opencv/modules/dnn/src/layers/eltwise_layer.cpp

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#include "../precomp.hpp"
#include "layers_common.hpp"
#include "op_halide.hpp"

namespace cv
{
namespace dnn
{

class EltwiseLayerImpl : public EltwiseLayer
{
public:
    EltwiseOp op;
    std::vector<int> coeffs;

    EltwiseLayerImpl(const LayerParams& params)
    {
        setParamsFrom(params);
        op = EltwiseLayer::SUM;
        if (params.has("operation"))
        {
            String operation = params.get<String>("operation").toLowerCase();
            if (operation == "prod")
                op = EltwiseLayer::PROD;
            else if (operation == "sum")
                op = EltwiseLayer::SUM;
            else if (operation == "max")
                op = EltwiseLayer::MAX;
            else
                CV_Error(cv::Error::StsBadArg, "Unknown operaticon type \"" + operation + "\"");
        }

        if (params.has("coeff"))
        {
            DictValue paramCoeff = params.get("coeff");
            int i, n = paramCoeff.size();
            coeffs.resize(n);
            for (i = 0; i < n; i++)
            {
                coeffs[i] = paramCoeff.get<int>(i);
            }
        }
    }

    virtual bool supportBackend(int backendId)
    {
        return backendId == DNN_BACKEND_DEFAULT ||
               backendId == DNN_BACKEND_HALIDE && haveHalide();
    }

    bool getMemoryShapes(const std::vector<MatShape> &inputs,
                         const int requiredOutputs,
                         std::vector<MatShape> &outputs,
                         std::vector<MatShape> &internals) const
    {
        CV_Assert(inputs.size() >= 2);
        CV_Assert(coeffs.size() == 0 || coeffs.size() == inputs.size());
        CV_Assert(op == SUM || coeffs.size() == 0);

        for (int i = 1; i < inputs.size(); i++)
        {
            CV_Assert(inputs[0] == inputs[i]);
        }

        outputs.assign(1, inputs[0]);

        return false;
    }

    void forward(std::vector<Mat *> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
    {
        Mat& output = outputs[0];
        switch (op)
        {
            case SUM:
                CV_Assert(coeffs.size() == 0 || coeffs.size() == inputs.size());
                if (0 < coeffs.size())
                {
                    output.setTo(0.);
                    for (size_t i = 0; i < inputs.size(); i++)
                    {
                        output += *inputs[i] * coeffs[i];
                    }
                }
                else
                {
                    add(*inputs[0], *inputs[1], output);
                    for (size_t i = 2; i < inputs.size(); i++)
                    {
                        output += *inputs[i];
                    }
                }
                break;
            case PROD:
                output.setTo(1.);
                for (size_t i = 0; i < inputs.size(); i++)
                {
                    output = output.mul(*inputs[i]);
                }
                break;
            case MAX:
                cv::max(*inputs[0], *inputs[1], output);
                for (size_t i = 2; i < inputs.size(); i++)
                {
                    cv::max(output, *inputs[i], output);
                }
                break;
            default:
                CV_Assert(0);
                break;
        }
    }

    virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &input)
    {
#ifdef HAVE_HALIDE
        Halide::Var x("x"), y("y"), c("c"), n("n");
        Halide::Func top = (name.empty() ? Halide::Func() : Halide::Func(name));
        Halide::Expr topExpr;
        std::vector<Halide::Buffer<> > inputBuffers = halideBuffers(input);
        switch (op)
        {
            case SUM:
                if (coeffs.empty())
                {
                    topExpr = inputBuffers[0](x, y, c, n) +
                              inputBuffers[1](x, y, c, n);
                    for (int i = 2; i < inputBuffers.size(); ++i)
                        topExpr += inputBuffers[i](x, y, c, n);
                }
                else
                {
                  topExpr = coeffs[0] * inputBuffers[0](x, y, c, n) +
                            coeffs[1] * inputBuffers[1](x, y, c, n);
                  for (int i = 2; i < inputBuffers.size(); ++i)
                      topExpr += coeffs[i] * inputBuffers[i](x, y, c, n);
                }
                break;
            case PROD:
                topExpr = inputBuffers[0](x, y, c, n) *
                          inputBuffers[1](x, y, c, n);
                for (int i = 2; i < inputBuffers.size(); ++i)
                    topExpr *= inputBuffers[i](x, y, c, n);
                break;
            case MAX:
                topExpr = max(inputBuffers[0](x, y, c, n),
                              inputBuffers[1](x, y, c, n));
                for (int i = 2; i < inputBuffers.size(); ++i)
                    topExpr = max(topExpr, inputBuffers[i](x, y, c, n));
                break;
            default:
                return Ptr<BackendNode>();
        }
        top(x, y, c, n) = topExpr;
        return Ptr<BackendNode>(new HalideBackendNode(top));
#endif  // HAVE_HALIDE
        return Ptr<BackendNode>();
    }

    virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
                           const std::vector<MatShape> &outputs) const
    {
        (void)outputs; // suppress unused variable warning
        CV_Assert(inputs.size());

        long flops = inputs.size() * total(inputs[0]);

        return flops;
    }
};

Ptr<EltwiseLayer> EltwiseLayer::create(const LayerParams& params)
{
    return Ptr<EltwiseLayer>(new EltwiseLayerImpl(params));
}

}
}