// MIT License
//
// Copyright (c) 2017-2020 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.

#include "common_test_header.hpp"

// hipcub API
#include "hipcub/device/device_segmented_reduce.hpp"

std::vector<size_t> get_sizes()
{
    std::vector<size_t> sizes = {
        1024, 2048, 4096, 1792,
        1, 10, 53, 211, 500,
        2345, 11001, 34567,
        100000,
        (1 << 16) - 1220
    };
    const std::vector<size_t> random_sizes = test_utils::get_random_data<size_t>(5, 1, 1000000, rand());
    sizes.insert(sizes.end(), random_sizes.begin(), random_sizes.end());
    return sizes;
}

template<
    class Input,
    class Output,
    class ReduceOp = hipcub::Sum,
    int Init = 0, // as only integral types supported, int is used here even for floating point inputs
    unsigned int MinSegmentLength = 0,
    unsigned int MaxSegmentLength = 1000
>
struct params1
{
    using input_type = Input;
    using output_type = Output;
    using reduce_op_type = ReduceOp;
    static constexpr input_type init = Init;
    static constexpr unsigned int min_segment_length = MinSegmentLength;
    static constexpr unsigned int max_segment_length = MaxSegmentLength;
};

template<class Params>
class HipcubDeviceSegmentedReduceOp : public ::testing::Test {
public:
    using params = Params;
};

typedef ::testing::Types<
    params1<unsigned int, unsigned int, hipcub::Sum>,
    params1<int, int, hipcub::Sum, -100, 0, 10000>,
    params1<double, double, hipcub::Min, 1000, 0, 10000>,
    params1<int, short, hipcub::Max, 10, 1000, 10000>,
    params1<short, double, hipcub::Sum, 5, 1, 1000>,
    params1<float, double, hipcub::Max, 50, 2, 10>,
    params1<float, float, hipcub::Sum, 123, 100, 200>
> Params1;

TYPED_TEST_SUITE(HipcubDeviceSegmentedReduceOp, Params1);

TYPED_TEST(HipcubDeviceSegmentedReduceOp, Reduce)
{
    using input_type = typename TestFixture::params::input_type;
    using output_type = typename TestFixture::params::output_type;
    using reduce_op_type = typename TestFixture::params::reduce_op_type;

    using result_type = output_type;
    using offset_type = unsigned int;

    constexpr input_type init = TestFixture::params::init;
    const bool debug_synchronous = false;
    reduce_op_type reduce_op;

    std::random_device rd;
    std::default_random_engine gen(rd());

    std::uniform_int_distribution<size_t> segment_length_dis(
        TestFixture::params::min_segment_length,
        TestFixture::params::max_segment_length
    );

    const std::vector<size_t> sizes = get_sizes();
    for(size_t size : sizes)
    {
        for (size_t seed_index = 0; seed_index < random_seeds_count + seed_size; seed_index++)
        {
            unsigned int seed_value = seed_index < random_seeds_count  ? rand() : seeds[seed_index - random_seeds_count];
            SCOPED_TRACE(testing::Message() << "with seed= " << seed_value);
            SCOPED_TRACE(testing::Message() << "with size = " << size);

            hipStream_t stream = 0; // default

            // Generate data and calculate expected results
            std::vector<output_type> aggregates_expected;

            std::vector<input_type> values_input = test_utils::get_random_data<input_type>(
                size,
                0,
                100,
                seed_value
            );

            std::vector<offset_type> offsets;
            unsigned int segments_count = 0;
            size_t offset = 0;
            while(offset < size)
            {
                const size_t segment_length = segment_length_dis(gen);
                offsets.push_back(offset);

                const size_t end = std::min(size, offset + segment_length);
                result_type aggregate = init;
                for(size_t i = offset; i < end; i++)
                {
                    aggregate = reduce_op(aggregate, static_cast<result_type>(values_input[i]));
                }
                aggregates_expected.push_back(aggregate);

                segments_count++;
                offset += segment_length;
            }
            offsets.push_back(size);

