modules/dnn/src/layers/split_layer.cpp - 4.x - Alx89/OpenCV

modules/dnn/src/layers/split_layer.cpp
139 строк5 KB
SamFC10
int8 layers and 8-bit quantization support
19 авг 2021, 07:26
19 авг 2021, 07:26fa90e14
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#include "../precomp.hpp"
#include "../op_cuda.hpp"
#include "layers_common.hpp"

#ifdef HAVE_CUDA
#include "../cuda4dnn/primitives/split.hpp"
using namespace cv::dnn::cuda4dnn;
#endif

namespace cv
{
namespace dnn
{

class SplitLayerImpl CV_FINAL : public SplitLayer
{
public:
    SplitLayerImpl(const LayerParams &params)
    {
        setParamsFrom(params);
        //TODO: maybe "top_count" param is useless because it can be determined by output connections number
        if (params.has("top_count"))
        {
            outputsCount = params.get<int>("top_count");
            CV_Assert(outputsCount >= 0);
        }
        else
        {
            outputsCount = -1;
        }
    }

    virtual bool supportBackend(int backendId) CV_OVERRIDE
    {
        return backendId == DNN_BACKEND_OPENCV ||
               backendId == DNN_BACKEND_CUDA;
    }

    bool getMemoryShapes(const std::vector<MatShape> &inputs,
                         const int requiredOutputs,
                         std::vector<MatShape> &outputs,
                         std::vector<MatShape> &internals) const CV_OVERRIDE
    {
        CV_Assert(inputs.size() == 1);

        Layer::getMemoryShapes(inputs, max(1, outputsCount >= 0 ? outputsCount : requiredOutputs),
                               outputs, internals);
        return false;
    }

    void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) CV_OVERRIDE
    {
        CV_TRACE_FUNCTION();
        CV_TRACE_ARG_VALUE(name, "name", name.c_str());

        std::vector<Mat> inputs, outputs;
        inputs_arr.getMatVector(inputs);
        outputs_arr.getMatVector(outputs);
        for (size_t i = 0; i < outputs.size(); i++)
        {
            CV_Assert(inputs[0].total() == outputs[i].total());
            inputs[0].copyTo(outputs[i]);
        }
    }

#ifdef HAVE_CUDA
    Ptr<BackendNode> initCUDA(
        void *context_,
        const std::vector<Ptr<BackendWrapper>>& inputs,
        const std::vector<Ptr<BackendWrapper>>& outputs
    ) override
    {
        auto context = reinterpret_cast<csl::CSLContext*>(context_);
        return make_cuda_node<cuda4dnn::SplitOp>(preferableTarget, std::move(context->stream));
    }
#endif

    virtual bool tryQuantize(const std::vector<std::vector<float> > &scales,
                             const std::vector<std::vector<int> > &zeropoints, LayerParams& params) CV_OVERRIDE
    {
        const int numOutputs = scales[1].size();
        for (int i = 0; i < numOutputs; i++)
        {
            if (scales[1][i] != scales[0][0])
             return false;
        }
        return true;
    }
};

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

}
}