Merge remote-tracking branch 'upstream/master' into move_node_to_ov

cmake/developer_package/plugins/plugins.cmake

@@ -112,8 +112,8 @@ function(ie_add_plugin)
     if(TARGET inference_engine_ir_v7_reader)
         add_dependencies(${IE_PLUGIN_NAME} inference_engine_ir_v7_reader)
     endif()
-    if(TARGET inference_engine_onnx_reader)
-        add_dependencies(${IE_PLUGIN_NAME} inference_engine_onnx_reader)
+    if(TARGET onnx_ngraph_frontend)
+        add_dependencies(${IE_PLUGIN_NAME} onnx_ngraph_frontend)
     endif()
 
     # install rules

docs/IE_DG/Deep_Learning_Inference_Engine_DevGuide.md

@@ -43,10 +43,10 @@ This library contains the classes to:
 Starting from 2020.4 release, Inference Engine introduced a concept of `CNNNetwork` reader plugins. Such plugins can be automatically dynamically loaded by Inference Engine in runtime depending on file format:
 * Linux* OS:
     - `libinference_engine_ir_reader.so` to read a network from IR
-    - `libinference_engine_onnx_reader.so` to read a network from ONNX model format
+    - `onnx_ngraph_frontend.so` to read a network from ONNX model format
 * Windows* OS:
     - `inference_engine_ir_reader.dll` to read a network from IR
-    - `inference_engine_onnx_reader.dll` to read a network from ONNX model format
+    - `onnx_ngraph_frontend.dll` to read a network from ONNX model format
 
 ### Device-Specific Plugin Libraries
 

docs/IE_DG/inference_engine_intro.md

@@ -46,10 +46,10 @@ This library contains the classes to:
 Starting from 2020.4 release, Inference Engine introduced a concept of `CNNNetwork` reader plugins. Such plugins can be automatically dynamically loaded by Inference Engine in runtime depending on file format:
 * Unix* OS:
     - `libinference_engine_ir_reader.so` to read a network from IR
-    - `libinference_engine_onnx_reader.so` to read a network from ONNX model format
+    - `onnx_ngraph_frontend.so` to read a network from ONNX model format
 * Windows* OS:
     - `inference_engine_ir_reader.dll` to read a network from IR
-    - `inference_engine_onnx_reader.dll` to read a network from ONNX model format
+    - `onnx_ngraph_frontend.dll` to read a network from ONNX model format
 
 ### Device-specific Plugin Libraries ###
 

inference-engine/src/CMakeLists.txt

@@ -54,5 +54,5 @@ add_custom_target(ie_libraries ALL
                           ir_frontend)
 
 if(NGRAPH_ONNX_FRONTEND_ENABLE)
-    add_dependencies(ie_libraries inference_engine_onnx_reader)
+    add_dependencies(ie_libraries onnx_ngraph_frontend)
 endif()

inference-engine/src/gna_plugin/optimizer/gna_pass_manager.cpp

@@ -1841,8 +1841,8 @@ void FuseFQIntoWeightsPass::run() {
             layers_connected_to_fq_count = inputTo.size();
         }
         for (int index = 0; index < layers_connected_to_fq_count; index++) {
-            auto weightableLayer = CNNNetGetNextLayerSkipCertain(layerBeforeWeightable, 0, index, isNonFunctional).first;
-            if (!LayerInfo(weightableLayer).isWeightable()) {
+            auto weightableLayer = CNNNetCheckNextLayerSkipCertain(layerBeforeWeightable, 0, index, true, isNonFunctional).first;
+            if (!weightableLayer || !LayerInfo(weightableLayer).isWeightable()) {
                 continue;
             }
             if (weightableLayer->insData.size() < 2) {

inference-engine/src/inference_engine/src/ie_network_reader.cpp

@@ -96,6 +96,11 @@ namespace {
 // Extension to plugins creator
 std::multimap<std::string, Reader::Ptr> readers;
 
+static ngraph::frontend::FrontEndManager* get_frontend_manager() {
+    static ngraph::frontend::FrontEndManager manager;
+    return &manager;
+}
+
 void registerReaders() {
     OV_ITT_SCOPED_TASK(ov::itt::domains::IE, "registerReaders");
     static bool initialized = false;
@@ -115,14 +120,6 @@ void registerReaders() {
         return std::make_shared<Reader>(name, library_name);
     };
 