            input_type * d_values_input;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_values_input, size * sizeof(input_type)));
            HIP_CHECK(
                hipMemcpy(
                    d_values_input, values_input.data(),
                    size * sizeof(input_type),
                    hipMemcpyHostToDevice
                )
            );

            offset_type * d_offsets;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_offsets, (segments_count + 1) * sizeof(offset_type)));
            HIP_CHECK(
                hipMemcpy(
                    d_offsets, offsets.data(),
                    (segments_count + 1) * sizeof(offset_type),
                    hipMemcpyHostToDevice
                )
            );

            output_type * d_aggregates_output;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_aggregates_output, segments_count * sizeof(output_type)));

            size_t temporary_storage_bytes;

            HIP_CHECK(
                hipcub::DeviceSegmentedReduce::Reduce(
                    nullptr, temporary_storage_bytes,
                    d_values_input, d_aggregates_output,
                    segments_count,
                    d_offsets, d_offsets + 1,
                    reduce_op, init,
                    stream, debug_synchronous
                )
            );

            ASSERT_GT(temporary_storage_bytes, 0U);

            void * d_temporary_storage;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_temporary_storage, temporary_storage_bytes));

            HIP_CHECK(
                hipcub::DeviceSegmentedReduce::Reduce(
                    d_temporary_storage, temporary_storage_bytes,
                    d_values_input, d_aggregates_output,
                    segments_count,
                    d_offsets, d_offsets + 1,
                    reduce_op, init,
                    stream, debug_synchronous
                )
            );

            HIP_CHECK(hipFree(d_temporary_storage));

            std::vector<output_type> aggregates_output(segments_count);
            HIP_CHECK(
                hipMemcpy(
                    aggregates_output.data(), d_aggregates_output,
                    segments_count * sizeof(output_type),
                    hipMemcpyDeviceToHost
                )
            );

            HIP_CHECK(hipFree(d_values_input));
            HIP_CHECK(hipFree(d_offsets));
            HIP_CHECK(hipFree(d_aggregates_output));

            for(size_t i = 0; i < segments_count; i++)
            {
                if(std::is_integral<output_type>::value)
                {
                    ASSERT_EQ(aggregates_output[i], aggregates_expected[i]);
                }
                else
                {
                    auto diff = std::max<output_type>(
                        std::abs(0.01 * aggregates_expected[i]), output_type(0.01)
                    );
                    ASSERT_NEAR(aggregates_output[i], aggregates_expected[i], diff);
                }
            }
        }
    }
}

template<
    class Input,
    class Output,
    unsigned int MinSegmentLength = 0,
    unsigned int MaxSegmentLength = 1000
>
struct params2
{
    using input_type = Input;
    using output_type = Output;
    static constexpr unsigned int min_segment_length = MinSegmentLength;
    static constexpr unsigned int max_segment_length = MaxSegmentLength;
};

template<class Params>
class HipcubDeviceSegmentedReduce : public ::testing::Test {
public:
    using params = Params;
};

typedef ::testing::Types<
    params2<unsigned int, unsigned int>,
    params2<int, int, 0, 10000>,
    params2<double, double, 0, 10000>,
    params2<int, long long, 1000, 10000>,
    params2<float, double, 2, 10>,
    params2<float, float, 100, 200>
> Params2;

TYPED_TEST_SUITE(HipcubDeviceSegmentedReduce, Params2);

