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#include <hip/hip_runtime.h>
#include <hipblaslt/hipblaslt-ext.hpp>
#include <iostream>

#include "helper.h"

void simpleGemmAlphaVecExt(hipblasLtHandle_t  handle,
                           hipblasOperation_t trans_a,
                           hipblasOperation_t trans_b,
                           int64_t            m,
                           int64_t            n,
                           int64_t            k,
                           int64_t            batch_count,
                           float&             alpha,
                           float&             beta,
                           void*              d_a,
                           void*              d_b,
                           void*              d_c,
                           void*              d_d,
                           void*              d_alphaVec,
                           void*              d_workspace,
                           int64_t            max_workspace_size,
                           hipStream_t        stream);

int main()
{
    /** This is an example using hipblaslt extension API.
     *  This is a NN example with
     *  a = (m, k). lda = m
     *  b = (k, n). ldb = k
     *  c = d = (m, n). ldc = ldd = m
     */
    Runner<hipblasLtHalf, hipblasLtHalf, hipblasLtHalf, float, float> runner(
        1024, 512, 1024, 1, 1.f, 1.f, 32 * 1024 * 1024);

    runner.run([&runner] {
        simpleGemmAlphaVecExt(runner.handle,
                              HIPBLAS_OP_N,
                              HIPBLAS_OP_N,
                              runner.m,
                              runner.n,
                              runner.k,
                              runner.batch_count,
                              runner.alpha,
                              runner.beta,
                              runner.d_a,
                              runner.d_b,
                              runner.d_c,
                              runner.d_d,
                              runner.d_alphaVec,
                              runner.d_workspace,
                              runner.max_workspace_size,
                              runner.stream);
    });

    return 0;
}

void simpleGemmAlphaVecExt(hipblasLtHandle_t  handle,
                           hipblasOperation_t trans_a,
                           hipblasOperation_t trans_b,
                           int64_t            m,
                           int64_t            n,
                           int64_t            k,
                           int64_t            batch_count,
                           float&             alpha,
                           float&             beta,
                           void*              d_a,
                           void*              d_b,
                           void*              d_c,
                           void*              d_d,
                           void*              d_alphaVec,
                           void*              d_workspace,
                           int64_t            max_workspace_size,
                           hipStream_t        stream)
{
    hipblaslt_ext::GemmPreference gemmPref;
    gemmPref.setMaxWorkspaceBytes(max_workspace_size);
    hipblaslt_ext::Gemm gemm(
        handle, trans_a, trans_b, HIP_R_16F, HIP_R_16F, HIP_R_16F, HIP_R_16F, HIPBLAS_COMPUTE_32F);

    hipblaslt_ext::GemmEpilogue
        epilogue; // No action needed, default is HIPBLASLT_EPILOGUE_DEFAULT. (Gemm only)
    hipblaslt_ext::GemmInputs inputs;
    inputs.setA(d_a);
    inputs.setB(d_b);
    inputs.setC(d_c);
    inputs.setD(d_d);
    inputs.setAlpha(&alpha);
    inputs.setBeta(&beta);
    inputs.setScaleAlphaVec(d_alphaVec); // use AlphaVec mode
    gemm.setProblem(m, n, k, batch_count, epilogue, inputs);

    const int                                     request_solutions = 1;
    std::vector<hipblasLtMatmulHeuristicResult_t> heuristicResult;
    CHECK_HIPBLASLT_ERROR(gemm.algoGetHeuristic(request_solutions, gemmPref, heuristicResult));

    if(heuristicResult.empty())
    {
        std::cerr << "No valid solution found!" << std::endl;
        return;
    }

    // In this sample, the workspace is already allocated with max_workspace_size
    // If not, calculate the needed workspace_size and allocate d_workspace here
    // Then initialize gemm with calculated d_workspace and workspace_size
    // uint64_t workspace_size = 0;
    // for(int i = 0; i < returnedAlgoCount; i++)
    //     workspace_size = max(workspace_size, heuristicResult[i].workspaceSize);
    // CHECK_HIP_ERRORhipMalloc(&d_workspace, workspace_size));
    if(max_workspace_size < (int64_t)heuristicResult[0].workspaceSize)
    {
        std::cerr << "Allocated workspace size is too small!" << std::endl;
        return;
    }

    // Make sure to initialize every time when algo changes
    gemm.setMaxWorkspaceBytes(max_workspace_size);
    CHECK_HIPBLASLT_ERROR(gemm.initialize(heuristicResult[0].algo, d_workspace));
    CHECK_HIPBLASLT_ERROR(gemm.run(stream));
    return;
}
