// Copyright (C) 2018-2026 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

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

namespace kernel_selector {
ParamsKey SoftmaxKernel_fb::GetSupportedKey() const {
    ParamsKey k;
    k.EnableInputDataType(Datatype::F16);
    k.EnableInputDataType(Datatype::F32);
    k.EnableOutputDataType(Datatype::F16);
    k.EnableOutputDataType(Datatype::F32);
    k.EnableInputLayout(DataLayout::yxfb);
    k.EnableInputLayout(DataLayout::fb);
    k.EnableOutputLayout(DataLayout::yxfb);
    k.EnableOutputLayout(DataLayout::fb);
    k.EnableSoftmaxDim(SoftmaxDim::X);  // in case that it can be flatten
    k.EnableSoftmaxDim(SoftmaxDim::Y);
    k.EnableSoftmaxDim(SoftmaxDim::FEATURE);
    k.EnableBatching();
    return k;
}

SoftmaxKernel_fb::Parent::DispatchData SoftmaxKernel_fb::SetDefault(const softmax_params& params) const {
    auto dispatchData = Parent::SetDefault(params);
    // start with 1 thread per data set
    dispatchData.gws[0] = dispatchData.dataSetsCount;
    dispatchData.gws[1] = 1;
    dispatchData.itemsNum = dispatchData.dataSetSize;

    dispatchData.normIndex = 1;

    // We have two units of data per work item in current implementation.
    auto local_mem_per_wi = 2 * BytesPerElement(params.inputs[0].GetDType());
    // Combining device execution and local memory restrictions to compute maximum possible LWS.
    auto max_lws = static_cast<std::size_t>(
        std::min(params.engineInfo.maxWorkGroupSize, params.engineInfo.maxLocalMemSize / local_mem_per_wi));

    dispatchData.lws[0] = std::min(dispatchData.dataSetsCount, max_lws);
    // Compute maximum possible LWS that does not exceed device capabilities and optimizes number of global memory
    // reads.
    while ((dispatchData.itemsNum > 32 || dispatchData.lws[0] < dispatchData.itemsNum) && (2 * dispatchData.lws[0] <= max_lws)) {
        dispatchData.lws[0] *= 2;
        dispatchData.itemsNum /= 2;
    }

    dispatchData.gws[0] = dispatchData.lws[0];
    dispatchData.gws[1] = 1;
    dispatchData.leftovers = (dispatchData.dataSetSize * dispatchData.dataSetsCount) % dispatchData.lws[0];

    assert(dispatchData.itemsNum > 0 && dispatchData.lws[0] && dispatchData.gws[0] > 0);

    return dispatchData;
}

KernelsPriority SoftmaxKernel_fb::GetKernelsPriority(const Params& /*params*/) const {
    return FORCE_PRIORITY_6;
}

bool kernel_selector::SoftmaxKernel_fb::Validate(const Params& params) const {
    if (!SoftmaxKernelBase::Validate(params)) {
        DO_NOT_USE_THIS_KERNEL(params.layerID);
    }

    const auto& softmax_params = static_cast<const kernel_selector::softmax_params&>(params);

    auto local_mem_per_wi = 2 * BytesPerElement(softmax_params.inputs[0].GetDType());
    auto max_lws = static_cast<std::size_t>(
        std::min(params.engineInfo.maxWorkGroupSize, params.engineInfo.maxLocalMemSize / local_mem_per_wi));

    size_t data_sets_count = softmax_params.inputs[0].Batch().v;
    if (data_sets_count > max_lws) {
        DO_NOT_USE_THIS_KERNEL(params.layerID);
    }

    const auto& input = softmax_params.inputs[0];
    switch (softmax_params.dim) {
        case SoftmaxDim::X:
            return input.Y().v == 1 && input.Feature().v == 1;
        case SoftmaxDim::Y:
            return input.X().v == 1 && input.Feature().v == 1;
        case SoftmaxDim::FEATURE:
            return input.X().v == 1 && input.Y().v == 1;
        default:
            DO_NOT_USE_THIS_KERNEL(params.layerID);
    }
}

KernelsData SoftmaxKernel_fb::GetKernelsData(const Params& params) const {
    if (!Validate(params)) {
        return {};
    }
    return GetCommonKernelsData(params);
}

JitConstants SoftmaxKernel_fb::GetJitConstants(const softmax_params& params, DispatchData dispatchData) const {
    auto jit = Parent::GetJitConstants(params, dispatchData);

    jit.AddConstants({
        MakeJitConstant("ITEMS_NUM", dispatchData.itemsNum),
        MakeJitConstant("LWS", dispatchData.lws[0]),
        MakeJitConstant("GWS", dispatchData.gws[0]),
        MakeJitConstant("DATA_SETS_COUNT", dispatchData.dataSetsCount),
        MakeJitConstant("DATA_SET_SIZE", dispatchData.dataSetSize),
        MakeJitConstant("LEFTOVERS", dispatchData.leftovers),
    });
    auto activation_dt = GetActivationType(params);
    jit.Merge(MakeTypeJitConstants(activation_dt, "ACTIVATION"));

    if (!params.fused_ops.empty()) {
        FusedOpsConfiguration conf_main = {"_MAIN",
                                           {"global_id", "LWS * i", "0", "0"},
                                           "dequantized",
                                           activation_dt};
        FusedOpsConfiguration conf_leftovers = {"_LEFTOVERS",
                                                {"global_id", "LWS * ITEMS_NUM", "0", "0"},
                                                "dequantized",
                                                activation_dt};
        jit.Merge(MakeFusedOpsJitConstants(params, {conf_main, conf_leftovers}));
    }

    return jit;
}
}  // namespace kernel_selector