TYPED_TEST(HipcubDeviceSegmentedReduce, Sum)
{
    using input_type = typename TestFixture::params::input_type;
    using output_type = typename TestFixture::params::output_type;
    using reduce_op_type = typename hipcub::Sum;
    using result_type = output_type;
    using offset_type = unsigned int;

    constexpr input_type init = input_type(0);
    const bool debug_synchronous = false;
    reduce_op_type reduce_op;


    std::random_device rd;
    std::default_random_engine gen(rd());

    std::uniform_int_distribution<size_t> segment_length_dis(
        TestFixture::params::min_segment_length,
        TestFixture::params::max_segment_length
    );

    const std::vector<size_t> sizes = get_sizes();
    for(size_t size : sizes)
    {
        for (size_t seed_index = 0; seed_index < random_seeds_count + seed_size; seed_index++)
        {
            unsigned int seed_value = seed_index < random_seeds_count  ? rand() : seeds[seed_index - random_seeds_count];
            SCOPED_TRACE(testing::Message() << "with seed= " << seed_value);
            SCOPED_TRACE(testing::Message() << "with size = " << size);

            hipStream_t stream = 0; // default

            // Generate data and calculate expected results
            std::vector<output_type> aggregates_expected;

            std::vector<input_type> values_input = test_utils::get_random_data<input_type>(
                size,
                0,
                100,
                seed_value
            );

            std::vector<offset_type> offsets;
            unsigned int segments_count = 0;
            size_t offset = 0;
            while(offset < size)
            {
                const size_t segment_length = segment_length_dis(gen);
                offsets.push_back(offset);

                const size_t end = std::min(size, offset + segment_length);
                result_type aggregate = init;
                for(size_t i = offset; i < end; i++)
                {
                    aggregate = reduce_op(aggregate, static_cast<result_type>(values_input[i]));
                }
                aggregates_expected.push_back(aggregate);

                segments_count++;
                offset += segment_length;
            }
            offsets.push_back(size);

            input_type * d_values_input;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_values_input, size * sizeof(input_type)));
            HIP_CHECK(
                hipMemcpy(
                    d_values_input, values_input.data(),
                    size * sizeof(input_type),
                    hipMemcpyHostToDevice
                )
            );

            offset_type * d_offsets;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_offsets, (segments_count + 1) * sizeof(offset_type)));
            HIP_CHECK(
                hipMemcpy(
                    d_offsets, offsets.data(),
                    (segments_count + 1) * sizeof(offset_type),
                    hipMemcpyHostToDevice
                )
            );

            output_type * d_aggregates_output;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_aggregates_output, segments_count * sizeof(output_type)));

            size_t temporary_storage_bytes;

            HIP_CHECK(
                hipcub::DeviceSegmentedReduce::Sum(
                    nullptr, temporary_storage_bytes,
                    d_values_input, d_aggregates_output,
                    segments_count,
                    d_offsets, d_offsets + 1,
                    stream, debug_synchronous
                )
            );

            ASSERT_GT(temporary_storage_bytes, 0U);

            void * d_temporary_storage;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_temporary_storage, temporary_storage_bytes));

            HIP_CHECK(
                hipcub::DeviceSegmentedReduce::Sum(
                    d_temporary_storage, temporary_storage_bytes,
                    d_values_input, d_aggregates_output,
                    segments_count,
                    d_offsets, d_offsets + 1,
                    stream, debug_synchronous
                )
            );

            HIP_CHECK(hipFree(d_temporary_storage));

            std::vector<output_type> aggregates_output(segments_count);
            HIP_CHECK(
                hipMemcpy(
                    aggregates_output.data(), d_aggregates_output,
                    segments_count * sizeof(output_type),
                    hipMemcpyDeviceToHost
                )
            );

            HIP_CHECK(hipFree(d_values_input));
            HIP_CHECK(hipFree(d_offsets));
            HIP_CHECK(hipFree(d_aggregates_output));

            for(size_t i = 0; i < segments_count; i++)
            {
                if(std::is_integral<output_type>::value)
                {
                    ASSERT_EQ(aggregates_output[i], aggregates_expected[i]);
                }
                else
                {
                    auto diff = std::max<output_type>(
                        std::abs(0.01 * aggregates_expected[i]), output_type(0.01)
                    );
                    ASSERT_NEAR(aggregates_output[i], aggregates_expected[i], diff);
                }
            }
        }
    }
}

