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132 lines
4.7 KiB
C++
132 lines
4.7 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
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// Copyright (C) 2017, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "../precomp.hpp"
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namespace cv
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{
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namespace dnn
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{
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class BlankLayerImpl : public BlankLayer
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{
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public:
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BlankLayerImpl(const LayerParams& params)
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{
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setParamsFrom(params);
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}
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bool getMemoryShapes(const std::vector<MatShape> &inputs,
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const int requiredOutputs,
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std::vector<MatShape> &outputs,
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std::vector<MatShape> &internals) const
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{
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Layer::getMemoryShapes(inputs, requiredOutputs, outputs, internals);
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return true;
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}
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#ifdef HAVE_OPENCL
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bool forward_ocl(InputArrayOfArrays inputs_, OutputArrayOfArrays outputs_, OutputArrayOfArrays internals_)
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{
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std::vector<UMat> inputs;
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std::vector<UMat> outputs;
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inputs_.getUMatVector(inputs);
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outputs_.getUMatVector(outputs);
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for (int i = 0, n = outputs.size(); i < n; ++i)
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{
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void *src_handle = inputs[i].handle(ACCESS_READ);
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void *dst_handle = outputs[i].handle(ACCESS_WRITE);
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if (src_handle != dst_handle)
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inputs[i].copyTo(outputs[i]);
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}
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return true;
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}
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#endif
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void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
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{
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CV_TRACE_FUNCTION();
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CV_TRACE_ARG_VALUE(name, "name", name.c_str());
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CV_OCL_RUN((preferableTarget == DNN_TARGET_OPENCL) &&
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OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel()),
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forward_ocl(inputs_arr, outputs_arr, internals_arr))
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Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
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}
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void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
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{
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CV_TRACE_FUNCTION();
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CV_TRACE_ARG_VALUE(name, "name", name.c_str());
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for (int i = 0, n = outputs.size(); i < n; ++i)
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if (outputs[i].data != inputs[i]->data)
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inputs[i]->copyTo(outputs[i]);
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}
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};
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Ptr<Layer> BlankLayer::create(const LayerParams& params)
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{
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// In case of Caffe's Dropout layer from Faster-RCNN framework,
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// https://github.com/rbgirshick/caffe-fast-rcnn/tree/faster-rcnn
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// return Power layer.
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if (!params.get<bool>("scale_train", true))
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{
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float scale = 1 - params.get<float>("dropout_ratio", 0.5f);
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CV_Assert(scale > 0);
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LayerParams powerParams;
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powerParams.name = params.name;
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powerParams.type = "Power";
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powerParams.set("scale", scale);
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return PowerLayer::create(powerParams);
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}
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else
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return Ptr<BlankLayer>(new BlankLayerImpl(params));
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}
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}
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}
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