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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
// Copyright (C) 2016, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
/*
Implementation of Batch Normalization layer.
*/
#include "../precomp.hpp"
#include "layers_common.hpp"
#include "../op_halide.hpp"
#include <opencv2/dnn/shape_utils.hpp>
#include <iostream>
namespace cv
{
namespace dnn
{
class MaxUnpoolLayerImpl CV_FINAL : public MaxUnpoolLayer
{
public:
MaxUnpoolLayerImpl(const LayerParams& params)
{
setParamsFrom(params);
poolKernel = Size(params.get<int>("pool_k_w"), params.get<int>("pool_k_h"));
poolPad = Size(params.get<int>("pool_pad_w"), params.get<int>("pool_pad_h"));
poolStride = Size(params.get<int>("pool_stride_w"), params.get<int>("pool_stride_h"));
}
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
return backendId == DNN_BACKEND_OPENCV ||
(backendId == DNN_BACKEND_HALIDE && haveHalide() && !poolPad.width && !poolPad.height);
}
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() == 2);
CV_Assert(total(inputs[0]) == total(inputs[1]));
MatShape outShape = inputs[0];
outShape[2] = (outShape[2] - 1) * poolStride.height + poolKernel.height - 2 * poolPad.height;
outShape[3] = (outShape[3] - 1) * poolStride.width + poolKernel.width - 2 * poolPad.width;
outputs.clear();
outputs.push_back(outShape);
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());
if (inputs_arr.depth() == CV_16S)
{
forward_fallback(inputs_arr, outputs_arr, internals_arr);
return;
}
std::vector<Mat> inputs, outputs;
inputs_arr.getMatVector(inputs);
outputs_arr.getMatVector(outputs);
CV_Assert(inputs.size() == 2);
Mat& input = inputs[0];
Mat& indices = inputs[1];
CV_Assert(input.total() == indices.total());
CV_Assert(input.size[0] == 1);
CV_Assert(input.isContinuous());
for(int i_n = 0; i_n < outputs.size(); i_n++)
{
Mat& outBlob = outputs[i_n];
outBlob.setTo(0);
CV_Assert(input.size[1] == outBlob.size[1]);
int outPlaneTotal = outBlob.size[2]*outBlob.size[3];
for (int i_c = 0; i_c < input.size[1]; i_c++)
{
Mat outPlane = getPlane(outBlob, 0, i_c);
int wh_area = input.size[2]*input.size[3];
const float* inptr = input.ptr<float>(0, i_c);
const float* idxptr = indices.ptr<float>(0, i_c);
float* outptr = outPlane.ptr<float>();
for(int i_wh = 0; i_wh < wh_area; i_wh++)
{
int index = idxptr[i_wh];
if (!(0 <= index && index < outPlaneTotal))
{
std::cerr
<< "i_n=" << i_n << std::endl
<< "i_c=" << i_c << std::endl
<< "i_wh=" << i_wh << std::endl
<< "index=" << index << std::endl
<< "maxval=" << inptr[i_wh] << std::endl
<< "outPlaneTotal=" << outPlaneTotal << std::endl
<< "input.size=" << input.size << std::endl
<< "indices.size=" << indices.size << std::endl
<< "outBlob=" << outBlob.size << std::endl
;
CV_Assert(0 <= index && index < outPlaneTotal);
}
outptr[index] = inptr[i_wh];
}
}
}
}
virtual Ptr<BackendNode> initHalide(const std::vector<Ptr<BackendWrapper> > &input) CV_OVERRIDE
{
#ifdef HAVE_HALIDE
// Meaningless operation if false because if kernel > stride
// it is not deterministic and if kernel < stride we just
// skip a part of input data (you'd better change your model).
if (poolKernel.width != poolStride.width ||
poolKernel.height != poolStride.height)
CV_Error(cv::Error::StsNotImplemented,
"Halide backend for maximum unpooling "
"is not support cases when kernel != stride");
Halide::Var x("x"), y("y"), c("c"), n("n");
Halide::Func top = (name.empty() ? Halide::Func() : Halide::Func(name));
Halide::Buffer<float> inputBuffer = halideBuffer(input[0]);
Halide::Buffer<float> indices = halideBuffer(input[1]);
Halide::Expr pooledX = x / poolKernel.width;
Halide::Expr pooledY = y / poolKernel.height;
const int outW = inputBuffer.width() * poolKernel.width;
top(x, y, c, n) = select(y * outW + x == indices(pooledX, pooledY, c, n),
inputBuffer(pooledX, pooledY, c, n), 0.0f);
return Ptr<BackendNode>(new HalideBackendNode(top));
#endif // HAVE_HALIDE
return Ptr<BackendNode>();
}
};
Ptr<MaxUnpoolLayer> MaxUnpoolLayer::create(const LayerParams& params)
{
return Ptr<MaxUnpoolLayer>(new MaxUnpoolLayerImpl(params));
}
}
}