(), stD,
                                                dInfo.data(), bc));

    CHECK_HIP_ERROR(hDRes.transfer_from(dD));
    CHECK_HIP_ERROR(hInfoRes.transfer_from(dInfo));
    if(evect != rocblas_evect_none)
        CHECK_HIP_ERROR(hARes.transfer_from(dA));

    // CPU lapack
    for(rocblas_int b = 0; b < bc; ++b)
    {
        cpu_sygv_hegv(itype, evect, uplo, n, hA[b], lda, hB[b], ldb, hD[b], work.data(), lwork,
                      rwork.data(), hInfo[b]);
    }

    // (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.
    // We do test with indefinite matrices B).

    // check info for non-convergence and/or positive-definiteness
    *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;
    }

    double err;

    for(rocblas_int b = 0; b < bc; ++b)
    {
        if(evect == rocblas_evect_none)
        {
            // only eigenvalues needed; can compare with LAPACK

            // error is ||hD - hDRes|| / ||hD||
            // using frobenius norm
            if(hInfoRes[b][0] == 0)
            {
                err = norm_error('F', 1, n, 1, hD[b], hDRes[b]);
                *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
            if(hInfoRes[b][0] == 0)
            {
                T alpha = 1;
                T beta = 0;

                // hARes contains eigenvectors x
                // compute B*x (or A*x) and store in hB
                cpu_symm_hemm(rocblas_side_left, uplo, n, n, alpha, B[b], ldb, hARes[b], lda, beta,
                              hB[b], ldb);

                if(itype == rocblas_eform_ax)
                {
                    // problem is A*x = (lambda)*B*x

                    // compute (1/lambda)*A*x and store in hA
                    for(int j = 0; j < n; j++)
                    {
                        alpha = T(1) / hDRes[b][j];
                        cpu_symv_hemv(uplo, n, alpha, A[b], lda, hARes[b] + j * lda, 1, beta,
                                      hA[b] + j * lda, 1);
                    }

                    // move B*x into hARes
                    for(rocblas_int i = 0; i < n; i++)
                        for(rocblas_int j = 0; j < n; j++)
                            hARes[b][i + j * lda] = hB[b][i + j * ldb];
                }
                else
                {
                    // problem is A*B*x = (lambda)*x or B*A*x = (lambda)*x

                    // compute (1/lambda)*A*B*x or (1/lambda)*B*A*x and store in hA
                    for(int j = 0; j < n; j++)
                    {
                        alpha = T(1) / hDRes[b][j];
                        cpu_symv_hemv(uplo, n, alpha, A[b], lda, hB[b] + j * ldb, 1, beta,
                                      hA[b] + j * lda, 1);
                    }
                }

                // error is ||hA - hARes|| / ||hA||
                // using frobenius norm
                err = norm_error('F', n, n, lda, hA[b], hARes[b]);
                *max_err = err > *max_err ? err : *max_err;
            }
        }
    }
}

template <bool STRIDED, typename T, typename Td, typename Ud, typename Vd, typename Th, typename Uh, typename Vh>
void sygvdj_hegvdj_getPerfData(const rocblas_handle handle,
                               const rocblas_eform itype,
                               const rocblas_evect evect,
                               const rocblas_fill uplo,
                               const rocblas_int n,
                               Td& dA,
                               const rocblas_int lda,
                               const rocblas_stride stA,
                               Td& dB,
                               const rocblas_int ldb,
                               const rocblas_stride stB,
                               Ud& dD,
                               const rocblas_stride stD,
                               Vd& dInfo,
                               const rocblas_int bc,
                               Th& hA,
                               Th& hB,
                               Uh& hD,
                               Vh& hInfo,
                               double* gpu_time_used,
                               double* cpu_time_used,
                               const rocblas_int hot_calls,
                               const int profile,
                               const bool profile_kernels,
                               const bool perf,
                               const bool singular)
{
    host_strided_batch_vector<T> A(1, 1, 1, 1);
    host_strided_batch_vector<T> B(1, 1, 1, 1);

    if(!perf)
    {
        // cpu-lapack performance (only if not in perf mode)
        *cpu_time_used = nan("");
    }

    sygvdj_hegvdj_initData<true, false, T>(handle, itype, evect, n, dA, lda, stA, dB, ldb, stB, bc,
                                           hA, hB, A, B, false, singular);

    // cold calls
    for(int iter = 0; iter < 2; iter++)
    {
        sygvdj_hegvdj_initData<false, true, T>(handle, itype, evect, n, dA, lda, stA, dB, ldb, stB,
                                               bc, hA, hB, A, B, false, singular);

