TheRock/rocm-libraries/projects/hipblas/clients/include/solver/testing_getrf.hpp

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#include <fstream>
#include <iostream>
#include <stdlib.h>
#include <vector>

#include "testing_common.hpp"

using hipblasGetrfModel = ArgumentModel<e_a_type, e_N, e_lda>;

inline void testname_getrf(const Arguments& arg, std::string& name)
{
    hipblasGetrfModel{}.test_name(arg, name);
}

template <typename T>
void testing_getrf_bad_arg(const Arguments& arg)
{
    bool FORTRAN        = arg.api == hipblas_client_api::FORTRAN;
    auto hipblasGetrfFn = FORTRAN ? hipblasGetrf<T, true> : hipblasGetrf<T, false>;

    hipblasLocalHandle handle(arg);
    int64_t            N         = 101;
    int64_t            M         = N;
    int64_t            lda       = 102;
    int64_t            Ipiv_size = std::min(M, N);

    host_matrix<T> hA(M, N, lda);

    // Allocate device memory
    device_matrix<T> dA(M, N, lda);

    device_matrix<int> dIpiv(1, Ipiv_size, 1);
    device_vector<int> dInfo(1);

    EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(nullptr, N, dA, lda, dIpiv, dInfo),
                          HIPBLAS_STATUS_NOT_INITIALIZED);

    EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(handle, -1, dA, lda, dIpiv, dInfo),
                          HIPBLAS_STATUS_INVALID_VALUE);

    EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(handle, N, dA, N - 1, dIpiv, dInfo),
                          HIPBLAS_STATUS_INVALID_VALUE);

    // If N == 0, A and ipiv can be nullptr
    CHECK_HIPBLAS_ERROR(hipblasGetrfFn(handle, 0, nullptr, lda, nullptr, dInfo));

    if(arg.bad_arg_all)
    {
        EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(handle, N, nullptr, lda, dIpiv, dInfo),
                              HIPBLAS_STATUS_INVALID_VALUE);
        EXPECT_HIPBLAS_STATUS(hipblasGetrfFn(handle, N, dA, lda, dIpiv, nullptr),
                              HIPBLAS_STATUS_INVALID_VALUE);
    }
}

template <typename T>
void testing_getrf(const Arguments& arg)
{
    using U             = real_t<T>;
    bool FORTRAN        = arg.api == hipblas_client_api::FORTRAN;
    auto hipblasGetrfFn = FORTRAN ? hipblasGetrf<T, true> : hipblasGetrf<T, false>;

    int M         = arg.N;
    int N         = arg.N;
    int lda       = arg.lda;
    int Ipiv_size = std::min(M, N);

    // Check to prevent memory allocation error
    if(M < 0 || N < 0 || lda < M)
    {
        return;
    }

    // Naming: dK is in GPU (device) memory. hK is in CPU (host) memory
    host_matrix<T>       hA(M, N, lda);
    host_matrix<T>       hA1(M, N, lda);
    host_matrix<int>     hIpiv(1, Ipiv_size, 1);
    host_matrix<int64_t> hIpiv64(1, Ipiv_size, 1);
    host_vector<int>     hInfo(1);
    host_vector<int>     hInfo1(1);

    // Allocate device memory
    device_matrix<T>   dA(M, N, lda);
    device_matrix<int> dIpiv(1, Ipiv_size, 1);
    device_vector<int> dInfo(1);

    // Check device memory allocation
    CHECK_DEVICE_ALLOCATION(dA.memcheck());
    CHECK_DEVICE_ALLOCATION(dIpiv.memcheck());
    CHECK_DEVICE_ALLOCATION(dInfo.memcheck());

    double             gpu_time_used{0}, hipblas_error{0};
    hipblasLocalHandle handle(arg);

    // Initial hA on CPU
    hipblas_init_matrix(hA, arg, hipblas_client_never_set_nan, hipblas_general_matrix, true);

    T* A = (T*)hA;
    // scale A to avoid singularities
    for(int i = 0; i < M; i++)
    {
        for(int j = 0; j < N; j++)
        {
            if(i == j)
                A[i + j * lda] += 400;
            else
                A[i + j * lda] -= 4;
        }
    }

    // Copy data from CPU to device
    CHECK_HIP_ERROR(dA.transfer_from(hA));
    CHECK_HIP_ERROR(hipMemset(dIpiv, 0, Ipiv_size * sizeof(int)));
    CHECK_HIP_ERROR(hipMemset(dInfo, 0, sizeof(int)));

    if(arg.unit_check || arg.norm_check)
    {
        /* =====================================================================
            HIPBLAS
        =================================================================== */
        CHECK_HIPBLAS_ERROR(hipblasGetrfFn(handle, N, dA, lda, dIpiv, dInfo));

        // Copy output from device to CPU
        CHECK_HIP_ERROR(hA1.transfer_from(dA));
        CHECK_HIP_ERROR(hIpiv.transfer_from(dIpiv));
        CHECK_HIP_ERROR(hipMemcpy(hInfo1, dInfo, sizeof(int), hipMemcpyDeviceToHost));

        /* =====================================================================
           CPU LAPACK
        =================================================================== */
        for(int i = 0; i < Ipiv_size; i++)
            hIpiv64[0][i] = hIpiv[0][i];

        hInfo[0] = ref_getrf(M, N, hA.data(), lda, hIpiv64.data());

        hipblas_error = norm_check_general<T>('F', M, N, lda, hA, hA1);
        if(arg.unit_check)
        {
            U      eps       = std::numeric_limits<U>::epsilon();
            double tolerance = eps * 2000;

            unit_check_error(hipblas_error, tolerance);
        }
    }

    if(arg.timing)
    {
        hipStream_t stream;
        CHECK_HIPBLAS_ERROR(hipblasGetStream(handle, &stream));

        int runs = arg.cold_iters + arg.iters;
        for(int iter = 0; iter < runs; iter++)
        {
            if(iter == arg.cold_iters)
                gpu_time_used = get_time_us_sync(stream);

            CHECK_HIPBLAS_ERROR(hipblasGetrfFn(handle, N, dA, lda, dIpiv, dInfo));
        }
        gpu_time_used = get_time_us_sync(stream) - gpu_time_used;

        hipblasGetrfModel{}.log_args<T>(std::cout,
                                        arg,
                                        gpu_time_used,
                                        getrf_gflop_count<T>(N, M),
                                        ArgumentLogging::NA_value,
                                        hipblas_error);
    }
}