Doc Migration (master) (#1377)
* Doc Migration from Gitlab (#1289) * doc migration * fix * Update FakeQuantize_1.md * Update performance_benchmarks.md * Updates graphs for FPGA * Update performance_benchmarks.md * Change DL Workbench structure (#1) * Changed DL Workbench structure * Fixed tags * fixes * Update ie_docs.xml * Update performance_benchmarks_faq.md * Fixes in DL Workbench layout * Fixes for CVS-31290 * [DL Workbench] Minor correction * Fix for CVS-30955 * Added nGraph deprecation notice as requested by Zoe * fix broken links in api doxy layouts * CVS-31131 fixes * Additional fixes * Fixed POT TOC * Update PAC_Configure.md PAC DCP 1.2.1 install guide. * Update inference_engine_intro.md * fix broken link * Update opset.md * fix * added opset4 to layout * added new opsets to layout, set labels for them * Update VisionAcceleratorFPGA_Configure.md Updated from 2020.3 to 2020.4 Co-authored-by: domi2000 <domi2000@users.noreply.github.com>
This commit is contained in:
Nikolay Tyukaev
GitHub
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docs/IE_DG/API_Changes.md
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docs/IE_DG/API_Changes.md
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# Inference Engine API Changes History {#openvino_docs_IE_DG_API_Changes}
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The sections below contain detailed list of changes made to the Inference Engine API in recent releases.
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## Deprecation Notice
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<table>
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<tr>
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<td><strong>Deprecation Begins</strong></td>
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<td>June 1, 2020</td>
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</tr>
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<tr>
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<td><strong>Removal Date</strong></td>
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<td>December 1, 2020</td>
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</tr>
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</table>
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Starting with the OpenVINO™ toolkit 2020.2 release, all of the features previously available through nGraph have been merged into the OpenVINO™ toolkit. As a result, all the features previously available through ONNX RT Execution Provider for nGraph have been merged with ONNX RT Execution Provider for OpenVINO™ toolkit.
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Therefore, ONNX RT Execution Provider for nGraph will be deprecated starting June 1, 2020 and will be completely removed on December 1, 2020. Users are recommended to migrate to the ONNX RT Execution Provider for OpenVINO™ toolkit as the unified solution for all AI inferencing on Intel® hardware.
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## 2020.4
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### New API
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**CPU Plugin API:**
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* InferenceEngine::PluginConfigParams::KEY_ENFORCE_BF16 config key
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|
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**Metrics and values for Query API:**
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* METRIC_KEY(OPTIMIZATION_CAPABILITIES)
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* METRIC_VALUE(BF16)
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## 2020.2
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### New API
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**Extensibility API:**
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* InferenceEngine::IExtension::getImplTypes(const std::shared_ptr<ngraph::Node>& node) method
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* InferenceEngine::IExtension::getImplementation(const std::shared_ptr<ngraph::Node>& node, const std::string& implType) method
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### Deprecated API
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**Extensibility API:**
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* InferenceEngine::ILayerImplFactory class
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* InferenceEngine::IShapeInferImpl class