        CHECK_ROCBLAS_ERROR(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n,
                                                    dA.data(), lda, stA, dB.data(), ldb, stB,
                                                    dD.data(), stD, dInfo.data(), bc));
    }

    // gpu-lapack performance
    hipStream_t stream;
    CHECK_ROCBLAS_ERROR(rocblas_get_stream(handle, &stream));
    double start;

    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++)
    {
        sygvdj_hegvdj_initData<false, true, T>(handle, itype, evect, n, dA, lda, stA, dB, ldb, stB,
                                               bc, hA, hB, A, B, false, singular);

        start = get_time_us_sync(stream);
        rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n, dA.data(), lda, stA,
                                dB.data(), ldb, stB, dD.data(), stD, dInfo.data(), bc);
        *gpu_time_used += get_time_us_sync(stream) - start;
    }
    *gpu_time_used /= hot_calls;
}

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

    // get arguments
    rocblas_local_handle handle;
    char itypeC = argus.get<char>("itype");
    char evectC = argus.get<char>("evect");
    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 ldb = argus.get<rocblas_int>("ldb", n);
    rocblas_stride stA = argus.get<rocblas_stride>("strideA", lda * n);
    rocblas_stride stB = argus.get<rocblas_stride>("strideB", ldb * n);
    rocblas_stride stD = argus.get<rocblas_stride>("strideD", n);

    rocblas_eform itype = char2rocblas_eform(itypeC);
    rocblas_evect evect = char2rocblas_evect(evectC);
    rocblas_fill uplo = char2rocblas_fill(uploC);
    rocblas_int bc = argus.batch_count;
    rocblas_int hot_calls = argus.iters;

    rocblas_stride stARes = (argus.unit_check || argus.norm_check) ? stA : 0;
    rocblas_stride stDRes = (argus.unit_check || argus.norm_check) ? stD : 0;

    // check non-supported values
    if(uplo == rocblas_fill_full || evect == rocblas_evect_tridiagonal)
    {
        if(BATCHED)
            EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n,
                                                          (T* const*)nullptr, lda, stA,
                                                          (T* const*)nullptr, ldb, stB, (S*)nullptr,
                                                          stD, (rocblas_int*)nullptr, bc),
                                  rocblas_status_invalid_value);
        else
            EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n,
                                                          (T*)nullptr, lda, stA, (T*)nullptr, ldb,
                                                          stB, (S*)nullptr, stD,
                                                          (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_B = size_t(ldb) * n;
    size_t size_D = size_t(n);
    double max_error = 0, gpu_time_used = 0, cpu_time_used = 0;

    size_t size_ARes = (argus.unit_check || argus.norm_check) ? size_A : 0;
    size_t size_DRes = (argus.unit_check || argus.norm_check) ? size_D : 0;

    // check invalid sizes
    bool invalid_size = (n < 0 || lda < n || ldb < n || bc < 0);
    if(invalid_size)
    {
        if(BATCHED)
            EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n,
                                                          (T* const*)nullptr, lda, stA,
                                                          (T* const*)nullptr, ldb, stB, (S*)nullptr,
                                                          stD, (rocblas_int*)nullptr, bc),
                                  rocblas_status_invalid_size);
        else
            EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n,
                                                          (T*)nullptr, lda, stA, (T*)nullptr, ldb,
                                                          stB, (S*)nullptr, stD,
                                                          (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 || !USE_ROCBLAS_REALLOC_ON_DEMAND)
    {
        CHECK_ROCBLAS_ERROR(rocblas_start_device_memory_size_query(handle));
        if(BATCHED)
            CHECK_ALLOC_QUERY(rocsolver_sygvdj_hegvdj(
                STRIDED, handle, itype, evect, uplo, n, (T* const*)nullptr, lda, stA,
                (T* const*)nullptr, ldb, stB, (S*)nullptr, stD, (rocblas_int*)nullptr, bc));
        else
            CHECK_ALLOC_QUERY(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n,
                                                      (T*)nullptr, lda, stA, (T*)nullptr, ldb, stB,
                                                      (S*)nullptr, stD, (rocblas_int*)nullptr, bc));

        size_t size;
        CHECK_ROCBLAS_ERROR(rocblas_stop_device_memory_size_query(handle, &size));
        if(argus.mem_query)
        {
            rocsolver_bench_inform(inform_mem_query, size);
            return;
        }

