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#include "../precomp.hpp"
#include "layers_common.hpp"
#include "flatten_layer.hpp"
#include <float.h>
#include <algorithm>

namespace cv
{
namespace dnn
{

FlattenLayer::FlattenLayer(LayerParams &params) : Layer(params)
{
    _startAxis = params.get<int>("axis", 1);
    _endAxis = params.get<int>("end_axis", -1);
}

void FlattenLayer::checkInputs(const std::vector<Blob*> &inputs)
{
    CV_Assert(inputs.size() > 0);
    for (size_t i = 1; i < inputs.size(); i++)
    {
        for (size_t j = 0; j < _numAxes; j++)
        {
            CV_Assert(inputs[i]->shape()[j] == inputs[0]->shape()[j]);
        }
    }
}

void FlattenLayer::allocate(const std::vector<Blob*> &inputs, std::vector<Blob> &outputs)
{
    checkInputs(inputs);

    _numAxes = inputs[0]->dims();
    _endAxis = inputs[0]->canonicalAxis(_endAxis);
    CV_Assert(_startAxis >= 0);
    CV_Assert(_endAxis >= _startAxis && _endAxis < (int)_numAxes);

    size_t flattenedDimensionSize = 1;
    for (int i = _startAxis; i <= _endAxis; i++)
    {
        flattenedDimensionSize *= inputs[0]->size(i);
    }

    std::vector<int> outputShapeVec;
    for (int i = 0; i < _startAxis; i++)
    {
        outputShapeVec.push_back(inputs[0]->size(i));
    }
    outputShapeVec.push_back(flattenedDimensionSize);
    for (size_t i = _endAxis + 1; i < _numAxes; i++)
    {
        outputShapeVec.push_back(inputs[0]->size(i));
    }
    CV_Assert(outputShapeVec.size() <= 4);

    resultShape = BlobShape(outputShapeVec);

    for (size_t i = 0; i < inputs.size(); i++)
    {
        //in-place
        outputs[i].shareFrom(*inputs[i]);
        outputs[i].reshape(resultShape);
    }
}

void FlattenLayer::forward(std::vector<Blob*> &inputs, std::vector<Blob> &outputs)
{
    for (size_t j = 0; j < inputs.size(); j++)
    {
        outputs[j].shareFrom(*inputs[j]);
        outputs[j].reshape(resultShape);
    }
}
}
}