-    // try to load ONNX reader if library exists
-    auto onnxReader =
-        create_if_exists("ONNX", std::string("inference_engine_onnx_reader") + std::string(IE_BUILD_POSTFIX));
-    if (onnxReader) {
-        readers.emplace("onnx", onnxReader);
-        readers.emplace("prototxt", onnxReader);
-    }
-
     // try to load IR reader v10 if library exists
     auto irReaderv10 =
         create_if_exists("IRv10", std::string("inference_engine_ir_reader") + std::string(IE_BUILD_POSTFIX));
@@ -174,10 +171,6 @@ CNNNetwork details::ReadNetwork(const std::string& modelPath,
 #endif
     // Try to open model file
     std::ifstream modelStream(model_path, std::ios::binary);
-    // save path in extensible array of stream
-    // notice: lifetime of path pointed by pword(0) is limited by current scope
-    const std::string path_to_save_in_stream = modelPath;
-    modelStream.pword(0) = const_cast<char*>(path_to_save_in_stream.c_str());
     if (!modelStream.is_open())
         IE_THROW() << "Model file " << modelPath << " cannot be opened!";
 
@@ -240,7 +233,7 @@ CNNNetwork details::ReadNetwork(const std::string& modelPath,
         }
     }
     // Try to load with FrontEndManager
-    static ngraph::frontend::FrontEndManager manager;
+    const auto manager = get_frontend_manager();
     ngraph::frontend::FrontEnd::Ptr FE;
     ngraph::frontend::InputModel::Ptr inputModel;
     if (!binPath.empty()) {
@@ -249,17 +242,17 @@ CNNNetwork details::ReadNetwork(const std::string& modelPath,
 #else
         std::string weights_path = binPath;
 #endif
-        FE = manager.load_by_model(model_path, weights_path);
+        FE = manager->load_by_model(model_path, weights_path);
         if (FE)
             inputModel = FE->load(model_path, weights_path);
     } else {
-        FE = manager.load_by_model(model_path);
+        FE = manager->load_by_model(model_path);
         if (FE)
             inputModel = FE->load(model_path);
     }
     if (inputModel) {
         auto ngFunc = FE->convert(inputModel);
-        return CNNNetwork(ngFunc);
+        return CNNNetwork(ngFunc, exts);
     }
     IE_THROW() << "Unknown model format! Cannot find reader for model format: " << fileExt
                << " and read the model: " << modelPath << ". Please check that reader library exists in your PATH.";
@@ -282,6 +275,19 @@ CNNNetwork details::ReadNetwork(const std::string& model,
             return reader->read(modelStream, exts);
         }
     }
+    // Try to load with FrontEndManager
+    // NOTE: weights argument is ignored
+    const auto manager = get_frontend_manager();
+    ngraph::frontend::FrontEnd::Ptr FE;
+    ngraph::frontend::InputModel::Ptr inputModel;
+    FE = manager->load_by_model(&modelStream);
+    if (FE)
+        inputModel = FE->load(&modelStream);
+    if (inputModel) {
+        auto ngFunc = FE->convert(inputModel);
+        return CNNNetwork(ngFunc, exts);
+    }
+
     IE_THROW() << "Unknown model format! Cannot find reader for the model and read it. Please check that reader "
                   "library exists in your PATH.";
 }

inference-engine/src/mkldnn_plugin/mkldnn_graph.cpp

@@ -1028,6 +1028,8 @@ void MKLDNNGraph::DropDWConvNode(const MKLDNNNodePtr &node) {
     auto parentConv = parentConvEdge->getParent();
     if (!parentConv) return;
 
+    parentConv->outputShapes[0] = node->outputShapes[0];
+
     for (size_t i = 0; i < 1; i++) {
         auto p_edge = parents[i].lock();
         if (!p_edge) continue;

inference-engine/src/readers/CMakeLists.txt

@@ -17,7 +17,3 @@ add_cpplint_target(${TARGET_NAME}_cpplint FOR_SOURCES ${reader_api_hpp})
 
 add_subdirectory(ir_reader)
 add_subdirectory(ir_reader_v7)
-
-if(NGRAPH_ONNX_FRONTEND_ENABLE)
-    add_subdirectory(onnx_reader)
-endif()