// layer blob.
int numReferences(const LayerPin& lp)
{
- std::map<LayerPin, LayerPin>::iterator mapIt = reuseMap.find(lp);
+ std::map<LayerPin, LayerPin>::const_iterator mapIt = reuseMap.find(lp);
CV_Assert(mapIt != reuseMap.end());
LayerPin memHost = mapIt->second;
- std::map<LayerPin, int>::iterator refIt = refCounter.find(memHost);
+ std::map<LayerPin, int>::const_iterator refIt = refCounter.find(memHost);
CV_Assert(refIt != refCounter.end());
return refIt->second;
}
// Decrease references counter to allocated memory inside specific blob.
void releaseReference(const LayerPin& lp)
{
- std::map<LayerPin, LayerPin>::iterator mapIt = reuseMap.find(lp);
+ std::map<LayerPin, LayerPin>::const_iterator mapIt = reuseMap.find(lp);
CV_Assert(mapIt != reuseMap.end());
std::map<LayerPin, int>::iterator refIt = refCounter.find(mapIt->second);
Mat bestBlob;
LayerPin bestBlobPin;
- std::map<LayerPin, Mat>::iterator hostIt;
- std::map<LayerPin, int>::iterator refIt;
+ std::map<LayerPin, Mat>::const_iterator hostIt;
+ std::map<LayerPin, int>::const_iterator refIt;
const int targetTotal = total(shape);
int bestBlobTotal = INT_MAX;
// it might be used as output.
if (refIt != refCounter.end() && refIt->second == 0)
{
- Mat& unusedBlob = hostIt->second;
+ const Mat& unusedBlob = hostIt->second;
if (unusedBlob.total() >= targetTotal &&
unusedBlob.total() < bestBlobTotal &&
unusedBlob.type() == dtype)
// nothing
}
-std::string detail::NetImplBase::getDumpFileNameBase()
+std::string detail::NetImplBase::getDumpFileNameBase() const
{
std::string dumpFileNameBase = cv::format("ocv_dnn_net_%05d_%02d", networkId, networkDumpCounter++);
return dumpFileNameBase;
bool fusion;
bool isAsync;
std::vector<int64> layersTimings;
- Mat output_blob;
#ifdef HAVE_CUDA
struct CudaInfo_t
std::vector< std::reference_wrapper<LayerData> > compileList; compileList.reserve(64);
for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); ++it)
{
- LayerData &ld = it->second;
+ LayerData& ld = it->second;
Ptr<Layer> layer = ld.layerInstance;
if (layer->supportBackend(DNN_BACKEND_HALIDE) && !ld.skip)
{
}
}
- int getLayerId(const String &layerName)
+ int getLayerId(const String &layerName) const
{
- std::map<String, int>::iterator it = layerNameToId.find(layerName);
+ std::map<String, int>::const_iterator it = layerNameToId.find(layerName);
return (it != layerNameToId.end()) ? it->second : -1;
}
- int getLayerId(int id)
+ int getLayerId(int id) const
{
- MapIdToLayerData::iterator it = layers.find(id);
+ MapIdToLayerData::const_iterator it = layers.find(id);
return (it != layers.end()) ? id : -1;
}
- int getLayerId(DictValue &layerDesc)
+ int getLayerId(DictValue &layerDesc) const
{
if (layerDesc.isInt())
return getLayerId(layerDesc.get<int>());
return -1;
}
- String getLayerName(int id)
+ String getLayerName(int id) const
{
- MapIdToLayerData::iterator it = layers.find(id);
+ MapIdToLayerData::const_iterator it = layers.find(id);
return (it != layers.end()) ? it->second.name : "(unknown layer)";
}
- LayerData& getLayerData(int id)
+ LayerData& getLayerData(int id) const
{
- MapIdToLayerData::iterator it = layers.find(id);
+ MapIdToLayerData::const_iterator it = layers.find(id);
if (it == layers.end())
