/* ************************************************************************
 * Copyright 2016-2021 Advanced Micro Devices, Inc.
 *
 * ************************************************************************ */

#include "testing_dgmm.hpp"
#include "testing_dgmm_batched.hpp"
#include "testing_dgmm_strided_batched.hpp"
#include "utility.h"
#include <math.h>
#include <stdexcept>
#include <vector>

using ::testing::Combine;
using ::testing::TestWithParam;
using ::testing::Values;
using ::testing::ValuesIn;
using namespace std;

// only GCC/VS 2010 comes with std::tr1::tuple, but it is unnecessary,  std::tuple is good enough;

typedef std::tuple<vector<int>, char, double, int, bool> dgmm_tuple;

/* =====================================================================
README: This file contains testers to verify the correctness of
        BLAS routines with google test

        It is supposed to be played/used by advance / expert users
        Normal users only need to get the library routines without testers
     =================================================================== */

/* =====================================================================
Advance users only: BrainStorm the parameters but do not make artificial one which invalidates the
matrix.
like lda pairs with M, and "lda must >= M". case "lda < M" will be guarded by argument-checkers
inside API of course.
Yet, the goal of this file is to verify result correctness not argument-checkers.

Representative sampling is sufficient, endless brute-force sampling is not necessary
=================================================================== */

// vector of vector, each vector is a {M, N, lda, incx, ldc};
// add/delete as a group
const vector<vector<int>> matrix_size_range = {
    {-1, -1, -1, -1, -1}, {128, 128, 150, -1, 150}, {1000, 1000, 1000, 2, 1000},

    // TODO: rocBLAS dgmm is currently broken when (M != N && incx < 0 && side == L)
    // {128, 130, 150, -1, 150},
};

const vector<char> side_range = {
    'L',
    'R',
};

const vector<double> stride_scale_range = {1.0, 2.5};
const vector<int>    batch_count_range  = {-1, 1, 2, 10};

const bool is_fortran[] = {false, true};

/* ===============Google Unit Test==================================================== */

/* =====================================================================
     BLAS-3 dgmm:
=================================================================== */

/* ============================Setup Arguments======================================= */

// Please use "class Arguments" (see utility.hpp) to pass parameters to templated testers;
// Some routines may not touch/use certain "members" of objects "argus".
// like BLAS-1 Scal does not have lda, BLAS-2 DGMM does not have ldb, ldc;
// That is fine. These testers & routines will leave untouched members alone.
// Do not use std::tuple to directly pass parameters to testers
// by std:tuple, you have unpack it with extreme care for each one by like "std::get<0>" which is
// not intuitive and error-prone

Arguments setup_dgmm_arguments(dgmm_tuple tup)
{

    vector<int> matrix_size  = std::get<0>(tup);
    char        side         = std::get<1>(tup);
    double      stride_scale = std::get<2>(tup);
    int         batch_count  = std::get<3>(tup);
    bool        fortran      = std::get<4>(tup);

    Arguments arg;

    arg.M    = matrix_size[0];
    arg.N    = matrix_size[1];
    arg.lda  = matrix_size[2];
    arg.incx = matrix_size[3];
    arg.ldc  = matrix_size[4];

    arg.side_option = side;

    arg.timing = 0;

    arg.stride_scale = stride_scale;
    arg.batch_count  = batch_count;

    arg.fortran = fortran;

    return arg;
}

class dgmm_gtest : public ::TestWithParam<dgmm_tuple>
{
protected:
    dgmm_gtest() {}
    virtual ~dgmm_gtest() {}
    virtual void SetUp() {}
    virtual void TearDown() {}
};

// It appears that cublas and rocblas differ with their
// dgmm results. Disable tests until they match.
// TODO: re-enable tests when rocblas matches cublas.
TEST_P(dgmm_gtest, dgmm_gtest_float)
{
    // GetParam return a tuple. Tee setup routine unpack the tuple
    // and initializes arg(Arguments) which will be passed to testing routine
    // The Arguments data struture have physical meaning associated.
    // while the tuple is non-intuitive.

    Arguments arg = setup_dgmm_arguments(GetParam());

    hipblasStatus_t status = testing_dgmm<float>(arg);

    // if not success, then the input argument is problematic, so detect the error message
    if(status != HIPBLAS_STATUS_SUCCESS)
    {
        if(arg.M < 0 || arg.N < 0 || arg.lda < arg.M || arg.ldc < arg.M)
        {
            EXPECT_EQ(HIPBLAS_STATUS_INVALID_VALUE, status);
        }
        else
        {
            EXPECT_EQ(HIPBLAS_STATUS_SUCCESS, status); // fail
        }
    }
}

TEST_P(dgmm_gtest, dgmm_gtest_float_complex)
{
    // GetParam return a tuple. Tee setup routine unpack the tuple
    // and initializes arg(Arguments) which will be passed to testing routine
    // The Arguments data struture have physical meaning associated.
    // while the tuple is non-intuitive.

