/* ************************************************************************
 * Copyright (C) 2020 Advanced Micro Devices, Inc. All rights Reserved.
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 * THE SOFTWARE.
 *
 * ************************************************************************ */

#pragma once
#ifndef TESTING_SPARSE_TO_DENSE_COO_HPP
#define TESTING_SPARSE_TO_DENSE_COO_HPP

#include "hipsparse_test_unique_ptr.hpp"
#include "unit.hpp"
#include "utility.hpp"

#include <hipsparse.h>
#include <string>
#include <typeinfo>

using namespace hipsparse_test;

void testing_sparse_to_dense_coo_bad_arg(void)
{
#if(!defined(CUDART_VERSION) || CUDART_VERSION >= 11020)
    int64_t safe_size = 100;
    int32_t m         = 10;
    int32_t n         = 10;
    int64_t nnz       = 10;
    int64_t ld        = m;

    hipsparseIndexBase_t        idxBase = HIPSPARSE_INDEX_BASE_ZERO;
    hipsparseSparseToDenseAlg_t alg     = HIPSPARSE_SPARSETODENSE_ALG_DEFAULT;
    hipsparseOrder_t            order   = HIPSPARSE_ORDER_COLUMN;

    // Index and data type
    hipsparseIndexType_t iType    = HIPSPARSE_INDEX_32I;
    hipDataType          dataType = HIP_R_32F;

    // Create handle
    std::unique_ptr<handle_struct> unique_ptr_handle(new handle_struct);
    hipsparseHandle_t              handle = unique_ptr_handle->handle;

    auto ddense_val_managed
        = hipsparse_unique_ptr{device_malloc(sizeof(float) * safe_size), device_free};
    auto dcoo_row_ind_managed
        = hipsparse_unique_ptr{device_malloc(sizeof(int32_t) * safe_size), device_free};
    auto dcoo_col_ind_managed
        = hipsparse_unique_ptr{device_malloc(sizeof(int32_t) * safe_size), device_free};
    auto dcoo_val_managed
        = hipsparse_unique_ptr{device_malloc(sizeof(float) * safe_size), device_free};
    auto dbuf_managed = hipsparse_unique_ptr{device_malloc(sizeof(char) * safe_size), device_free};

    float*   ddense_val   = (float*)ddense_val_managed.get();
    int32_t* dcoo_row_ind = (int32_t*)dcoo_row_ind_managed.get();
    int32_t* dcoo_col_ind = (int32_t*)dcoo_col_ind_managed.get();
    float*   dcoo_val     = (float*)dcoo_val_managed.get();
    void*    dbuf         = (void*)dbuf_managed.get();

    if(!ddense_val || !dcoo_row_ind || !dcoo_col_ind || !dcoo_val || !dbuf)
    {
        PRINT_IF_HIP_ERROR(hipErrorOutOfMemory);
        return;
    }

    // Matrix structures
    hipsparseSpMatDescr_t matA;
    hipsparseDnVecDescr_t matB;

    size_t bsize;

    // Create matrix structures
    verify_hipsparse_status_success(
        hipsparseCreateCoo(
            &matA, m, n, nnz, dcoo_row_ind, dcoo_col_ind, dcoo_val, iType, idxBase, dataType),
        "success");
    verify_hipsparse_status_success(
        hipsparseCreateDnMat(&matB, m, n, ld, ddense_val, dataType, order), "success");

    // SparseToDense buffer size
    verify_hipsparse_status_invalid_handle(
        hipsparseSparseToDense_bufferSize(nullptr, matA, matB, alg, &bsize));
    verify_hipsparse_status_invalid_pointer(
        hipsparseSparseToDense_bufferSize(handle, nullptr, matB, alg, &bsize),
        "Error: matA is nullptr");
    verify_hipsparse_status_invalid_pointer(
        hipsparseSparseToDense_bufferSize(handle, matA, nullptr, alg, &bsize),
        "Error: matB is nullptr");
    verify_hipsparse_status_invalid_pointer(
        hipsparseSparseToDense_bufferSize(handle, matA, matB, alg, nullptr),
        "Error: bsize is nullptr");

    // SparseToDense
    verify_hipsparse_status_invalid_handle(hipsparseSparseToDense(nullptr, matA, matB, alg, dbuf));
    verify_hipsparse_status_invalid_pointer(
        hipsparseSparseToDense(handle, nullptr, matB, alg, dbuf), "Error: matA is nullptr");
    verify_hipsparse_status_invalid_pointer(
        hipsparseSparseToDense(handle, matA, nullptr, alg, dbuf), "Error: matB is nullptr");
    // cuda returns success here
#if(!defined(CUDART_VERSION))
    verify_hipsparse_status_invalid_pointer(
        hipsparseSparseToDense(handle, matA, matB, alg, nullptr), "Error: dbuf is nullptr");
#endif

    // Destruct
    verify_hipsparse_status_success(hipsparseDestroySpMat(matA), "success");
    verify_hipsparse_status_success(hipsparseDestroyDnMat(matB), "success");
#endif
}

template <typename I, typename T>
hipsparseStatus_t testing_sparse_to_dense_coo(void)
{
#if(!defined(CUDART_VERSION) || CUDART_VERSION >= 11020)
    hipsparseIndexBase_t        idx_base = HIPSPARSE_INDEX_BASE_ZERO;
    hipsparseSparseToDenseAlg_t alg      = HIPSPARSE_SPARSETODENSE_ALG_DEFAULT;
    hipsparseOrder_t            order    = HIPSPARSE_ORDER_COLUMN;

    // Matrices are stored at the same path in matrices directory
    std::string filename = hipsparse_exepath() + "../matrices/nos3.bin";