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* InferenceEngine::IShapeInferImpl class
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* InferenceEngine::IShapeInferExtension class
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* InferenceEngine::IExtension::getFactoryFor(ILayerImplFactory\*& factory, const CNNLayer\* cnnLayer, ResponseDesc\* resp) noexcept method
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* InferenceEngine::IExtension::getPrimitiveTypes(char\*\*& types, unsigned int& size, ResponseDesc\* resp) noexcept method
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* InferenceEngine::ShapeInferImpl class
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* InferenceEngine::Extension::getFactoryFor(ILayerImplFactory\*& factory, const CNNLayer\* cnnLayer, ResponseDesc\* resp) noexcept method
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* InferenceEngine::Extension::getPrimitiveTypes(char\*\*& types, unsigned int& size, ResponseDesc\* resp) noexcept method
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**Network API:**
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* InferenceEngine::details::CNNNetworkIterator class
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* InferenceEngine::CNNNetwork::getPrecision() const method
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* InferenceEngine::CNNNetwork::getLayerByName(const char\* layerName) const method
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* InferenceEngine::CNNNetwork::size() const method
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* InferenceEngine::CNNNetwork::begin() const method
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* InferenceEngine::CNNNetwork::end() const method
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* InferenceEngine::CNNNetwork::AddExtension(const IShapeInferExtensionPtr& extension) method
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* InferenceEngine::ICNNNetwork::getPrecision() const noexcept method
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* InferenceEngine::ICNNNetwork::getName(char\* pName, size_t len) const noexcept method
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* InferenceEngine::ICNNNetwork::getData(const char\* dname) noexcept method
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* InferenceEngine::ICNNNetwork::addLayer(const CNNLayerPtr& layer) noexcept method
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* InferenceEngine::ICNNNetwork::getLayerByName(const char\* layerName, CNNLayerPtr& out, ResponseDesc\* resp) const noexcept method
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* InferenceEngine::ICNNNetwork::AddExtension(const IShapeInferExtensionPtr& extension, ResponseDesc\* resp) noexcept method
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* InferenceEngine::ICNNNetwork::getStats(ICNNNetworkStats\*\* stats, ResponseDesc\* resp) const noexcept method
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* InferenceEngine::ICNNNetworkStats class
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* InferenceEngine::NetworkNodeStats class
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* InferenceEngine::Data::getCreatorLayer() method
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* InferenceEngine::Data::getInputTo() method
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* InferenceEngine::LayerParams class
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**Layer API:**
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* InferenceEngine::CNNLayer class
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* InferenceEngine::WeightableLayer class
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* InferenceEngine::BatchNormalizationLayer class
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* InferenceEngine::BatchToSpaceLayer class
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* InferenceEngine::BinaryConvolutionLayer class
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* InferenceEngine::BroadcastLayer class
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* InferenceEngine::BucketizeLayer class
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* InferenceEngine::ClampLayer class
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* InferenceEngine::ConcatLayer class
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* InferenceEngine::ConvolutionLayer class
