// Copyright (c) 2016 Intel Corporation
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.


#include "fully_connected_kernel_fb_io_b8_f8.h"
#include <algorithm>

namespace kernel_selector {
ParamsKey FullyConnected_fb_io_b8_f8::GetSupportedKey() const {
    ParamsKey k;
    k.EnableInputDataType(Datatype::F32);
    k.EnableInputDataType(Datatype::F16);
    k.EnableOutputDataType(Datatype::F32);
    k.EnableOutputDataType(Datatype::F16);
    k.EnableInputWeightsType(WeightsType::F32);
    k.EnableInputWeightsType(WeightsType::F16);
    k.EnableAllInputLayout();
    k.EnableOutputLayout(DataLayout::fb);
    k.EnableBatching();
    k.EnableBiasPerFeature();
    k.EnableNonBiasTerm();
    k.EnableSubGroup();
    return k;
}

size_t FullyConnected_fb_io_b8_f8::GetBatchesPerWorkItem(const fully_connected_params& params) const {
    auto batch_size = params.output.Batch().v;

    if (batch_size % 32 == 0)
        return std::min(batch_size, static_cast<size_t>(32U));

    if (batch_size % 16 == 0)
        return std::min(batch_size, static_cast<size_t>(16U));

    return std::min(batch_size, static_cast<size_t>(8U));
}

FullyConnected_fb_io_b8_f8::DispatchData FullyConnected_fb_io_b8_f8::SetDefault(const fully_connected_params& arg,
                                                                                int) const {
    auto kd = FullyConnectedBlockKernelBase::SetDefault(arg);

    const auto& output = arg.output;

    size_t groups_per_batches = GetLocalGroupsSize(arg);
    kd.gws0 =
        Align(output.LogicalSize() / (GetNeuronsPerWorkItem(arg) * GetBatchesPerWorkItem(arg) * groups_per_batches), 8);
    kd.gws1 = groups_per_batches;
    kd.lws0 = 8;
    kd.lws1 = 1;

    return kd;
}

bool FullyConnected_fb_io_b8_f8::Validate(const Params& p, const optional_params& o) const {
    if (!FullyConnectedBlockKernelBase::Validate(p, o)) {
        return false;
    }

    const auto& params = static_cast<const fully_connected_params&>(p);

    const auto& output = params.output;
    const auto batches = output.Batch().v;
    const auto x_size = output.LogicalSize() / batches;

    const auto& input = params.inputs[0];
    const auto input_x_size = input.LogicalSize() / input.Batch().v;
    const bool proper_input_aligment = (input_x_size % 8) == 0;
    const bool proper_output_aligment =
        (output.LogicalSize() /
         (GetNeuronsPerWorkItem(params) * GetBatchesPerWorkItem(params) * GetLocalGroupsSize(params)) % 8) == 0;
    const bool bSupportedBatch = (batches % 8) == 0;
    const bool bSupportedFeature = (x_size % 8) == 0;

    if (!bSupportedBatch || !bSupportedFeature || !proper_input_aligment || !proper_output_aligment) {
        return false;
    }

    return true;
}

KernelsData FullyConnected_fb_io_b8_f8::GetKernelsData(const Params& params, const optional_params& optParams) const {
    assert(params.GetType() == KernelType::FULLY_CONNECTED);
    KernelsData res = {};
    const auto& orgParams = static_cast<const fully_connected_params&>(params);

    float estimated_time = orgParams.inputs[0].GetDType() == Datatype::F16 && orgParams.output.Batch().v >= 16
                               ? FORCE_PRIORITY_3
                               : FORCE_PRIORITY_5;

    for (size_t i = 0; i < autoTuneOptions.size(); i++) {
        KernelsData kd =
            GetTunedKernelsDataByIndex(params, optParams, DataLayout::fb, WeightsLayout::io, estimated_time, static_cast<int>(i));
        if (!kd.empty()) {
            res.emplace_back(kd[0]);
        }
    }

    return res;
}
}  // namespace kernel_selector
