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Open Source Computer Vision Library
https://opencv.org/
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262 lines
7.9 KiB
262 lines
7.9 KiB
3 years ago
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#ifndef __OPENCV_DNN_SRC_NET_IMPL_HPP__
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#define __OPENCV_DNN_SRC_NET_IMPL_HPP__
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#include "op_halide.hpp"
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#include "op_inf_engine.hpp"
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#include "ie_ngraph.hpp"
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#include "op_vkcom.hpp"
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#include "op_cuda.hpp"
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#include "op_webnn.hpp"
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#include <opencv2/dnn/shape_utils.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/dnn/layer_reg.private.hpp>
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#include <opencv2/core/utils/fp_control_utils.hpp>
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#include <opencv2/core/utils/logger.hpp>
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#include "layer_internals.hpp" // LayerPin LayerData DataLayer
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#include "legacy_backend.hpp" // wrapMat BlobManager OpenCLBackendWrapper
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namespace cv {
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namespace dnn {
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CV__DNN_INLINE_NS_BEGIN
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using std::make_pair;
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using std::string;
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// NB: Implementation is divided between of multiple .cpp files
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struct Net::Impl : public detail::NetImplBase
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{
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typedef std::map<int, LayerShapes> LayersShapesMap;
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typedef std::map<int, LayerData> MapIdToLayerData;
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Impl();
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Ptr<DataLayer> netInputLayer;
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std::vector<LayerPin> blobsToKeep;
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MapIdToLayerData layers;
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std::map<String, int> layerNameToId;
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std::map<std::string, int> outputNameToId; // use registerOutput() to populate outputs
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BlobManager blobManager;
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int preferableBackend;
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int preferableTarget;
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String halideConfigFile;
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bool skipInfEngineInit;
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bool hasDynamicShapes;
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// Map host data to backend specific wrapper.
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std::map<void*, Ptr<BackendWrapper>> backendWrappers;
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int lastLayerId;
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bool netWasAllocated;
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bool netWasQuantized;
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bool fusion;
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bool isAsync;
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std::vector<int64> layersTimings;
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bool empty() const;
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void setPreferableBackend(int backendId);
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void setPreferableTarget(int targetId);
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// FIXIT use inheritance
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Ptr<BackendWrapper> wrap(Mat& host);
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void clear();
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void setUpNet(const std::vector<LayerPin>& blobsToKeep_ = std::vector<LayerPin>());
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Ptr<Layer> getLayer(int layerId) const;
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Ptr<Layer> getLayer(const LayerId& layerId) const;
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int getLayerId(const String& layerName) const;
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int getLayerId(int id) const;
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int getLayerId(DictValue& layerDesc) const;
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String getLayerName(int id) const;
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LayerData& getLayerData(int id) const;
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LayerData& getLayerData(const String& layerName) const;
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LayerData& getLayerData(const DictValue& layerDesc) const;
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static void addLayerInput(LayerData& ld, int inNum, LayerPin from);
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int resolvePinOutputName(LayerData& ld, const String& outName) const;
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LayerPin getPinByAlias(const String& layerName) const;
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std::vector<LayerPin> getLayerOutPins(const String& layerName) const;
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// FIXIT remove dtype
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int addLayer(const String& name, const String& type, const int& dtype, LayerParams& params);
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int addLayerToPrev(const String& name, const String& type, const int& dtype, LayerParams& params);
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void connect(int outLayerId, int outNum, int inLayerId, int inNum);
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int registerOutput(const std::string& outputName, int layerId, int outputPort);
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// FIXIT drop "unconnected" API
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std::vector<int> getUnconnectedOutLayers() const;
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std::vector<String> getUnconnectedOutLayersNames() /*const*/;
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void setInputsNames(const std::vector<String>& inputBlobNames);
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void setInputShape(const String& inputName, const MatShape& shape);
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void setInput(InputArray blob, const String& name, double scalefactor, const Scalar& mean);
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Mat getParam(int layer, int numParam) const;
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void setParam(int layer, int numParam, const Mat& blob);
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std::vector<Ptr<Layer>> getLayerInputs(int layerId) const;
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std::vector<String> getLayerNames() const;
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// TODO drop?
