ONNX Importer in MO

CMakeLists.txt

@@ -107,6 +107,7 @@ function(build_ngraph)
     set(SDL_cmake_included ON)
     add_subdirectory(ngraph)
     set(NGRAPH_LIBRARIES ngraph PARENT_SCOPE)
+    set(FRONTEND_LIBRARIES frontend_manager PARENT_SCOPE)
     set(NGRAPH_REF_LIBRARIES ngraph_reference PARENT_SCOPE)
 endfunction()
 

inference-engine/samples/benchmark_app/CMakeLists.txt

@@ -8,6 +8,6 @@ file (GLOB HDR ${CMAKE_CURRENT_SOURCE_DIR}/*.hpp)
 ie_add_sample(NAME benchmark_app
               SOURCES ${SRC}
               HEADERS ${HDR}
-              DEPENDENCIES format_reader ie_samples_utils
-              OPENCV_DEPENDENCIES core)
+              DEPENDENCIES format_reader ie_samples_utils frontend_manager
+              OPENCV_DEPENDENCIES imgcodecs)
 

inference-engine/samples/benchmark_app/main.cpp

@@ -17,6 +17,8 @@
 #include <vector>
 #include <vpu/vpu_plugin_config.hpp>
 
+#include <frontend_manager/frontend_manager.hpp>
+
 #include "benchmark_app.hpp"
 #include "infer_request_wrap.hpp"
 #include "inputs_filling.hpp"
@@ -338,7 +340,79 @@ int main(int argc, char* argv[]) {
             slog::info << "Loading network files" << slog::endl;
 
             auto startTime = Time::now();
-            CNNNetwork cnnNetwork = ie.ReadNetwork(FLAGS_m);
+
+            //////////////////////////////////////////////////////////////
+
+            //CNNNetwork cnnNetwork = ie.ReadNetwork(FLAGS_m);
+
+            ngraph::frontend::FrontEndManager manager;
+            auto FE = manager.loadByFramework("onnx");
+            auto inputModel = FE->loadFromFile(FLAGS_m);
+
+            int test_scenario = 2;
+
+            // The next test cases are applicable for resnet50-v1-7.onnx model from the official repository
+
+            switch (test_scenario) {
+                case 0: {
+                    inputModel->setPartialShape(inputModel->getInputs()[0], ngraph::PartialShape({10, 3, 224, 224}));
+                    break;
+                }
+                case 1: {
+                    auto new_input = inputModel->getPlaceByTensorName("resnetv17_conv0_fwd");
+                    inputModel->overrideAllInputs({inputModel->getPlaceByTensorName("resnetv17_conv0_fwd")});
+                    break;
+                }
+                case 2: {
+                    auto new_input = inputModel->getPlaceByTensorName("resnetv17_conv0_fwd");
+                    inputModel->overrideAllInputs({new_input});
+                    inputModel->setPartialShape(new_input, ngraph::PartialShape({2, 64, 112, 112}));
+                    break;
+                }
+                case 3: {
+                    auto new_input = inputModel->getPlaceByTensorName("resnetv17_conv0_fwd");
+                    inputModel->setPartialShape(new_input, ngraph::PartialShape({2, 64, 112, 112}));
+                    inputModel->overrideAllInputs({new_input});
+                    break;
+                }
+                case 4: {
+                    auto new_input = inputModel->getPlaceByTensorName("resnetv17_conv0_fwd");
+                    inputModel->setPartialShape(new_input, ngraph::PartialShape({2, 64, 112, 112}));
+                    inputModel->overrideAllInputs({new_input});
+                    break;
+                }
+                case 5: {
+                    // Multiple consumers for a tensor, should be converted to a single Parameter
+                    auto new_input = inputModel->getPlaceByTensorName("resnetv17_pool0_fwd");
+                    inputModel->overrideAllInputs({new_input});
+                    break;
+                }
+                case 6: {
+                    // Split usages of a tensor to two Parameters; using ports instead of tensors
+                    auto new_input = inputModel->getPlaceByTensorName("resnetv17_pool0_fwd");
+                    auto ports = new_input->getConsumingPorts();
+                    inputModel->overrideAllInputs({ports[0], ports[1]});  // it is known there are two ports
+                    break;
+                }
+                case 7: {
+                    auto new_output_1 = inputModel->getPlaceByTensorName("resnetv17_stage1_conv2_fwd");
+                    auto new_output_2 = inputModel->getPlaceByTensorName("resnetv17_stage1_conv3_fwd");
+                    inputModel->overrideAllOutputs({new_output_1, new_output_2});
+                    break;
+                }
+            }
+
+#if 1 // Complete convert
+            auto ngFunc = FE->convert(inputModel);
+#else // Decode first, than finalize conversion -- should give identical to simple `convert` result
+            auto ngFunc = FE->decode(inputModel);
+            FE->convert(ngFunc);
+#endif
+            CNNNetwork cnnNetwork(ngFunc);
+            cnnNetwork.serialize("benchmark_app_loaded_network.xml");
+
+            /////////////////////////////////////////////////////////////
+
             auto duration_ms = double_to_string(get_total_ms_time(startTime));
             slog::info << "Read network took " << duration_ms << " ms" << slog::endl;
             if (statistics)