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* InferenceEngine::CropLayer class
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* InferenceEngine::DeconvolutionLayer class
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* InferenceEngine::DeformableConvolutionLayer class
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* InferenceEngine::DepthToSpaceLayer class
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* InferenceEngine::EltwiseLayer class
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* InferenceEngine::ExperimentalDetectronPriorGridGenerator class
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* InferenceEngine::ExperimentalDetectronPriorGridGeneratorLayer class
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* InferenceEngine::ExperimentalSparseWeightedReduceLayer class
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* InferenceEngine::FillLayer class
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* InferenceEngine::FullyConnectedLayer class
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* InferenceEngine::GRNLayer class
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* InferenceEngine::GRUCell class
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* InferenceEngine::GatherLayer class
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* InferenceEngine::GemmLayer class
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* InferenceEngine::LSTMCell class
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* InferenceEngine::MVNLayer class
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* InferenceEngine::MathLayer class
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* InferenceEngine::NonMaxSuppression class
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* InferenceEngine::NormLayer class
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* InferenceEngine::OneHotLayer class
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* InferenceEngine::PReLULayer class
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* InferenceEngine::PadLayer class
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* InferenceEngine::PoolingLayer class
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* InferenceEngine::PowerLayer class
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* InferenceEngine::QuantizeLayer class
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* InferenceEngine::RNNCell class
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* InferenceEngine::RNNCellBase class
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* InferenceEngine::RNNSequenceLayer class
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* InferenceEngine::RangeLayer class
|
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* InferenceEngine::ReLU6Layer class
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* InferenceEngine::ReLULayer class
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* InferenceEngine::ReduceLayer class
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* InferenceEngine::ReshapeLayer class
|
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* InferenceEngine::ReverseSequenceLayer class
|
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* InferenceEngine::ScaleShiftLayer class
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* InferenceEngine::ScatterLayer class
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* InferenceEngine::SelectLayer class
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* InferenceEngine::ShuffleChannelsLayer class
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* InferenceEngine::SoftMaxLayer class
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* InferenceEngine::SpaceToBatchLayer class
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* InferenceEngine::SpaceToDepthLayer class
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* InferenceEngine::SparseFillEmptyRowsLayer class
|
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* InferenceEngine::SparseSegmentReduceLayer class
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* InferenceEngine::SparseToDenseLayer class
|
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* InferenceEngine::SplitLayer class
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* InferenceEngine::StridedSliceLayer class
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* InferenceEngine::TensorIterator class
|
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* InferenceEngine::TileLayer class