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void getLayerTypes(std::vector<String>& layersTypes) const;
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int getLayersCount(const String& layerType) const;
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// FIXIT use inheritance
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void initBackend(const std::vector<LayerPin>& blobsToKeep_);
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void setHalideScheduler(const String& scheduler);
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#ifdef HAVE_HALIDE
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void compileHalide();
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void initHalideBackend();
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#endif
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#ifdef HAVE_DNN_NGRAPH
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void addNgraphOutputs(LayerData& ld);
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void initNgraphBackend(const std::vector<LayerPin>& blobsToKeep_);
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#endif
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#ifdef HAVE_WEBNN
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void addWebnnOutputs(LayerData& ld);
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void initWebnnBackend(const std::vector<LayerPin>& blobsToKeep_);
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#endif
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#ifdef HAVE_VULKAN
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void initVkComBackend();
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#endif
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#ifdef HAVE_CUDA
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struct CudaInfo_t
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{
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CudaInfo_t(cuda4dnn::csl::CSLContext ctxt, cuda4dnn::csl::Stream d2h_stream_)
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: context(std::move(ctxt))
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, d2h_stream(std::move(d2h_stream_))
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{}
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cuda4dnn::csl::CSLContext context;
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cuda4dnn::csl::Stream d2h_stream;
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cuda4dnn::csl::Workspace workspace;
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};
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std::unique_ptr<CudaInfo_t> cudaInfo;
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void initCUDABackend(const std::vector<LayerPin>& blobsToKeep_);
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#endif
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void allocateLayer(int lid, const LayersShapesMap& layersShapes);
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// TODO add getter
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void enableFusion(bool fusion_);
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void fuseLayers(const std::vector<LayerPin>& blobsToKeep_);
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void allocateLayers(const std::vector<LayerPin>& blobsToKeep_);
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void forwardLayer(LayerData& ld);
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void forwardToLayer(LayerData& ld, bool clearFlags = true);
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Mat forward(const String& outputName);
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AsyncArray forwardAsync(const String& outputName);
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void forward(OutputArrayOfArrays outputBlobs, const String& outputName);
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void forward(OutputArrayOfArrays outputBlobs,
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const std::vector<String>& outBlobNames);
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void forward(std::vector<std::vector<Mat>>& outputBlobs,
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const std::vector<String>& outBlobNames);
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void getLayerShapesRecursively(int id, LayersShapesMap& inOutShapes);
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void getLayersShapes(
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const ShapesVec& netInputShapes,
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std::vector<int>& layersIds,
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std::vector<ShapesVec>& inLayersShapes,
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std::vector<ShapesVec>& outLayersShapes) /*const*/;
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void getLayersShapes(const ShapesVec& netInputShapes,
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LayersShapesMap& inOutShapes);
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void getLayerShapes(const ShapesVec& netInputShapes,
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const int layerId,
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LayerShapes& shapes);
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void updateLayersShapes();
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int64 getFLOPS(const std::vector<MatShape>& netInputShapes) /*const*/;
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int64 getFLOPS(
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const int layerId,
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const std::vector<MatShape>& netInputShapes) /*const*/;
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void getMemoryConsumption(
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const int layerId,
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const std::vector<MatShape>& netInputShapes,
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size_t& weights, size_t& blobs) /*const*/;
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void getMemoryConsumption(
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const std::vector<MatShape>& netInputShapes,
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size_t& weights, size_t& blobs) /*const*/;
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void getMemoryConsumption(
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const std::vector<MatShape>& netInputShapes,
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std::vector<int>& layerIds, std::vector<size_t>& weights,
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std::vector<size_t>& blobs) /*const*/;
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int64 getPerfProfile(std::vector<double>& timings) const;
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// TODO drop
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LayerPin getLatestLayerPin(const std::vector<LayerPin>& pins) const;
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Mat getBlob(const LayerPin& pin) const;
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Mat getBlob(String outputName) const;
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#ifdef CV_CXX11
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AsyncArray getBlobAsync(const LayerPin& pin);
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AsyncArray getBlobAsync(String outputName);
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#endif // CV_CXX11
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#ifdef HAVE_INF_ENGINE
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static
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Net createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork& ieNet);
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#endif
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string dump(bool forceAllocation = false) const;
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void dumpNetworkToFile() const;
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// FIXIT drop from inference API
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Net quantize(InputArrayOfArrays calibData, int inputsDtype, int outputsDtype) /*const*/;
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void getInputDetails(std::vector<float>& scales, std::vector<int>& zeropoints) /*const*/;
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void getOutputDetails(std::vector<float>& scales, std::vector<int>& zeropoints) /*const*/;
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}; // Net::Impl
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CV__DNN_INLINE_NS_END
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}} // namespace cv::dnn
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#endif // __OPENCV_DNN_SRC_NET_IMPL_HPP__
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