        CHECK_ROCBLAS_ERROR(rocblas_set_device_memory_size(handle, size));
    }

    // memory allocations (all cases)
    // host
    host_strided_batch_vector<S> hD(size_D, 1, stD, bc);
    host_strided_batch_vector<S> hDRes(size_DRes, 1, stDRes, 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<S> dD(size_D, 1, stD, bc);
    device_strided_batch_vector<rocblas_int> dInfo(1, 1, 1, bc);
    if(size_D)
        CHECK_HIP_ERROR(dD.memcheck());
    CHECK_HIP_ERROR(dInfo.memcheck());

    if(BATCHED)
    {
        // memory allocations
        host_batch_vector<T> hA(size_A, 1, bc);
        host_batch_vector<T> hARes(size_ARes, 1, bc);
        host_batch_vector<T> hB(size_B, 1, bc);
        device_batch_vector<T> dA(size_A, 1, bc);
        device_batch_vector<T> dB(size_B, 1, bc);
        if(size_A)
            CHECK_HIP_ERROR(dA.memcheck());
        if(size_B)
            CHECK_HIP_ERROR(dB.memcheck());

        // check quick return
        if(n == 0 || bc == 0)
        {
            EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n,
                                                          dA.data(), lda, stA, dB.data(), ldb, stB,
                                                          dD.data(), stD, 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)
            sygvdj_hegvdj_getError<STRIDED, T>(handle, itype, evect, uplo, n, dA, lda, stA, dB, ldb,
                                               stB, dD, stD, dInfo, bc, hA, hARes, hB, hD, hDRes,
                                               hInfo, hInfoRes, &max_error, argus.singular);

        // collect performance data
        if(argus.timing)
            sygvdj_hegvdj_getPerfData<STRIDED, T>(
                handle, itype, evect, uplo, n, dA, lda, stA, dB, ldb, stB, dD, stD, dInfo, bc, hA,
                hB, hD, hInfo, &gpu_time_used, &cpu_time_used, hot_calls, argus.profile,
                argus.profile_kernels, argus.perf, argus.singular);
    }

    else
    {
        // memory allocations
        host_strided_batch_vector<T> hA(size_A, 1, stA, bc);
        host_strided_batch_vector<T> hARes(size_ARes, 1, stARes, bc);
        host_strided_batch_vector<T> hB(size_B, 1, stB, bc);
        device_strided_batch_vector<T> dA(size_A, 1, stA, bc);
        device_strided_batch_vector<T> dB(size_B, 1, stB, bc);
        if(size_A)
            CHECK_HIP_ERROR(dA.memcheck());
        if(size_B)
            CHECK_HIP_ERROR(dB.memcheck());

        // check quick return
        if(n == 0 || bc == 0)
        {
            EXPECT_ROCBLAS_STATUS(rocsolver_sygvdj_hegvdj(STRIDED, handle, itype, evect, uplo, n,
                                                          dA.data(), lda, stA, dB.data(), ldb, stB,
                                                          dD.data(), stD, 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)
            sygvdj_hegvdj_getError<STRIDED, T>(handle, itype, evect, uplo, n, dA, lda, stA, dB, ldb,
                                               stB, dD, stD, dInfo, bc, hA, hARes, hB, hD, hDRes,
                                               hInfo, hInfoRes, &max_error, argus.singular);

        // collect performance data
        if(argus.timing)
            sygvdj_hegvdj_getPerfData<STRIDED, T>(
                handle, itype, evect, uplo, n, dA, lda, stA, dB, ldb, stB, dD, stD, dInfo, bc, hA,
                hB, hD, hInfo, &gpu_time_used, &cpu_time_used, hot_calls, argus.profile,
                argus.profile_kernels, argus.perf, argus.singular);
    }

    // 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("itype", "evect", "uplo", "n", "lda", "ldb", "strideD",
                                       "batch_c");
                rocsolver_bench_output(itypeC, evectC, uploC, n, lda, ldb, stD, bc);
            }
            else if(STRIDED)
            {
                rocsolver_bench_output("itype", "evect", "uplo", "n", "lda", "ldb", "strideA",
                                       "strideB", "strideD", "batch_c");
                rocsolver_bench_output(itypeC, evectC, uploC, n, lda, ldb, stA, stB, stD, bc);
            }
            else
            {
                rocsolver_bench_output("itype", "evect", "uplo", "n", "lda", "ldb");
                rocsolver_bench_output(itypeC, evectC, uploC, n, lda, ldb);
            }
            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();
        }
        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_SYGVDJ_HEGVDJ(...) \
    extern template void testing_sygvdj_hegvdj<__VA_ARGS__>(Arguments&);

INSTANTIATE(EXTERN_TESTING_SYGVDJ_HEGVDJ, FOREACH_MATRIX_DATA_LAYOUT, FOREACH_SCALAR_TYPE, APPLY_STAMP)