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* InferenceEngine::TopKLayer class
|
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* InferenceEngine::UniqueLayer class
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## 2020.1
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|
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### New API
|
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|
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**Integration with ngraph API:**
|
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|
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* InferenceEngine::CNNNetwork(const std::shared_ptr<ngraph::Function>& network) ctor from ngraph::Function
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* InferenceEngine::CNNNetwork::getFunction() const noexcept method
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* InferenceEngine::ICNNNetwork::getFunction() const noexcept method
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* InferenceEngine::Parameter(const std::shared_ptr<ngraph::Variant>& var) ctor
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* InferenceEngine::Parameter::asVariant() const method
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* InferenceEngine::Parameter::operator std::shared_ptr<ngraph::Variant>() const operator
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* InferenceEngine::Core::ReadNetwork(const std::wstring& modelPath, const std::wstring& binPath) method
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* InferenceEngine::Core::ReadNetwork(const std::string& modelPath, const std::string& binPath = "") method
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* InferenceEngine::Core::ReadNetwork(const std::string& model, const Blob::CPtr& weights) method
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* InferenceEngine::Code::AddExtension(const IExtensionPtr& extension) method
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* InferenceEngine::IExtension::getOpSets() method
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**Offline compilation: import / export to std::stream:**
|
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|
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* InferenceEngine::ExecutableNetwork::Export(std::ostream& networkModel) method
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* InferenceEngine::Core::ImportNetwork(std::istream& networkModel, const std::string& deviceName = {}, const std::map<std::string, std::string>& config = {}) method
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* InferenceEngine::IExecutableNetwork::Export(std::ostream& networkModel, ResponseDesc \*resp) noexcept method
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|
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|
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**RemoteBlob accelerator memory sharing API:**
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|
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* InferenceEngine::RemoteContext class
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* InferenceEngine::RemoteBlob class
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* InferenceEngine::Core::CreateContext(const std::string& deviceName, const ParamMap& params) method
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* InferenceEngine::Core::GetDefaultContext(const std::string& deviceName) method
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* InferenceEngine::Core::LoadNetwork(CNNNetwork network, RemoteContext::Ptr context, const std::map<std::string, std::string>& config = std::map<std::string, std::string>()) method
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|
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**GNA firmware model image generation:**
|
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|
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* GNA_CONFIG_KEY(FIRMWARE_MODEL_IMAGE_GENERATION) config key
|
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* GNA_CONFIG_VALUE(GEN) value
|
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* GNA_CONFIG_VALUE(GEN_EXACT) value
|
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* GNA_CONFIG_VALUE(SSE) value
|
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* GNA_CONFIG_VALUE(SSE_EXACT) value
|
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* GNA_CONFIG_VALUE(AVX1) value