TYPED_TEST(HipcubDeviceSegmentedReduce, Min)
{
    using input_type = typename TestFixture::params::input_type;
    using output_type = typename TestFixture::params::output_type;
    using reduce_op_type = typename hipcub::Min;
    using result_type = output_type;
    using offset_type = unsigned int;

    constexpr input_type init = std::numeric_limits<input_type>::max();
    const bool debug_synchronous = false;
    reduce_op_type reduce_op;

    std::random_device rd;
    std::default_random_engine gen(rd());

    std::uniform_int_distribution<size_t> segment_length_dis(
        TestFixture::params::min_segment_length,
        TestFixture::params::max_segment_length
    );

    const std::vector<size_t> sizes = get_sizes();
    for(size_t size : sizes)
    {
        for (size_t seed_index = 0; seed_index < random_seeds_count + seed_size; seed_index++)
        {
            unsigned int seed_value = seed_index < random_seeds_count  ? rand() : seeds[seed_index - random_seeds_count];
            SCOPED_TRACE(testing::Message() << "with seed= " << seed_value);
            SCOPED_TRACE(testing::Message() << "with size = " << size);

            hipStream_t stream = 0; // default

            // Generate data and calculate expected results
            std::vector<output_type> aggregates_expected;

            std::vector<input_type> values_input = test_utils::get_random_data<input_type>(
                size,
                0,
                100,
                seed_value
            );

            std::vector<offset_type> offsets;
            unsigned int segments_count = 0;
            size_t offset = 0;
            while(offset < size)
            {
                const size_t segment_length = segment_length_dis(gen);
                offsets.push_back(offset);

                const size_t end = std::min(size, offset + segment_length);
                result_type aggregate = init;
                for(size_t i = offset; i < end; i++)
                {
                    aggregate = reduce_op(aggregate, static_cast<result_type>(values_input[i]));
                }
                aggregates_expected.push_back(aggregate);

                segments_count++;
                offset += segment_length;
            }
            offsets.push_back(size);

            input_type * d_values_input;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_values_input, size * sizeof(input_type)));
            HIP_CHECK(
                hipMemcpy(
                    d_values_input, values_input.data(),
                    size * sizeof(input_type),
                    hipMemcpyHostToDevice
                )
            );

            offset_type * d_offsets;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_offsets, (segments_count + 1) * sizeof(offset_type)));
            HIP_CHECK(
                hipMemcpy(
                    d_offsets, offsets.data(),
                    (segments_count + 1) * sizeof(offset_type),
                    hipMemcpyHostToDevice
                )
            );

            output_type * d_aggregates_output;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_aggregates_output, segments_count * sizeof(output_type)));

            size_t temporary_storage_bytes;

            HIP_CHECK(
                hipcub::DeviceSegmentedReduce::Min(
                    nullptr, temporary_storage_bytes,
                    d_values_input, d_aggregates_output,
                    segments_count,
                    d_offsets, d_offsets + 1,
                    stream, debug_synchronous
                )
            );

            ASSERT_GT(temporary_storage_bytes, 0U);

            void * d_temporary_storage;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_temporary_storage, temporary_storage_bytes));

            HIP_CHECK(
                hipcub::DeviceSegmentedReduce::Min(
                    d_temporary_storage, temporary_storage_bytes,
                    d_values_input, d_aggregates_output,
                    segments_count,
                    d_offsets, d_offsets + 1,
                    stream, debug_synchronous
                )
            );

            HIP_CHECK(hipFree(d_temporary_storage));

            std::vector<output_type> aggregates_output(segments_count);
            HIP_CHECK(
                hipMemcpy(
                    aggregates_output.data(), d_aggregates_output,
                    segments_count * sizeof(output_type),
                    hipMemcpyDeviceToHost
                )
            );

            HIP_CHECK(hipFree(d_values_input));
            HIP_CHECK(hipFree(d_offsets));
            HIP_CHECK(hipFree(d_aggregates_output));

            for(size_t i = 0; i < segments_count; i++)
            {
                ASSERT_EQ(aggregates_output[i], aggregates_expected[i]);
            }
        }
    }
}