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path: root/inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/upsampling/upsampling_kernel_base.cpp
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/*
// 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 "upsampling_kernel_base.h"
#include "kernel_selector_utils.h" 

namespace kernel_selector
{
    bool UpSamplingKernelBase::Validate(const Params& p, const optional_params& o) const
    {
        if (p.GetType() != KernelType::UPSAMPLING ||
            o.GetType() != KernelType::UPSAMPLING)
        {
            return false;
        }

        const upsampling_params& params = static_cast<const upsampling_params&>(p);

        if (params.inputs.size() == 0)
        {
            return false;
        }

        return true;
    }

    JitConstants UpSamplingKernelBase::GetJitConstants(const upsampling_params& params) const
    {
        JitConstants jit = MakeBaseParamsJitConstants(params);

        const auto& input = params.inputs[0];
        const auto& output = params.output;

        auto x_ratio = (float)input.X().v / (float)output.X().v;
        auto y_ratio = (float)input.Y().v / (float)output.Y().v;

        jit.AddConstants({
            MakeJitConstant(toString(params.sampleType), ""),
            MakeJitConstant("X_RATIO", x_ratio),
            MakeJitConstant("Y_RATIO", y_ratio),
        });

        return jit;
    }

    KernelsData UpSamplingKernelBase::GetCommonKernelsData(const Params& params, const optional_params& options) const
    {
        if (!Validate(params, options))
        {
            return{};
        }

        KernelData kd = KernelData::Default<upsampling_params>(params);
        upsampling_params& newParams = *static_cast<upsampling_params*>(kd.params.get());

        auto entry_point = GetEntryPoint(kernelName, newParams.layerID, options);
        auto cldnn_jit = GetJitConstants(newParams);
        std::string jit = CreateJit(kernelName, cldnn_jit, entry_point);

        auto& kernel = kd.kernels[0];

        const auto& out = newParams.output;

        kernel.workGroups.global = { out.X().v, out.Y().v, out.Feature().v * out.Batch().v };
        kernel.workGroups.local = GetOptimalLocalWorkGroupSizes(kernel.workGroups.global);
        kernel.kernelString = GetKernelString(kernelName, jit, entry_point, params.engineInfo, ROUND_ROBIN);
        kernel.arguments = GetArgsDesc((uint32_t)newParams.inputs.size(), false, false);

        kd.estimatedTime = DONT_USE_IF_HAVE_SOMETHING_ELSE;

        return{ kd };
    }
}