|
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* GNA_CONFIG_VALUE(AVX1_EXACT) value
|
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* GNA_CONFIG_VALUE(AVX2) value
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* GNA_CONFIG_VALUE(AVX2_EXACT) value
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**MemoryBlob mapping of memory to the user space:**
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|
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* InferenceEngine::MemoryBlob::rwmap() noexcept method
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* InferenceEngine::MemoryBlob::rmap() noexcept method
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* InferenceEngine::MemoryBlob::wmap() noexcept method
|
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|
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**Memory interoperability on acceleration devices. General classes and GPU helper functions**
|
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* InferenceEngine::RemoteBlob class
|
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* InferenceEngine::RemoteContext class
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* InferenceEngine::Core::CreateContext(const std::string& deviceName, const ParamMap& params) method
|
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* InferenceEngine::Core::GetDefaultContext(const std::string& deviceName) method
|
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* InferenceEngine::make_shared_blob(const TensorDesc& desc, RemoteContext::Ptr ctx) function
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* InferenceEngine::gpu::make_shared_blob_nv12(size_t height, size_t width, RemoteContext::Ptr ctx, VASurfaceID nv12_surf) function
|
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* InferenceEngine::gpu::make_shared_context(Core& core, std::string deviceName, VADisplay device) function
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* InferenceEngine::gpu::make_shared_blob(const TensorDesc& desc, RemoteContext::Ptr ctx, VASurfaceID surface, uint32_t plane = 0) function
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* InferenceEngine::gpu::make_shared_blob_nv12(RemoteContext::Ptr ctx, cl::Image2D& nv12_image_plane_y, cl::Image2D& nv12_image_plane_uv) function
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* InferenceEngine::gpu::make_shared_context(Core& core, std::string deviceName, cl_context ctx) function
|
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* InferenceEngine::gpu::make_shared_blob(const TensorDesc& desc, ClContext::Ptr ctx) function
|
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* InferenceEngine::gpu::make_shared_blob(const TensorDesc& desc, RemoteContext::Ptr ctx, cl::Buffer& buffer) function
|
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* InferenceEngine::gpu::make_shared_blob(const TensorDesc& desc, RemoteContext::Ptr ctx, cl_mem buffer) function
|
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* InferenceEngine::gpu::make_shared_blob(const TensorDesc& desc, RemoteContext::Ptr ctx, cl::Image2D& image) function
|
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|
||||
### Deprecated API
|
||||
|
||||
**Inference Engine NN Builder API:**
|
||||
|
||||
* InferenceEngine::Builder::EltwiseLayer
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* InferenceEngine::Builder::MemoryLayer
|
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* InferenceEngine::Builder::ROIPoolingLayer
|
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* InferenceEngine::Builder::DeconvolutionLayer
|
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* InferenceEngine::Builder::ReLULayer
|
||||
* InferenceEngine::Builder::TanHLayer
|
||||
* InferenceEngine::Builder::InputLayer
|
||||
* InferenceEngine::Builder::PoolingLayer
|
||||
* InferenceEngine::Builder::CropLayer
|
||||
* InferenceEngine::Builder::GRUSequenceLayer
|
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* InferenceEngine::Builder::NormLayer
|
||||
* InferenceEngine::Builder::LSTMSequenceLayer
|
||||
* InferenceEngine::Builder::ClampLayer
|
||||
* InferenceEngine::Builder::PSROIPoolingLayer
|
||||
* InferenceEngine::Builder::Layer
|
||||
* InferenceEngine::Builder::RNNSequenceLayer
|
||||
* InferenceEngine::Builder::ReorgYoloLayer
|
||||
* InferenceEngine::Builder::NormalizeLayer
|
||||
* InferenceEngine::Builder::PriorBoxClusteredLayer