CV_Error(Error::StsObjectNotFound, format("Layer with requested id=%d not found", id));
- return it->second;
+ return const_cast<LayerData&>(it->second);
}
- LayerData& getLayerData(const String &layerName)
+ LayerData& getLayerData(const String &layerName) const
{
int id = getLayerId(layerName);
return getLayerData(id);
}
- LayerData& getLayerData(const DictValue &layerDesc)
+ LayerData& getLayerData(const DictValue &layerDesc) const
{
CV_Assert(layerDesc.isInt() || layerDesc.isString());
if (layerDesc.isInt())
ld.inputBlobsId[inNum] = from;
}
- int resolvePinOutputName(LayerData &ld, const String &outName)
+ int resolvePinOutputName(LayerData &ld, const String &outName) const
{
if (outName.empty())
return 0;
return ld.getLayerInstance()->outputNameToIndex(outName);
}
- LayerPin getPinByAlias(const String &layerName)
+ LayerPin getPinByAlias(const String &layerName) const
{
LayerPin pin;
pin.lid = (layerName.empty()) ? 0 : getLayerId(layerName);
return pin;
}
- std::vector<LayerPin> getLayerOutPins(const String &layerName)
+ std::vector<LayerPin> getLayerOutPins(const String &layerName) const
{
int lid = (layerName.empty()) ? 0 : getLayerId(layerName);
- std::vector<LayerPin> pins;
+ MapIdToLayerData::const_iterator it = layers.find(lid);
+ if (it == layers.end())
+ CV_Error_(Error::StsOutOfRange, ("Layer #%d is not valid", lid));
+ const size_t nOutputs = it->second.outputBlobs.size();
- for (int i = 0; i < layers[lid].outputBlobs.size(); i++)
+ std::vector<LayerPin> pins;
+ for (int i = 0; i < nOutputs; i++)
{
pins.push_back(LayerPin(lid, i));
}
CV_TRACE_FUNCTION();
CV_Assert_N(preferableBackend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, haveInfEngine());
- MapIdToLayerData::iterator it;
Ptr<InfEngineNgraphNet> net;
- for (it = layers.begin(); it != layers.end(); ++it)
+ for (MapIdToLayerData::const_iterator it = layers.begin(); it != layers.end(); ++it)
{
- LayerData &ld = it->second;
+ const LayerData& ld = it->second;
if (ld.id == 0)
{
CV_Assert((netInputLayer->outNames.empty() && ld.outputBlobsWrappers.size() == 1) ||
InfEngineNgraphNet& ienet = *ieNode->net;
ienet.reset();
- for (it = layers.begin(); it != layers.end(); ++it)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); ++it)
{
- LayerData &ld = it->second;
+ LayerData& ld = it->second;
if (ld.id == 0)
{
for (int i = 0; i < ld.inputBlobsWrappers.size(); ++i)
// Build Inference Engine networks from sets of layers that support this
// backend. Split a whole model on several Inference Engine networks if
// some of layers are not implemented.
- for (it = layers.begin(); it != layers.end(); ++it)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); ++it)
{
- LayerData &ld = it->second;
+ LayerData& ld = it->second;
if (ld.id == 0 && ld.skip)
continue;
CV_TRACE_FUNCTION();
CV_Assert_N(preferableBackend == DNN_BACKEND_WEBNN, haveWebnn());
- MapIdToLayerData::iterator it;
Ptr<WebnnNet> net;
- for (it = layers.begin(); it != layers.end(); ++it)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); ++it)
{
LayerData &ld = it->second;
if (ld.id == 0)
// Build WebNN networks from sets of layers that support this
// backend. Split a whole model on several WebNN networks if
// some of layers are not implemented.