inference-engine/samples/hello_classification/CMakeLists.txt

@@ -4,6 +4,6 @@
 
 ie_add_sample(NAME hello_classification
               SOURCES "${CMAKE_CURRENT_SOURCE_DIR}/main.cpp"
-              DEPENDENCIES ie_samples_utils
+              DEPENDENCIES ie_samples_utils frontend_manager
               OPENCV_DEPENDENCIES core imgcodecs)
 

inference-engine/samples/hello_classification/main.cpp

@@ -130,7 +130,6 @@ int main(int argc, char* argv[]) {
         DataPtr output_info = network.getOutputsInfo().begin()->second;
         std::string output_name = network.getOutputsInfo().begin()->first;
 
-        output_info->setPrecision(Precision::FP32);
         // -----------------------------------------------------------------------------------------------------
 
         // --------------------------- Step 4. Loading a model to the device

inference-engine/src/CMakeLists.txt

@@ -51,5 +51,5 @@ add_custom_target(ie_libraries ALL
                           inference_engine_lp_transformations inference_engine_snippets)
 
 if(NGRAPH_ONNX_IMPORT_ENABLE)
-    add_dependencies(ie_libraries inference_engine_onnx_reader)
+    add_dependencies(ie_libraries inference_engine_onnx_reader frontend_manager)
 endif()

inference-engine/src/inference_engine/CMakeLists.txt

@@ -125,6 +125,7 @@ target_compile_definitions(${TARGET_NAME}_obj PRIVATE IMPLEMENT_INFERENCE_ENGINE
                                                       $<TARGET_PROPERTY:ngraph::ngraph,INTERFACE_COMPILE_DEFINITIONS>)
 
 target_include_directories(${TARGET_NAME}_obj SYSTEM PRIVATE $<TARGET_PROPERTY:ngraph::ngraph,INTERFACE_INCLUDE_DIRECTORIES>
+        $<TARGET_PROPERTY:ngraph::frontend_manager,INTERFACE_INCLUDE_DIRECTORIES>
                                                              $<TARGET_PROPERTY:pugixml,INTERFACE_INCLUDE_DIRECTORIES>
                                                              $<TARGET_PROPERTY:xbyak,INTERFACE_INCLUDE_DIRECTORIES>)
 
@@ -162,7 +163,7 @@ if (TBBBIND_2_4_FOUND)
 endif()
 
 target_link_libraries(${TARGET_NAME} PRIVATE pugixml openvino::itt ${CMAKE_DL_LIBS} Threads::Threads
-                                             ${NGRAPH_LIBRARIES} inference_engine_transformations)
+                                             ${NGRAPH_LIBRARIES} ${FRONTEND_LIBRARIES} inference_engine_transformations)
 
 target_include_directories(${TARGET_NAME} INTERFACE ${PUBLIC_HEADERS_DIR}
     PRIVATE $<TARGET_PROPERTY:${TARGET_NAME}_plugin_api,INTERFACE_INCLUDE_DIRECTORIES>

inference-engine/src/inference_engine/ie_core.cpp

@@ -15,6 +15,7 @@
 #include <ngraph/ngraph.hpp>
 #include <ngraph/graph_util.hpp>
 #include <ngraph/pass/constant_folding.hpp>
+#include <frontend_manager/frontend_manager.hpp>
 
 #include "compilation_context.hpp"
 #include "ie_plugin_cpp.hpp"
@@ -207,6 +208,7 @@ class Core::Impl : public ICore {
 
     std::unordered_set<std::string> opsetNames;
     std::vector<IExtensionPtr> extensions;
+    //ngraph::frontend::FrontEndManager frontEndManager;
 
     std::map<std::string, PluginDescriptor> pluginRegistry;
     mutable std::mutex pluginsMutex;  // to lock parallel access to pluginRegistry and plugins

inference-engine/src/inference_engine/xml_parse_utils.cpp

@@ -12,6 +12,23 @@
 
 #include "ie_precision.hpp"
 
