// Step 1978: CUDALibraryProfile
//
//  t1: buildLedger has cublas at 0.99 for compute.matrix
//  t2: cufft/compute.fft = 0.99
//  t3: thrust/compute.parallel = 0.97
//  t4: cudnn/compute.ml.inference = 0.99
//  t5: cublas/compute.statistics is not applicable (score 0 / notApplicable)

#include "CUDALibraryProfile.h"
#include <iostream>

namespace ws = whetstone;
static int p = 0, f = 0;
#define T(n) { std::cout << "  " << #n << "... "; }
#define P()  { std::cout << "PASS\n"; ++p; }
#define F(m) { std::cout << "FAIL: " << m << "\n"; ++f; }
#define C(c, m) if (!(c)) { F(m); return; }

void t1() {
    T(cublas_compute_matrix_0_99);
    auto ledger = ws::CUDALibraryProfile::buildLedger();
    C(ledger.score("cublas", "compute.matrix") == 0.99f, "cublas/compute.matrix = 0.99");
    auto rec = ledger.get("cublas", "compute.matrix");
    C(rec.has_value(),             "record present");
    C(!rec->preferredAPIs.empty(), "preferredAPIs non-empty");
    bool hasSgemm = false;
    for (const auto& api : rec->preferredAPIs)
        if (api.find("cublasSgemm") != std::string::npos) hasSgemm = true;
    C(hasSgemm, "cublasSgemm in preferredAPIs");
    P();
}

void t2() {
    T(cufft_compute_fft_0_99);
    auto ledger = ws::CUDALibraryProfile::buildLedger();
    C(ledger.score("cufft", "compute.fft") == 0.99f, "cufft/compute.fft = 0.99");
    auto rec = ledger.get("cufft", "compute.fft");
    C(rec.has_value(), "cufft record present");
    C(!rec->preferredAPIs.empty(), "cufft preferredAPIs non-empty");
    P();
}

void t3() {
    T(thrust_compute_parallel_0_97);
    auto ledger = ws::CUDALibraryProfile::buildLedger();
    C(ledger.score("thrust", "compute.parallel") == 0.97f, "thrust/compute.parallel = 0.97");
    C(ledger.score("thrust", "compute.sort")     == 0.97f, "thrust/compute.sort = 0.97");
    P();
}

void t4() {
    T(cudnn_ml_inference_0_99);
    auto ledger = ws::CUDALibraryProfile::buildLedger();
    C(ledger.score("cudnn", "compute.ml.inference") == 0.99f, "cudnn/ml.inference = 0.99");
    C(ledger.score("cudnn", "compute.ml.training")  == 0.97f, "cudnn/ml.training = 0.97");
    P();
}

void t5() {
    T(cublas_statistics_not_applicable);
    auto ledger = ws::CUDALibraryProfile::buildLedger();
    // cublas/compute.statistics has notApplicable=true, score=0
    C(ledger.score("cublas", "compute.statistics") == 0.0f, "cublas/compute.statistics = 0");
    auto rec = ledger.get("cublas", "compute.statistics");
    C(rec.has_value(),    "record exists");
    C(rec->notApplicable, "notApplicable = true");
    P();
}

int main() {
    std::cout << "Step 1978: CUDALibraryProfile\n";
    t1(); t2(); t3(); t4(); t5();
    std::cout << "\n" << p << "/" << (p + f) << " passed\n";
    return f > 0 ? 1 : 0;
}