    Arguments arg = setup_dgmm_arguments(GetParam());

    hipblasStatus_t status = testing_dgmm<hipblasComplex>(arg);

    // if not success, then the input argument is problematic, so detect the error message
    if(status != HIPBLAS_STATUS_SUCCESS)
    {
        if(arg.M < 0 || arg.N < 0 || arg.lda < arg.M || arg.ldc < arg.M)
        {
            EXPECT_EQ(HIPBLAS_STATUS_INVALID_VALUE, status);
        }
        else
        {
            EXPECT_EQ(HIPBLAS_STATUS_SUCCESS, status); // fail
        }
    }
}

#ifndef __HIP_PLATFORM_NVCC__

TEST_P(dgmm_gtest, dgmm_batched_gtest_float)
{
    // GetParam return a tuple. Tee setup routine unpack the tuple
    // and initializes arg(Arguments) which will be passed to testing routine
    // The Arguments data struture have physical meaning associated.
    // while the tuple is non-intuitive.

    Arguments arg = setup_dgmm_arguments(GetParam());

    hipblasStatus_t status = testing_dgmm_batched<float>(arg);

    // if not success, then the input argument is problematic, so detect the error message
    if(status != HIPBLAS_STATUS_SUCCESS)
    {
        if(arg.M < 0 || arg.N < 0 || arg.lda < arg.M || arg.ldc < arg.M || arg.incx == 0
           || arg.batch_count < 0)
        {
            EXPECT_EQ(HIPBLAS_STATUS_INVALID_VALUE, status);
        }
        else
        {
            EXPECT_EQ(HIPBLAS_STATUS_SUCCESS, status); // fail
        }
    }
}

TEST_P(dgmm_gtest, dgmm_batched_gtest_float_complex)
{
    // GetParam return a tuple. Tee setup routine unpack the tuple
    // and initializes arg(Arguments) which will be passed to testing routine
    // The Arguments data struture have physical meaning associated.
    // while the tuple is non-intuitive.

    Arguments arg = setup_dgmm_arguments(GetParam());

    hipblasStatus_t status = testing_dgmm_batched<hipblasComplex>(arg);

    // if not success, then the input argument is problematic, so detect the error message
    if(status != HIPBLAS_STATUS_SUCCESS)
    {
        if(arg.M < 0 || arg.N < 0 || arg.lda < arg.M || arg.ldc < arg.M || arg.incx == 0
           || arg.batch_count < 0)
        {
            EXPECT_EQ(HIPBLAS_STATUS_INVALID_VALUE, status);
        }
        else
        {
            EXPECT_EQ(HIPBLAS_STATUS_SUCCESS, status); // fail
        }
    }
}

TEST_P(dgmm_gtest, dgmm_strided_batched_gtest_float)
{
    // GetParam return a tuple. Tee setup routine unpack the tuple
    // and initializes arg(Arguments) which will be passed to testing routine
    // The Arguments data struture have physical meaning associated.
    // while the tuple is non-intuitive.

    Arguments arg = setup_dgmm_arguments(GetParam());

    hipblasStatus_t status = testing_dgmm_strided_batched<float>(arg);

    // if not success, then the input argument is problematic, so detect the error message
    if(status != HIPBLAS_STATUS_SUCCESS)
    {
        if(arg.M < 0 || arg.N < 0 || arg.lda < arg.M || arg.ldc < arg.M || arg.incx == 0
           || arg.batch_count < 0)
        {
            EXPECT_EQ(HIPBLAS_STATUS_INVALID_VALUE, status);
        }
        else
        {
            EXPECT_EQ(HIPBLAS_STATUS_SUCCESS, status); // fail
        }
    }
}

TEST_P(dgmm_gtest, dgmm_strided_batched_gtest_float_complex)
{
    // GetParam return a tuple. Tee setup routine unpack the tuple
    // and initializes arg(Arguments) which will be passed to testing routine
    // The Arguments data struture have physical meaning associated.
    // while the tuple is non-intuitive.

    Arguments arg = setup_dgmm_arguments(GetParam());

    hipblasStatus_t status = testing_dgmm_strided_batched<hipblasComplex>(arg);

    // if not success, then the input argument is problematic, so detect the error message
    if(status != HIPBLAS_STATUS_SUCCESS)
    {
        if(arg.M < 0 || arg.N < 0 || arg.lda < arg.M || arg.ldc < arg.M || arg.incx == 0
           || arg.batch_count < 0)
        {
            EXPECT_EQ(HIPBLAS_STATUS_INVALID_VALUE, status);
        }
        else
        {
            EXPECT_EQ(HIPBLAS_STATUS_SUCCESS, status); // fail
        }
    }
}

#endif

// notice we are using vector of vector
// so each elment in xxx_range is a avector,
// ValuesIn take each element (a vector) and combine them and feed them to test_p
// The combinations are  { {M}, {incx,incy} {alpha, alphai, beta, betai}, {transA}, {stride_scale}, {batch_count} }

INSTANTIATE_TEST_SUITE_P(hipblasDgmm,
                         dgmm_gtest,
                         Combine(ValuesIn(matrix_size_range),
                                 ValuesIn(side_range),
                                 ValuesIn(stride_scale_range),
                                 ValuesIn(batch_count_range),
                                 ValuesIn(is_fortran)));