- for (it = layers.begin(); it != layers.end(); ++it)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); ++it)
{
LayerData &ld = it->second;
if (!haveVulkan())
return;
- MapIdToLayerData::iterator it = layers.begin();
- for (; it != layers.end(); it++)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); it++)
{
LayerData &ld = it->second;
Ptr<Layer> layer = ld.layerInstance;
ld.inputLayersId.insert(ld.inputBlobsId[i].lid);
//allocate parents
- for (set<int>::iterator i = ld.inputLayersId.begin(); i != ld.inputLayersId.end(); i++)
+ for (set<int>::const_iterator i = ld.inputLayersId.begin(); i != ld.inputLayersId.end(); i++)
allocateLayer(*i, layersShapes);
//bind inputs
// we try to embed this activation into the convolution and disable separate execution of the activation
std::set<LayerPin> pinsToKeep(blobsToKeep_.begin(),
blobsToKeep_.end());
- MapIdToLayerData::iterator it;
- for (it = layers.begin(); it != layers.end(); it++)
+ for (MapIdToLayerData::const_iterator it = layers.begin(); it != layers.end(); it++)
{
int lid = it->first;
LayerData& ld = layers[lid];
{
CV_TRACE_FUNCTION();
- MapIdToLayerData::iterator it;
- for (it = layers.begin(); it != layers.end(); it++)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); it++)
it->second.flag = 0;
CV_Assert(!layers[0].outputBlobs.empty());
// Fake references to input blobs.
for (int i = 0; i < layers[0].outputBlobs.size(); ++i)
blobManager.addReference(LayerPin(0, i));
- for (it = layers.begin(); it != layers.end(); ++it)
+ for (MapIdToLayerData::const_iterator it = layers.begin(); it != layers.end(); ++it)
{
const LayerData& ld = it->second;
blobManager.addReferences(ld.inputBlobsId);
blobManager.addReference(blobsToKeep_[i]);
}
- for (it = layers.begin(); it != layers.end(); it++)
+ for (MapIdToLayerData::const_iterator it = layers.begin(); it != layers.end(); it++)
{
int lid = it->first;
allocateLayer(lid, layersShapes);
TickMeter tm;
tm.start();
+#ifndef HAVE_VULKAN
+ std::map<int, Ptr<BackendNode> >::const_iterator it = ld.backendNodes.find(preferableBackend);
+#else
std::map<int, Ptr<BackendNode> >::iterator it = ld.backendNodes.find(preferableBackend);
+#endif
if (preferableBackend == DNN_BACKEND_OPENCV || it == ld.backendNodes.end() || it->second.empty())
{
if (isAsync)
{
forwardWebnn(ld.outputBlobsWrappers, node, isAsync);
}
+#ifdef HAVE_VULKAN
else if (preferableBackend == DNN_BACKEND_VKCOM)
{
try
forwardLayer(ld);
}
}
+#endif
else
{
CV_Error(Error::StsNotImplemented, "Unknown backend identifier");
if (clearFlags)
{
- MapIdToLayerData::iterator it;
- for (it = layers.begin(); it != layers.end(); it++)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); it++)
it->second.flag = 0;
}
return;
//forward parents
- MapIdToLayerData::iterator it;
- for (it = layers.begin(); it != layers.end() && (it->second.id < ld.id); ++it)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end() && (it->second.id < ld.id); ++it)
{
LayerData &ld = it->second;
if (ld.flag)
for(int i = 0; i < inputLayerIds.size(); i++)
{
int layerId = inputLayerIds[i].lid;
- LayersShapesMap::iterator it =
+ LayersShapesMap::const_iterator it =
inOutShapes.find(layerId);
if(it == inOutShapes.end() ||
it->second.out.empty())
inOutShapes.clear();
inOutShapes[0].in = netInputShapes; //insert shape for first input layer
