/*
// 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_bs_f_bsv16_af8.h"

namespace kernel_selector 
{
    ParamsKey FullyConnected_bs_f_bsv16_af8::GetSupportedKey() const
    {
        ParamsKey k;
        k.EnableInputDataType(Datatype::F16);
        k.EnableOutputDataType(Datatype::F16);
        k.EnableInputWeightsType(WeightsType::F16);
        k.EnableInputWeightsType(WeightsType::F32);
        k.EnableAllInputLayout();
        k.EnableOutputLayout(DataLayout::fb);
        k.EnableOutputLayout(DataLayout::bs_f_bsv16__af8);
        k.EnableBatching();
        k.EnableBiasPerFeature();
        k.EnableNonBiasTerm();
        k.EnableSubGroup();
        return k;
    }

    FullyConnected_bs_f_bsv16_af8::DispatchData FullyConnected_bs_f_bsv16_af8::SetDefault(const fully_connected_params& arg, int ) const
    {
        auto kd = FullyConnectedBlockKernelBase::SetDefault(arg);

        size_t groups_per_batches = GetLocalGroupsSize(arg);
        kd.gws0 = Align(arg.output.LogicalSize() / (GetBatchesPerWorkItem(arg) * groups_per_batches), 16);
        kd.gws1 = groups_per_batches;
        kd.lws0 = 16;
        kd.lws1 = 1;

        return kd;
    }
    
    static bool check_input_layout(const DataTensor& t)
    {
        bool b16_layout = false;
        b16_layout |= t.GetLayout() == DataLayout::bs_f_bsv16__af8;
        b16_layout |= DataTensor::Channelndex(t.GetLayout(), Tensor::DataChannelName::BATCH) == 0 && t.Batch().v == 16;
        return b16_layout;
    }

    bool FullyConnected_bs_f_bsv16_af8::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& optParams = static_cast<const fully_connected_optional_params&>(o);

        if (!params.engineInfo.bSubGroupShortSupport && params.inputs[0].GetDType() == Datatype::F16)
        {
            return false;
        }

        const bool bProperBatch = params.inputs[0].Batch().v == 16;
        const bool bProperInput = check_input_layout(params.inputs[0]);
        const bool bSupportedLayout = optParams.allowInputReordering || bProperInput;

        if (!bProperBatch || !bSupportedLayout)
        {
            return false;
        }

        return true;
    }

    KernelsData FullyConnected_bs_f_bsv16_af8::GetKernelsData(const Params& params, const optional_params& optParams) const
    {   
        KernelsData res = {};
        for (size_t i = 0; i < autoTuneOptions.size(); i++)
        {
            KernelsData kd = GetTunedKernelsDataByIndex(params, optParams, DataLayout::bs_f_bsv16__af8, { WeightsLayout::os_i_osv16__ai8 }, FORCE_PRIORITY_2, (int)i);
            if (!kd.empty())
            {
                res.emplace_back(kd[0]);
            }
        }

        return res;
    }
}