|
||||
* InferenceEngine::Builder::MVNLayer
|
||||
* InferenceEngine::Builder::PermuteLayer
|
||||
* InferenceEngine::Builder::SimplerNMSLayer
|
||||
* InferenceEngine::Builder::ConstLayer
|
||||
* InferenceEngine::Builder::DeformableConvolutionLayer
|
||||
* InferenceEngine::Builder::FullyConnectedLayer
|
||||
* InferenceEngine::Builder::PriorBoxLayer
|
||||
* InferenceEngine::Builder::SoftMaxLayer
|
||||
* InferenceEngine::Builder::OutputLayer
|
||||
* InferenceEngine::Builder::TileLayer
|
||||
* InferenceEngine::Builder::SplitLayer
|
||||
* InferenceEngine::Builder::PReLULayer
|
||||
* InferenceEngine::Builder::RegionYoloLayer
|
||||
* InferenceEngine::Builder::ReshapeLayer
|
||||
* InferenceEngine::Builder::ConvolutionLayer
|
||||
* InferenceEngine::Builder::DetectionOutputLayer
|
||||
* InferenceEngine::Builder::ConcatLayer
|
||||
* InferenceEngine::Builder::ELULayer
|
||||
* InferenceEngine::Builder::GRNLayer
|
||||
* InferenceEngine::Builder::LRNLayer
|
||||
* InferenceEngine::Builder::ArgMaxLayer
|
||||
* InferenceEngine::Builder::ReLU6Layer
|
||||
* InferenceEngine::Builder::ScaleShiftLayer
|
||||
* InferenceEngine::Builder::ProposalLayer
|
||||
* InferenceEngine::Builder::SigmoidLayer
|
||||
* InferenceEngine::Builder::ResampleLayer
|
||||
* InferenceEngine::Builder::CTCGreedyDecoderLayer
|
||||
* InferenceEngine::Builder::BatchNormalizationLayer
|
||||
* InferenceEngine::Builder::LayerDecorator
|
||||
* InferenceEngine::Builder::PowerLayer
|
||||
* InferenceEngine::Builder::Network
|
||||
* InferenceEngine::Builder::PortInfo
|
||||
* InferenceEngine::Builder::Connection
|
||||
* InferenceEngine::Builder::PortData
|
||||
* InferenceEngine::Builder::Port
|
||||
* InferenceEngine::Builder::ILayer
|
||||
* InferenceEngine::Builder::INetworkIterator
|
||||
* InferenceEngine::Builder::INetwork
|
||||
* InferenceEngine::Builder::ILayer
|
||||
|
||||
|
||||
**Plugin API:**
|
||||
|
||||
* InferenceEngine::InferencePlugin C++ plugin wrapper class
|
||||
* InferenceEngine::IInferencePlugin plugin interface
|
||||
* InferenceEngine::PluginDispatcher class
|
||||
* InferenceEngine::InferenceEnginePluginPtr typedef
|
||||
* InferenceEngine::ICNNNetReader reader interface
|
||||
* InferenceEngine::CNNNetReader class
|
||||
|
||||
**Blob API:**
|
||||
|
||||
* Blob::element_size() const noexcept method
|
||||
* Blob::buffer() noexcept method
|
||||
* Blob::cbuffer() noexcept method
|
||||
* MemoryBlob::buffer() noexcept method
|
||||
* MemoryBlob::cbuffer() noexcept method
|
||||
|
||||
|
||||
### Removed API
|
||||
|
||||
Removed all [Inference Engine API which deprecated in 2019'R2](https://docs.openvinotoolkit.org/2019_R3/_docs_IE_DG_API_Changes.html#deprecated_api)
|
||||
|
||||
## 2019 R3
|
||||
|
||||
### New API
|
||||
|
||||
**New supported layers:**
|
||||
|
||||
* InferenceEngine::SparseFillEmptyRowsLayer new class
|
||||
* InferenceEngine::UniqueLayer new class
|
||||
* InferenceEngine::NonMaxSuppressionLayer new class
|
||||
* InferenceEngine::ScatterLayer new class
|
||||
|
||||
**FPGA plugin streaming support:**
|
||||
|
||||
* DLIA_METRIC_VALUE(INPUT_STREAMING) value to METRIC_KEY(OPTIMIZATION_CAPABILITIES)
|
||||
* DLIA_CONFIG_KEY(ENABLE_STREAMING) config key
|
||||
|
||||
### Removed API
|
||||
|
||||
* InferenceEngine::EltwiseLayer::Select from InferenceEngine::EltwiseLayer::eOperation enumeration
|
||||
|
||||
## 2019 R2
|
||||
|
||||
### New API
|
||||
|
||||
**Inference Engine Core API:**
|
||||
|
||||
* Introduced InferenceEngine::Core high level class to manage devices
|
||||
|
||||
**Query API extensions to InferenceEngine::ExecutableNetwork and InferenceEngine::IExecutableNetwork:**
|
||||
|
||||
* InferenceEngine::ExecutableNetwork::SetConfig method
|
||||
* InferenceEngine::ExecutableNetwork::GetConfig method
|
||||
* InferenceEngine::ExecutableNetwork::GetMetric method
|
||||
* InferenceEngine::IExecutableNetwork::SetConfig method
|
||||
* InferenceEngine::IExecutableNetwork::GetConfig method
|
||||
* InferenceEngine::IExecutableNetwork::GetMetric method
|
||||
|
||||
**Metrics and values for Query API:**
|
||||
|
||||
* METRIC_KEY(AVAILABLE_DEVICES)
|
||||
* METRIC_KEY(SUPPORTED_METRICS)
|
||||
* METRIC_KEY(SUPPORTED_CONFIG_KEYS)
|
||||
* METRIC_KEY(FULL_DEVICE_NAME)
|
||||
* METRIC_KEY(OPTIMIZATION_CAPABILITIES)
|
||||
* METRIC_VALUE(FP32)
|
||||
* METRIC_VALUE(FP16)
|
||||
* METRIC_VALUE(INT8)
|
||||
* METRIC_VALUE(BIN)
|
||||
