/* **************************************************************************
 * Copyright (C) 2020-2022 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 "client_util.hpp"
#include "clientcommon.hpp"
#include "lapack_host_reference.hpp"
#include "norm.hpp"
#include "rocsolver.hpp"
#include "rocsolver_arguments.hpp"
#include "rocsolver_test.hpp"

template <typename T, typename U>
void laswp_checkBadArgs(const rocblas_handle handle,
                        const rocblas_int n,
                        T dA,
                        const rocblas_int lda,
                        const rocblas_int k1,
                        const rocblas_int k2,
                        U dIpiv,
                        const rocblas_int inc)
{
    // handle
    EXPECT_ROCBLAS_STATUS(rocsolver_laswp(nullptr, n, dA, lda, k1, k2, dIpiv, inc),
                          rocblas_status_invalid_handle);

    // values
    // N/A

    // pointers
    EXPECT_ROCBLAS_STATUS(rocsolver_laswp(handle, n, (T) nullptr, lda, k1, k2, dIpiv, inc),
                          rocblas_status_invalid_pointer);
    EXPECT_ROCBLAS_STATUS(rocsolver_laswp(handle, n, dA, lda, k1, k2, (U) nullptr, inc),
                          rocblas_status_invalid_pointer);

    // quick return with invalid pointers
    EXPECT_ROCBLAS_STATUS(rocsolver_laswp(handle, 0, (T) nullptr, lda, k1, k2, dIpiv, inc),
                          rocblas_status_success);
}

template <typename T>
void testing_laswp_bad_arg()
{
    // safe arguments
    rocblas_local_handle handle;
    rocblas_int n = 1;
    rocblas_int lda = 1;
    rocblas_int k1 = 1;
    rocblas_int k2 = 2;
    rocblas_int inc = 1;

    // memory allocation
    device_strided_batch_vector<T> dA(1, 1, 1, 1);
    device_strided_batch_vector<rocblas_int> dIpiv(1, 1, 1, 1);
    CHECK_HIP_ERROR(dA.memcheck());
    CHECK_HIP_ERROR(dIpiv.memcheck());

    // check bad arguments
    laswp_checkBadArgs(handle, n, dA.data(), lda, k1, k2, dIpiv.data(), inc);
}

template <bool CPU, bool GPU, typename T, typename Td, typename Ud, typename Th, typename Uh>
void laswp_initData(const rocblas_handle handle,
                    const rocblas_int n,
                    Td& dA,
                    const rocblas_int lda,
                    const rocblas_int k1,
                    const rocblas_int k2,
                    Ud& dIpiv,
                    const rocblas_int inc,
                    Th& hA,
                    Uh& hIpiv)
{
    if(CPU)
    {
        // for simplicity consider number of rows m = lda
        rocblas_init<T>(hA, true);
        rocblas_init<rocblas_int>(hIpiv, true);

        // put indices in range [1, x]
        // for simplicity, consider x = lda as this is the number of rows
        for(rocblas_int i = 0; i < hIpiv.n(); ++i)
            hIpiv[0][i] = hIpiv[0][i] * lda < 10 ? 1 : hIpiv[0][i] * lda / 10;
    }

    if(GPU)
    {
        // copy data from CPU to device
        CHECK_HIP_ERROR(dA.transfer_from(hA));
        CHECK_HIP_ERROR(dIpiv.transfer_from(hIpiv));
    }
}

template <typename T, typename Td, typename Ud, typename Th, typename Uh>
void laswp_getError(const rocblas_handle handle,
                    const rocblas_int n,
                    Td& dA,
                    const rocblas_int lda,
                    const rocblas_int k1,
                    const rocblas_int k2,
                    Ud& dIpiv,
                    const rocblas_int inc,
                    Th& hA,
                    Th& hAr,
                    Uh& hIpiv,
                    double* max_err)
{
    // initialize data
    laswp_initData<true, true, T>(handle, n, dA, lda, k1, k2, dIpiv, inc, hA, hIpiv);

    // execute computations
    // GPU lapack
    CHECK_ROCBLAS_ERROR(rocsolver_laswp(handle, n, dA.data(), lda, k1, k2, dIpiv.data(), inc));
    CHECK_HIP_ERROR(hAr.transfer_from(dA));

    // CPU lapack
    cpu_laswp(n, hA[0], lda, k1, k2, hIpiv[0], inc);

    // error |hA - hAr| (elements must be identical)
    *max_err = 0;
    double diff;
    for(int i = 0; i < lda; i++)
    {
        for(int j = 0; j < n; j++)
        {
            diff = std::abs(hAr[0][i + j * lda] - hA[0][i + j * lda]);
            *max_err = diff > *max_err ? diff : *max_err;
        }
    }
}

template <typename T, typename Td, typename Ud, typename Th, typename Uh>
void laswp_getPerfData(const rocblas_handle handle,
                       const rocblas_int n,
                       Td& dA,
                       const rocblas_int lda,
                       const rocblas_int k1,
                       const rocblas_int k2,
                       Ud& dIpiv,
                       const rocblas_int inc,
                       Th& hA,
                       Uh& hIpiv,
                       double* gpu_time_used,
                       double* cpu_time_used,
                       const rocblas_int hot_calls,
                       const int profile,
                       const bool profile_kernels,
                       const bool perf)
{
    if(!perf)
    {
        laswp_initData<true, false, T>(handle, n, dA, lda, k1, k2, dIpiv, inc, hA, hIpiv);