    // Index and data type
    hipsparseIndexType_t typeI
        = (typeid(I) == typeid(int32_t)) ? HIPSPARSE_INDEX_32I : HIPSPARSE_INDEX_64I;
    hipDataType typeT = (typeid(T) == typeid(float))
                            ? HIP_R_32F
                            : ((typeid(T) == typeid(double))
                                   ? HIP_R_64F
                                   : ((typeid(T) == typeid(hipComplex) ? HIP_C_32F : HIP_C_64F)));

    // hipSPARSE handle
    std::unique_ptr<handle_struct> test_handle(new handle_struct);
    hipsparseHandle_t              handle = test_handle->handle;

    // Host structures
    std::vector<I> hcsr_row_ptr;
    std::vector<I> hcsr_col_ind;
    std::vector<T> hcsr_val;

    // Initial Data on CPU
    srand(12345ULL);

    I m;
    I n;
    I nnz;

    if(read_bin_matrix(filename.c_str(), m, n, nnz, hcsr_row_ptr, hcsr_col_ind, hcsr_val, idx_base)
       != 0)
    {
        fprintf(stderr, "Cannot open [read] %s\n", filename.c_str());
        return HIPSPARSE_STATUS_INTERNAL_ERROR;
    }

    I ld = m;

    // Fill host COO arrays
    std::vector<I> hcoo_row_ind(nnz);
    std::vector<I> hcoo_col_ind = hcsr_col_ind;
    std::vector<T> hcoo_val     = hcsr_val;

    for(I i = 0; i < m; i++)
    {
        I start = hcsr_row_ptr[i] - idx_base;
        I end   = hcsr_row_ptr[i + 1] - idx_base;

        for(I j = start; j < end; j++)
        {
            hcoo_row_ind[j] = i + idx_base;
        }
    }

    // allocate memory on device
    auto drow_managed   = hipsparse_unique_ptr{device_malloc(sizeof(I) * nnz), device_free};
    auto dcol_managed   = hipsparse_unique_ptr{device_malloc(sizeof(I) * nnz), device_free};
    auto dval_managed   = hipsparse_unique_ptr{device_malloc(sizeof(T) * nnz), device_free};
    auto ddense_managed = hipsparse_unique_ptr{device_malloc(sizeof(T) * ld * n), device_free};

    I* drow   = (I*)drow_managed.get();
    I* dcol   = (I*)dcol_managed.get();
    T* dval   = (T*)dval_managed.get();
    T* ddense = (T*)ddense_managed.get();

    if(!dval || !drow || !dcol || !ddense)
    {
        verify_hipsparse_status_success(HIPSPARSE_STATUS_ALLOC_FAILED,
                                        "!dval || !drow || !dcol || !ddense");
        return HIPSPARSE_STATUS_ALLOC_FAILED;
    }

    // Dense matrix
    std::vector<T> hdense(ld * n);

    // copy data from CPU to device
    CHECK_HIP_ERROR(hipMemcpy(drow, hcoo_row_ind.data(), sizeof(I) * nnz, hipMemcpyHostToDevice));
    CHECK_HIP_ERROR(hipMemcpy(dcol, hcoo_col_ind.data(), sizeof(I) * nnz, hipMemcpyHostToDevice));
    CHECK_HIP_ERROR(hipMemcpy(dval, hcoo_val.data(), sizeof(T) * nnz, hipMemcpyHostToDevice));

    // Create matrices
    hipsparseSpMatDescr_t matA;
    CHECK_HIPSPARSE_ERROR(
        hipsparseCreateCoo(&matA, m, n, nnz, drow, dcol, dval, typeI, idx_base, typeT));

    // Create dense matrix
    hipsparseDnMatDescr_t matB;
    CHECK_HIPSPARSE_ERROR(hipsparseCreateDnMat(&matB, m, n, ld, ddense, typeT, order));

    // Query SparseToDense buffer
    size_t bufferSize;
    CHECK_HIPSPARSE_ERROR(hipsparseSparseToDense_bufferSize(handle, matA, matB, alg, &bufferSize));

    void* buffer;
    CHECK_HIP_ERROR(hipMalloc(&buffer, bufferSize));

    CHECK_HIPSPARSE_ERROR(hipsparseSparseToDense(handle, matA, matB, alg, buffer));

    // copy output from device to CPU
    CHECK_HIP_ERROR(hipMemcpy(hdense.data(), ddense, sizeof(T) * ld * n, hipMemcpyDeviceToHost));

    // Query for warpSize
    hipDeviceProp_t prop;
    hipGetDeviceProperties(&prop, 0);

    std::vector<T> hdense_cpu(ld * n);

    for(I col = 0; col < n; ++col)
    {
        for(I row = 0; row < m; ++row)
        {
            hdense_cpu[row + ld * col] = make_DataType<T>(0.0);
        }
    }

    for(I i = 0; i < nnz; i++)
    {
        I row = hcoo_row_ind[i] - idx_base;
        I col = hcoo_col_ind[i] - idx_base;

        hdense_cpu[ld * col + row] = hcoo_val[i];
    }

    unit_check_general(m, n, ld, hdense_cpu.data(), hdense.data());

    CHECK_HIP_ERROR(hipFree(buffer));
    CHECK_HIPSPARSE_ERROR(hipsparseDestroySpMat(matA));
    CHECK_HIPSPARSE_ERROR(hipsparseDestroyDnMat(matB));
#endif

    return HIPSPARSE_STATUS_SUCCESS;
}

#endif // TESTING_SPARSE_TO_DENSE_COO_HPP