* METRIC_VALUE(WINOGRAD)
|
||||
* DLIA_METRIC_VALUE(FP11)
|
||||
* METRIC_KEY(RANGE_FOR_STREAMS)
|
||||
* METRIC_KEY(NUMBER_OF_WAITING_INFER_REQUESTS)
|
||||
* METRIC_KEY(NUMBER_OF_EXEC_INFER_REQUESTS)
|
||||
* METRIC_KEY(DEVICE_THERMAL)
|
||||
* METRIC_KEY(RANGE_FOR_ASYNC_INFER_REQUESTS)
|
||||
* EXEC_NETWORK_METRIC_KEY(NETWORK_NAME)
|
||||
* EXEC_NETWORK_METRIC_KEY(OPTIMAL_NUMBER_OF_INFER_REQUESTS)
|
||||
|
||||
**Common API:**
|
||||
|
||||
* CLDNN_CONFIG_KEY(INT8_ENABLED) config key
|
||||
* CONFIG_KEY(GPU_THROUGHPUT_AUTO)
|
||||
* CONFIG_KEY(GPU_THROUGHPUT_STREAMS)
|
||||
* DLIA_CONFIG_KEY(IO_TRANSFORMATIONS_NATIVE) config key
|
||||
* DLIA_CONFIG_KEY(DUMP_SUPPORTED_LAYERS_INFORMATION) config key
|
||||
* GNA_CONFIG_VALUE(SW_FP32) config value for GNA_CONFIG_KEY(DEVICE_MODE) key
|
||||
* MULTI_CONFIG_KEY(DEVICE_PRIORITIES) config key for `MULTI` device
|
||||
* InferenceEngine::CNNNetReader::ReadNetwork(const std::wstring &filepath) new method
|
||||
* InferenceEngine::CNNNetReader::ReadWeights(const std::wstring &filepath) new method
|
||||
* InferenceEngine::ExecutableNetwork::ExecutableNetwork(IExecutableNetwork::Ptr actual, InferenceEnginePluginPtr plg) constructor with additional `plg` parameter
|
||||
* InferenceEngine::InferRequest::InferRequest(IInferRequest::Ptr request, InferenceEnginePluginPtr plg) constructor with additional `plg` parameter
|
||||
* InferenceEngine::Data::setName method
|
||||
* InferenceEngine::QueryNetworkResult::supportedLayersMap
|
||||
* InferenceEngine::Precision::I64 extension to InferenceEngine::Precision::ePrecision enumeration
|
||||
|
||||
**New supported primitives:**
|
||||
|
||||
* InferenceEngine::Builder::DeformableConvolutionLayer new class
|
||||
* InferenceEngine::DeformableConvolutionLayer new class
|
||||
* InferenceEngine::EltwiseLayer::Logical_NOT, InferenceEngine::EltwiseLayer::Mean, InferenceEngine::EltwiseLayer::Select extensions to InferenceEngine::EltwiseLayer::eOperation enumeration
|
||||
* InferenceEngine::OneHotLayer new class
|
||||
* InferenceEngine::SelectLayer new class
|
||||
* InferenceEngine::BroadcastLayer new class
|
||||
* InferenceEngine::MathLayer new class
|
||||
* InferenceEngine::ReduceLayer new class
|
||||
* InferenceEngine::TopKLayer new class
|
||||
|
||||
**Extensions to Blob creation API:**
|
||||
|
||||
* InferenceEngine::Blob::is method
|
||||
* InferenceEngine::Blob::is const method
|
||||
* InferenceEngine::Blob::as method
|
||||
* InferenceEngine::Blob::as const method
|
||||
* InferenceEngine::Blob::getAllocator abstract method
|
||||
* InferenceEngine::Blob::getHandle abstract method
|
||||
* InferenceEngine::MemoryBlob class
|
||||
* InferenceEngine::ColorFormat enumeration
|
||||
* InferenceEngine::PreProcessInfo::setColorFormat method
|
||||
* InferenceEngine::PreProcessInfo::getColorFormat method
|
||||
* InferenceEngine::CompoundBlob class to work with blobs consisting of several planes
|
||||
* InferenceEngine::NV12Blob class representing NV12 blob with two planes
|
||||
|
||||
### Deprecated API
|
||||
|
||||
The methods listed below are deprecated and will be removed in 2019 R4 release:
|
||||
|
||||
**Common API:**
|
||||
|
||||
* InferenceEngine::InputInfo::getInputPrecision method
|
||||
* InferenceEngine::InputInfo::setInputPrecision method
|
||||
* InferenceEngine::InputInfo::getDims method
|
||||
* InferenceEngine::CNNLayer::GetParamsAsBool method
|
||||
* InferenceEngine::CNNNetwork::CNNNetwork(ICNNNetwork* actual) constructor
|
||||
* InferenceEngine::CNNNetwork::setTargetDevice method
|
||||
* HETERO_CONFIG_KEY(DUMP_DLA_MESSAGES) config key
|
||||
* InferenceEngine::ILayerImplFactory::getShapes method
|
||||
* InferenceEngine::IShapeInferImpl::inferShapes(const std::vector<SizeVector>&, const std::map<std::string, std::string>& , const std::map<std::string, Blob::Ptr>&, std::vector<SizeVector>&, ResponseDesc\*) method
|
||||
* InferenceEngine::Data::setBatchSize method
|
||||
* InferenceEngine::QueryNetworkResult::supportedLayers field
|
||||
* InferenceEngine::ICNNNetwork::setBatchSize(const size_t size) method
|
||||
* InferenceEngine::Blob::Resize method
|
||||
* InferenceEngine::Blob::Reshape method
|
||||
* InferenceEngine::TBlob::set method
|
||||
|
||||
**InferenceEngine::IInferencePlugin and InferenceEngine:InferencePlugin obsolete methods:**
|
||||
|
||||
* InferenceEngine::InferencePlugin::LoadNetwork(ICNNNetwork &network) method
|
||||
* InferenceEngine::InferencePlugin::Infer method
