// 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_reduce.hpp"

template<
    class Key,
    class Value,
    class ReduceOp,
    unsigned int MinSegmentLength,
    unsigned int MaxSegmentLength,
    class Aggregate = Value
>
struct params
{
    using key_type = Key;
    using value_type = Value;
    using reduce_op_type = ReduceOp;
    static constexpr unsigned int min_segment_length = MinSegmentLength;
    static constexpr unsigned int max_segment_length = MaxSegmentLength;
    using aggregate_type = Aggregate;
};

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

typedef ::testing::Types<
    params<int, int, hipcub::Sum, 1, 1>,
    params<double, int, hipcub::Sum, 3, 5>,
    params<float, int, hipcub::Sum, 1, 10>,
    params<unsigned long long, float, hipcub::Min, 1, 30>,
    params<int, unsigned int, hipcub::Max, 20, 100, short>,
    params<float, unsigned long long, hipcub::Max, 100, 400>,
    params<unsigned int, unsigned int, hipcub::Sum, 200, 600>,
    params<double, int, hipcub::Sum, 100, 2000>,
    params<int, unsigned int, hipcub::Sum, 1000, 5000>,
    params<unsigned int, int, hipcub::Sum, 2048, 2048>,
    params<unsigned int, double, hipcub::Min, 1000, 50000>,
    params<long long, short, hipcub::Sum, 1000, 10000, long long>,
    params<unsigned long long, unsigned long long, hipcub::Sum, 100000, 100000>
> Params;

TYPED_TEST_SUITE(HipcubDeviceReduceByKey, Params);

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, (1 << 23) - 76543
    };
    const std::vector<size_t> random_sizes = test_utils::get_random_data<size_t>(10, 1, 100000, rand());
    sizes.insert(sizes.end(), random_sizes.begin(), random_sizes.end());
    return sizes;
}

TYPED_TEST(HipcubDeviceReduceByKey, ReduceByKey)
{
    using key_type = typename TestFixture::params::key_type;
    using value_type = typename TestFixture::params::value_type;
    using aggregate_type = typename TestFixture::params::aggregate_type;
    using reduce_op_type = typename TestFixture::params::reduce_op_type;
    using key_distribution_type = typename std::conditional<
        std::is_floating_point<key_type>::value,
        std::uniform_real_distribution<key_type>,
        std::uniform_int_distribution<key_type>
    >::type;

    const bool debug_synchronous = false;

    reduce_op_type reduce_op;
    hipcub::Equality key_compare_op;

    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<key_type> unique_expected;
            std::vector<aggregate_type> aggregates_expected;
            size_t unique_count_expected = 0;

            std::vector<key_type> keys_input(size);
            key_distribution_type key_delta_dis(1, 5);
            std::uniform_int_distribution<size_t> key_count_dis(
                TestFixture::params::min_segment_length,
                TestFixture::params::max_segment_length
            );
            std::vector<value_type> values_input = test_utils::get_random_data<value_type>(
                size,
                0,
                100,
                seed_value
            );

            size_t offset = 0;
            std::default_random_engine gen(seed_value + seed_value_addition);
            key_type current_key = key_distribution_type(0, 100)(gen);
            key_type prev_key = current_key;
            while(offset < size)
            {
                const size_t key_count = key_count_dis(gen);
                current_key += key_delta_dis(gen);

                const size_t end = std::min(size, offset + key_count);
                for(size_t i = offset; i < end; i++)
                {
                    keys_input[i] = current_key;
                }
                aggregate_type aggregate = values_input[offset];
                for(size_t i = offset + 1; i < end; i++)
                {
                    aggregate = reduce_op(aggregate, static_cast<aggregate_type>(values_input[i]));
                }

                // The first key of the segment must be written into unique
                // (it may differ from other keys in case of custom key compraison operators)
                if(unique_count_expected == 0 || !key_compare_op(prev_key, current_key))
                {
                    unique_expected.push_back(current_key);
                    unique_count_expected++;
                    aggregates_expected.push_back(aggregate);
                }
                else
                {
                    aggregates_expected.back() = reduce_op(aggregates_expected.back(), aggregate);
                }

                prev_key = current_key;
                offset += key_count;
            }

            key_type * d_keys_input;
            value_type * d_values_input;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_keys_input, size * sizeof(key_type)));
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_values_input, size * sizeof(value_type)));
            HIP_CHECK(
                hipMemcpy(
                    d_keys_input, keys_input.data(),
                    size * sizeof(key_type),
                    hipMemcpyHostToDevice
                )
            );
            HIP_CHECK(
                hipMemcpy(
                    d_values_input, values_input.data(),
                    size * sizeof(value_type),
                    hipMemcpyHostToDevice
                )
            );

            key_type * d_unique_output;
            aggregate_type * d_aggregates_output;
            unsigned int * d_unique_count_output;
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_unique_output, unique_count_expected * sizeof(key_type)));
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_aggregates_output, unique_count_expected * sizeof(aggregate_type)));
            HIP_CHECK(test_common_utils::hipMallocHelper(&d_unique_count_output, sizeof(unsigned int)));

            size_t temporary_storage_bytes = 0;

            HIP_CHECK(
                hipcub::DeviceReduce::ReduceByKey(
                    nullptr, temporary_storage_bytes,
                    d_keys_input, d_unique_output,
                    d_values_input, d_aggregates_output,
                    d_unique_count_output,
                    reduce_op, size,
                    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::DeviceReduce::ReduceByKey(
                    d_temporary_storage, temporary_storage_bytes,
                    d_keys_input, d_unique_output,
                    d_values_input, d_aggregates_output,
                    d_unique_count_output,
                    reduce_op, size,
                    stream, debug_synchronous
                )
            );

            HIP_CHECK(hipFree(d_temporary_storage));

            std::vector<key_type> unique_output(unique_count_expected);
            std::vector<aggregate_type> aggregates_output(unique_count_expected);
            std::vector<unsigned int> unique_count_output(1);
            HIP_CHECK(
                hipMemcpy(
                    unique_output.data(), d_unique_output,
                    unique_count_expected * sizeof(key_type),
                    hipMemcpyDeviceToHost
                )
            );
            HIP_CHECK(
                hipMemcpy(
                    aggregates_output.data(), d_aggregates_output,
                    unique_count_expected * sizeof(aggregate_type),
                    hipMemcpyDeviceToHost
                )
            );
            HIP_CHECK(
                hipMemcpy(
                    unique_count_output.data(), d_unique_count_output,
                    sizeof(unsigned int),
                    hipMemcpyDeviceToHost
                )
            );

            HIP_CHECK(hipFree(d_keys_input));
            HIP_CHECK(hipFree(d_values_input));
            HIP_CHECK(hipFree(d_unique_output));
            HIP_CHECK(hipFree(d_aggregates_output));
            HIP_CHECK(hipFree(d_unique_count_output));

            ASSERT_EQ(unique_count_output[0], unique_count_expected);

            // Validating results
            for(size_t i = 0; i < unique_count_expected; i++)
            {
                ASSERT_EQ(unique_output[i], unique_expected[i]);
                if(std::is_integral<aggregate_type>::value)
                {
                    ASSERT_EQ(aggregates_output[i], aggregates_expected[i]);
                }
                else if (std::is_floating_point<aggregate_type>::value)
                {
                    auto tolerance = std::max<aggregate_type>(
                        std::abs(0.1f * aggregates_expected[i]), aggregate_type(0.01f)
                    );
                    ASSERT_NEAR(aggregates_output[i], aggregates_expected[i], tolerance);
                }
            }
        }
    }
}