- for (MapIdToLayerData::iterator it = layers.begin();
+ for (MapIdToLayerData::const_iterator it = layers.begin();
it != layers.end(); it++)
{
getLayerShapesRecursively(it->first, inOutShapes);
CV_LOG_DEBUG(NULL, toString(inputShapes, "Network input shapes"));
LayersShapesMap layersShapes;
layersShapes[0].in = inputShapes;
- for (MapIdToLayerData::iterator it = layers.begin();
- it != layers.end(); it++)
+ for (MapIdToLayerData::iterator it = layers.begin(); it != layers.end(); it++)
{
int layerId = it->first;
LayerData& layerData = it->second;
- std::vector<LayerPin>& inputLayerIds = layerData.inputBlobsId;
+ const std::vector<LayerPin>& inputLayerIds = layerData.inputBlobsId;
LayerShapes& layerShapes = layersShapes[layerId];
CV_LOG_DEBUG(NULL, "layer " << layerId << ": [" << layerData.type << "]:(" << layerData.name << ") with inputs.size=" << inputLayerIds.size());
if (layerShapes.in.empty())
const LayerPin& inputPin = inputLayerIds[i];
int inputLayerId = inputPin.lid;
CV_LOG_DEBUG(NULL, " input[" << i << "] " << inputLayerId << ":" << inputPin.oid << " as [" << layers[inputLayerId].type << "]:(" << layers[inputLayerId].name << ")");
- LayersShapesMap::iterator inputIt = layersShapes.find(inputLayerId);
+ LayersShapesMap::const_iterator inputIt = layersShapes.find(inputLayerId);
if (inputIt == layersShapes.end() || inputIt->second.out.empty())
{
getLayerShapesRecursively(inputLayerId, layersShapes);
CV_LOG_DEBUG(NULL, "updateLayersShapes() - DONE");
}
- LayerPin getLatestLayerPin(const std::vector<LayerPin>& pins)
+ LayerPin getLatestLayerPin(const std::vector<LayerPin>& pins) const
{
return *std::max_element(pins.begin(), pins.end());
}
- Mat getBlob(const LayerPin& pin)
+ Mat getBlob(const LayerPin& pin) const
{
CV_TRACE_FUNCTION();
if (!pin.valid())
CV_Error(Error::StsObjectNotFound, "Requested blob not found");
- LayerData &ld = layers[pin.lid];
+ MapIdToLayerData::const_iterator it = layers.find(pin.lid);
+ if (it == layers.end())
+ CV_Error_(Error::StsOutOfRange, ("Layer #%d is not valid (output #%d requested)", pin.lid, pin.oid));
+
+ const LayerData &ld = it->second;
if ((size_t)pin.oid >= ld.outputBlobs.size())
{
CV_Error(Error::StsOutOfRange, format("Layer \"%s\" produce only %zu outputs, "
if (ld.outputBlobs[pin.oid].depth() == CV_16S)
{
+ Mat output_blob;
convertFp16(ld.outputBlobs[pin.oid], output_blob);
return output_blob;
}
return ld.outputBlobs[pin.oid];
}
- Mat getBlob(String outputName)
+ Mat getBlob(String outputName) const
{
return getBlob(getPinByAlias(outputName));
}
Net createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork& ieNet);
#endif
- string dump();
+ string dump() const;
- void dumpNetworkToFile()
+ void dumpNetworkToFile() const
{
#ifndef OPENCV_DNN_DISABLE_NETWORK_AUTO_DUMP
string dumpFileNameBase = getDumpFileNameBase();
impl->netWasAllocated = impl->netWasAllocated && oldShape;
}
-Mat Net::getParam(LayerId layer, int numParam)
+Mat Net::getParam(int layer, int numParam) const
{
LayerData &ld = impl->getLayerData(layer);
std::vector<Mat> &layerBlobs = ld.getLayerInstance()->blobs;
return layerBlobs[numParam];
}
-void Net::setParam(LayerId layer, int numParam, const Mat &blob)
+void Net::setParam(int layer, int numParam, const Mat &blob)
{
LayerData &ld = impl->getLayerData(layer);