|
||||
* InferenceEngine::InferencePlugin::GetPerformanceCounts method
|
||||
* InferenceEngine::InferencePlugin::QueryNetwork(const ICNNNetwork &network, QueryNetworkResult &res) const method
|
||||
* InferenceEngine::IInferencePlugin::LoadNetwork(ICNNNetwork &network, ResponseDesc \*resp) method
|
||||
* InferenceEngine::IInferencePlugin::Infer(const Blob &input, Blob &result, ResponseDesc \*resp) method
|
||||
* InferenceEngine::IInferencePlugin::Infer(const BlobMap &input, BlobMap &result, ResponseDesc \*resp) method
|
||||
* InferenceEngine::IInferencePlugin::GetPerformanceCounts method
|
||||
* InferenceEngine::IInferencePlugin::QueryNetwork(const ICNNNetwork& network, QueryNetworkResult& res) const method
|
||||
|
||||
|
||||
**Fields in InferenceEngine::Data class are replaced with appropriate methods:**
|
||||
|
||||
* InferenceEngine::Data::precision field
|
||||
* InferenceEngine::Data::layout field
|
||||
* InferenceEngine::Data::dims field
|
||||
* InferenceEngine::Data::creatorLayer field
|
||||
* InferenceEngine::Data::name field
|
||||
* InferenceEngine::Data::inputTo field
|
||||
* InferenceEngine::Data::userObject field
|
||||
|
||||
**Heterogeneous plugin:**
|
||||
|
||||
* InferenceEngine::IHeteroDeviceLoader class
|
||||
* InferenceEngine::IHeteroInferencePlugin class
|
||||
* InferenceEngine::HeteroPluginPtr class
|
||||
* operator InferenceEngine::InferencePlugin::HeteroPluginPtr operator
|
||||
|
||||
**Blob creation API with dimensions in reverse order:**
|
||||
|
||||
* InferenceEngine::Blob::Blob(Precision p) constructor
|
||||
* InferenceEngine::Blob::Blob(Precision p, Layout l) constructor
|
||||
* InferenceEngine::Blob::Blob(Precision p, const SizeVector &dims) constructor
|
||||
* InferenceEngine::Blob::Blob(Precision p, Layout l, const SizeVector &dims) constructor
|
||||
* InferenceEngine::TBlob::TBlob(Precision p, Layout l) constructor
|
||||
* InferenceEngine::TBlob::TBlob(Precision p, Layout l, const SizeVector& dims) constructor
|
||||
* InferenceEngine::TBlob::TBlob(Precision p, Layout l, const SizeVector& dims, T* ptr, size_t data_size) constructor
|
||||
* InferenceEngine::TBlob::TBlob(Precision p, Layout l, const SizeVector &dims, std::shared_ptr<IAllocator> alloc) constructor
|
||||
* InferenceEngine::Blob::type() method
|
||||
* InferenceEngine::Blob::precision() method
|
||||
* InferenceEngine::Blob::layout() method
|
||||
* InferenceEngine::Blob::dims() method
|
||||
* InferenceEngine::make_shared_blob(Precision p, Layout l, const SizeVector &dims) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, const SizeVector &dims) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, Layout l, const TArg &arg) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, const TArg &arg) function
|
||||
* InferenceEngine::make_shared_blob(TBlob<TypeTo> &&arg) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, Layout l) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, Layout l, SizeVector dims, const std::vector<TypeTo> &arg) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, Layout l, const std::vector<TypeTo> &arg) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, const std::vector<TypeTo> &arg) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, Layout l, const SizeVector &dims, TypeTo * ptr, size_t size) function
|
||||
* InferenceEngine::make_shared_blob(Precision p, const SizeVector &dims, TypeTo * ptr, size_t size) function
|
||||
* InferenceEngine::I_N variable
|
||||
* InferenceEngine::I_C variable
|
||||
* InferenceEngine::I_H variable
|
||||
* InferenceEngine::I_W variable
|
||||
* InferenceEngine::LayoutOffsetCounter class
|
||||
* InferenceEngine::ConvertLayout function
|
||||
|
||||
**API working with device enumeration:**
|
||||
|
||||
* InferenceEngine::TargetDevice enumeration
|
||||
* InferenceEngine::TargetDeviceInfo class
|
||||
* InferenceEngine::getDeviceName function
|
||||
* InferenceEngine::FindPluginRequest class
|
||||
* InferenceEngine::FindPluginResponse class
|
||||
* InferenceEngine::findPlugin(const FindPluginRequest &req, FindPluginResponse &result, ResponseDesc *resp) function
|
||||
* InferenceEngine::ICNNNetwork::setTargetDevice method
|
||||
* InferenceEngine::ICNNNetwork::getTargetDevice method
|
||||
* InferenceEngine::PluginDispatcher::getPluginByDevice method
|
||||
* InferenceEngine::PluginDispatcher::getSuitablePlugin method
|
||||
Reference in New Issue
Block a user