fully_connected_layer.cpp 4.5 KB
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//  If you do not agree to this license, do not download, install,
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//
//                           License Agreement
//                For Open Source Computer Vision Library
//
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//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
//   * Redistribution's of source code must retain the above copyright notice,
//     this list of conditions and the following disclaimer.
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#include "../precomp.hpp"
#include "layers_common.hpp"
#include "fully_connected_layer.hpp"
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#include "op_blas.hpp"
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#include <opencv2/dnn/shape_utils.hpp>
#include <opencv2/core/ocl.hpp>
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namespace cv
{
namespace dnn
{

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FullyConnectedLayerImpl::FullyConnectedLayerImpl(int axis_)
{
    axis = axis_;
}
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void FullyConnectedLayerImpl::allocate(const std::vector<Blob*> &input, std::vector<Blob> &output)
{
    CV_Assert(input.size() > 0);
    CV_Assert(1 <= blobs.size() && blobs.size() <= 2);
    CV_Assert(blobs[0].dims() == 2);
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    bias = (blobs.size() >= 1);
    axisCan = input[0]->canonicalAxis(axis);
    dtype = input[0]->type();
    numOutput = blobs[0].size(0);
    innerSize = blobs[0].size(1);
    outerSize = input[0]->total(0, axisCan);
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    CV_Assert((size_t)innerSize == input[0]->total(axisCan));
    CV_Assert(!bias || (size_t)numOutput == blobs[1].total());
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    useOpenCL = ocl::useOpenCL();
    int allocFlags = useOpenCL ? Blob::ALLOC_UMAT : Blob::ALLOC_UMAT;
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    biasOnesBlob.create(Shape(outerSize, 1), dtype, allocFlags);
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    biasOnesBlob.setTo(1);
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    output.resize(input.size());
    for (size_t i = 0; i < input.size(); i++)
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    {
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        CV_Assert(i == 0 || (input[i]->equalShape(*input[0]) && input[i]->type() == dtype));
        Shape outShape = input[i]->shape().slice(0, axis) + Shape(numOutput);
        output[i].create(outShape, dtype, allocFlags);
    }
}
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void FullyConnectedLayerImpl::forward(std::vector<Blob*> &input, std::vector<Blob> &output)
{
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    #ifdef HAVE_OPENCL
    if (useOpenCL)
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        forward_<UMat>(input, output);
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    else
    #endif
        forward_<Mat>(input, output);
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}

template<typename XMat>
void FullyConnectedLayerImpl::forward_(std::vector<Blob *> &input, std::vector<Blob> &output)
{
    const XMat &weight = blobs[0].getRefConst<XMat>();
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    const XMat *biasMat = NULL, *biasOnesMat = NULL;
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    if (bias)
    {
        biasOnesMat = &biasOnesBlob.getRefConst<XMat>();
        biasMat = &blobs[1].getRefConst<XMat>();
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    }

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    for (size_t i = 0; i < input.size(); i++)
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    {
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        const XMat srcMat = reshaped(input[i]->getRefConst<XMat>(), Shape(outerSize, innerSize));
        XMat dstMat = reshaped(output[i].getRef<XMat>(), Shape(outerSize, numOutput));
        dnn::gemm(srcMat, weight, 1, dstMat, 0, GEMM_2_T);

        if (bias)
            dnn::gemm(*biasOnesMat, *biasMat, 1, dstMat, 1);
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    }
}
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Ptr<InnerProductLayer> InnerProductLayer::create(int axis)
{
    return Ptr<InnerProductLayer>(new FullyConnectedLayerImpl(axis));
}

}
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}