layerBlobs[numParam] = blob;
}
-int Net::getLayerId(const String &layer)
+int Net::getLayerId(const String &layer) const
{
return impl->getLayerId(layer);
}
return impl->dump();
}
-string Net::Impl::dump()
+string Net::Impl::dump() const
{
bool hasInput = !netInputLayer->inputsData.empty();
file.close();
}
-Ptr<Layer> Net::getLayer(LayerId layerId)
+Ptr<Layer> Net::getLayer(int layerId) const
+{
+ LayerData &ld = impl->getLayerData(layerId);
+ return ld.getLayerInstance();
+}
+Ptr<Layer> Net::getLayer(const LayerId& layerId) const
{
LayerData &ld = impl->getLayerData(layerId);
return ld.getLayerInstance();
}
-std::vector<Ptr<Layer> > Net::getLayerInputs(LayerId layerId)
+std::vector<Ptr<Layer> > Net::getLayerInputs(int layerId) const
{
LayerData &ld = impl->getLayerData(layerId);
std::vector<String> res;
res.reserve(impl->layers.size());
- Impl::MapIdToLayerData::iterator it;
+ Impl::MapIdToLayerData::const_iterator it;
for (it = impl->layers.begin(); it != impl->layers.end(); it++)
{
if (it->second.id) //skip Data layer
{
std::vector<int> layersIds;
- Impl::MapIdToLayerData::iterator it;
+ Impl::MapIdToLayerData::const_iterator it;
for (it = impl->layers.begin(); it != impl->layers.end(); it++)
{
int lid = it->first;
- LayerData &ld = it->second;
+ const LayerData &ld = it->second;
if (ld.requiredOutputs.size() == 0)
layersIds.push_back(lid);
int64 Net::getFLOPS(const int layerId,
const std::vector<MatShape>& netInputShapes) const
{
- Impl::MapIdToLayerData::iterator layer = impl->layers.find(layerId);
+ Impl::MapIdToLayerData::const_iterator layer = impl->layers.find(layerId);
CV_Assert(layer != impl->layers.end());
LayerShapes shapes;
impl->getLayerShapes(netInputShapes, layerId, shapes);
- return layer->second.getLayerInstance()->getFLOPS(shapes.in, shapes.out);
+ return const_cast<LayerData&>(layer->second).getLayerInstance()->getFLOPS(shapes.in, shapes.out);
}
int64 Net::getFLOPS(const int layerId,
layersTypes.clear();
std::map<String, int> layers;
- for (Impl::MapIdToLayerData::iterator it = impl->layers.begin();
+ for (Impl::MapIdToLayerData::const_iterator it = impl->layers.begin();
it != impl->layers.end(); it++)
{
if (layers.find(it->second.type) == layers.end())
layers[it->second.type]++;
}
- for (std::map<String, int>::iterator it = layers.begin();
+ for (std::map<String, int>::const_iterator it = layers.begin();
it != layers.end(); it++)
{
layersTypes.push_back(it->first);
int Net::getLayersCount(const String& layerType) const
{
int count = 0;
- for (Impl::MapIdToLayerData::iterator it = impl->layers.begin();
+ for (Impl::MapIdToLayerData::const_iterator it = impl->layers.begin();
it != impl->layers.end(); it++)
{
if (it->second.type == layerType)
{
CV_TRACE_FUNCTION();
- Impl::MapIdToLayerData::iterator layer = impl->layers.find(layerId);
+ Impl::MapIdToLayerData::const_iterator layer = impl->layers.find(layerId);
CV_Assert(layer != impl->layers.end());
weights = blobs = 0;
for(int i = 0; i < layerIds.size(); i++)
{
int w = 0, b = 0;
- Impl::MapIdToLayerData::iterator layer = impl->layers.find(layerIds[i]);
+ Impl::MapIdToLayerData::const_iterator layer = impl->layers.find(layerIds[i]);
CV_Assert(layer != impl->layers.end());
for(int j = 0; j < layer->second.params.blobs.size(); j++)
projects / platform / upstream / opencv.git / commitdiff