        // cpu-lapack performance (only if not in perf mode)
        *cpu_time_used = get_time_us_no_sync();
        cpu_laswp(n, hA[0], lda, k1, k2, hIpiv[0], inc);
        *cpu_time_used = get_time_us_no_sync() - *cpu_time_used;
    }

    laswp_initData<true, false, T>(handle, n, dA, lda, k1, k2, dIpiv, inc, hA, hIpiv);

    // cold calls
    for(int iter = 0; iter < 2; iter++)
    {
        laswp_initData<false, true, T>(handle, n, dA, lda, k1, k2, dIpiv, inc, hA, hIpiv);

        CHECK_ROCBLAS_ERROR(rocsolver_laswp(handle, n, dA.data(), lda, k1, k2, dIpiv.data(), inc));
    }

    // 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(int iter = 0; iter < hot_calls; iter++)
    {
        laswp_initData<false, true, T>(handle, n, dA, lda, k1, k2, dIpiv, inc, hA, hIpiv);

        start = get_time_us_sync(stream);
        rocsolver_laswp(handle, n, dA.data(), lda, k1, k2, dIpiv.data(), inc);
        *gpu_time_used += get_time_us_sync(stream) - start;
    }
    *gpu_time_used /= hot_calls;
}

template <typename T>
void testing_laswp(Arguments& argus)
{
    // get arguments
    rocblas_local_handle handle;
    rocblas_int n = argus.get<rocblas_int>("n");
    rocblas_int k1 = argus.get<rocblas_int>("k1");
    rocblas_int k2 = argus.get<rocblas_int>("k2");
    rocblas_int lda = argus.get<rocblas_int>("lda", k2);
    rocblas_int inc = argus.get<rocblas_int>("incx");

    rocblas_int hot_calls = argus.iters;

    // check non-supported values
    // N/A

    // determine sizes
    size_t size_A = size_t(lda) * n;
    size_t size_P = k1 + size_t(k2 - k1) * abs(inc);
    double max_error = 0, gpu_time_used = 0, cpu_time_used = 0;

    size_t size_Ar = (argus.unit_check || argus.norm_check) ? size_A : 0;

    // check invalid sizes
    bool invalid_size = (n < 0 || lda < 1 || !inc || k1 < 1 || k2 < 1 || k2 < k1);
    if(invalid_size)
    {
        EXPECT_ROCBLAS_STATUS(
            rocsolver_laswp(handle, n, (T*)nullptr, lda, k1, k2, (rocblas_int*)nullptr, inc),
            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));
        CHECK_ALLOC_QUERY(
            rocsolver_laswp(handle, n, (T*)nullptr, lda, k1, k2, (rocblas_int*)nullptr, inc));

        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
    host_strided_batch_vector<T> hA(size_A, 1, size_A, 1);
    host_strided_batch_vector<T> hAr(size_Ar, 1, size_Ar, 1);
    host_strided_batch_vector<rocblas_int> hIpiv(size_P, 1, size_P, 1);
    device_strided_batch_vector<T> dA(size_A, 1, size_A, 1);
    device_strided_batch_vector<rocblas_int> dIpiv(size_P, 1, size_P, 1);
    if(size_A)
        CHECK_HIP_ERROR(dA.memcheck());
    if(size_P)
        CHECK_HIP_ERROR(dIpiv.memcheck());

    // check quick return
    if(n == 0)
    {
        EXPECT_ROCBLAS_STATUS(rocsolver_laswp(handle, n, dA.data(), lda, k1, k2, dIpiv.data(), inc),
                              rocblas_status_success);

        if(argus.timing)
            rocsolver_bench_inform(inform_quick_return);

        return;
    }

    // check computations
    if(argus.unit_check || argus.norm_check)
        laswp_getError<T>(handle, n, dA, lda, k1, k2, dIpiv, inc, hA, hAr, hIpiv, &max_error);

    // collect performance data
    if(argus.timing)
        laswp_getPerfData<T>(handle, n, dA, lda, k1, k2, dIpiv, inc, hA, hIpiv, &gpu_time_used,
                             &cpu_time_used, hot_calls, argus.profile, argus.profile_kernels,
                             argus.perf);

    // validate results for rocsolver-test
    // no tolerance
    if(argus.unit_check)
        ROCSOLVER_TEST_CHECK(T, max_error, 0);

    // output results for rocsolver-bench
    if(argus.timing)
    {
        if(!argus.perf)
        {
            rocsolver_bench_header("Arguments:");
            rocsolver_bench_output("n", "lda", "k1", "k2", "inc");
            rocsolver_bench_output(n, lda, k1, k2, inc);

            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_LASWP(...) extern template void testing_laswp<__VA_ARGS__>(Arguments&);

INSTANTIATE(EXTERN_TESTING_LASWP, FOREACH_SCALAR_TYPE, APPLY_STAMP)