+template <typename T>
+bool is_bool_value(const std::string & str, T & val) {
+    std::string tmp;
+    for (const auto ch : str) {
+        tmp += std::tolower(ch);
+    }
+    if (tmp == "true") {
+        val = 1;
+        return true;
+    }
+    if (tmp == "false") {
+        val = 0;
+        return true;
+    }
+    return false;
+}
+
 int XMLParseUtils::GetIntAttr(const pugi::xml_node& node, const char* str) {
     auto attr = node.attribute(str);
     if (attr.empty())
@@ -20,10 +37,11 @@ int XMLParseUtils::GetIntAttr(const pugi::xml_node& node, const char* str) {
     std::string str_value = std::string(attr.value());
     std::size_t idx = 0;
     int int_value = std::stoi(str_value, &idx, 10);
-    if (idx != str_value.length())
-        IE_THROW() << "node <" << node.name() << "> has attribute \"" << str << "\" = \"" << str_value
-                           << "\" which is not an integer"
-                           << " at offset " << node.offset_debug();
+//mnosov: TODO - commented out according to rebase
+//    if (idx != str_value.length())
+//        IE_THROW() << "node <" << node.name() << "> has attribute \"" << str << "\" = \"" << str_value
+//                           << "\" which is not an integer"
+//                           << " at offset " << node.offset_debug();
     return int_value;
 }
 
@@ -65,10 +83,11 @@ unsigned int XMLParseUtils::GetUIntAttr(const pugi::xml_node& node, const char*
     std::string str_value = std::string(attr.value());
     std::size_t idx = 0;
     long long int_value = std::stoll(str_value, &idx, 10);
-    if (idx != str_value.length() || int_value < 0 || int_value > (std::numeric_limits<unsigned int>::max)())
-        IE_THROW() << "node <" << node.name() << "> has attribute \"" << str << "\" = \"" << str_value
-                           << "\" which is not an unsigned integer"
-                           << " at offset " << node.offset_debug();
+// TODO: mnosov: commented out according to rebase
+//    if (idx != str_value.length() || int_value < 0 || int_value > (std::numeric_limits<unsigned int>::max)())
+//        IE_THROW() << "node <" << node.name() << "> has attribute \"" << str << "\" = \"" << str_value
+//                           << "\" which is not an unsigned integer"
+//                           << " at offset " << node.offset_debug();
     return static_cast<unsigned int>(int_value);
 }
 

inference-engine/src/plugin_api/ie_ngraph_utils.hpp

@@ -134,6 +134,8 @@ inline Precision convertPrecision(const ::ngraph::element::Type& precision) {
         return Precision(Precision::BIN);
     case ::ngraph::element::Type_t::boolean:
         return Precision(Precision::BOOL);
+    case ::ngraph::element::Type_t::dynamic:
+        return Precision(Precision::UNSPECIFIED);
     default:
         IE_THROW() << "Incorrect precision " << precision.get_type_name() << "!"; return{};
     }

inference-engine/src/transformations/src/transformations/serialize.cpp

@@ -11,6 +11,7 @@
 #include <unordered_set>
 
 #include <ngraph/variant.hpp>
+#include <assert.h>
 #include "ngraph/ops.hpp"
 #include "ngraph/opsets/opset.hpp"
 #include "ngraph/opsets/opset1.hpp"
@@ -502,6 +503,7 @@ std::string get_opset_name(
 std::string get_precision_name(const ngraph::element::Type & elem_type) {
     switch (elem_type) {
     case ::ngraph::element::Type_t::undefined:
+    case ::ngraph::element::Type_t::dynamic:
         return "UNSPECIFIED";
     case ::ngraph::element::Type_t::f16:
         return "FP16";
@@ -542,17 +544,6 @@ std::string get_precision_name(const ngraph::element::Type & elem_type) {
     }
 }
 
-std::string escape_delim(const std::string& name, const char delim = ',') {
-    std::string result_name = name;
-    const std::string escaped_delim = std::string("\\") + delim;
-    size_t index = result_name.find(delim, 0);
-    while (index != std::string::npos) {
-        result_name.replace(index, 1, escaped_delim);
-        index = result_name.find(delim, index + 2);
-    }
-    return result_name;
-}
-
 std::string generate_unique_name(
     const std::unordered_set<std::string>& unique_names, std::string base_name,
     int suffix) {
@@ -565,6 +556,17 @@ std::string generate_unique_name(
     }
 }
 
+std::string escape_delim(const std::string& name, const char delim = ',') {
+    std::string result_name = name;
+    const std::string escaped_delim = std::string("\\") + delim;
+    size_t index = result_name.find(delim, 0);
+    while (index != std::string::npos) {
+        result_name.replace(index, 1, escaped_delim);
+        index = result_name.find(delim, index + 2);
+    }
+    return result_name;
+}
+
 // TODO: remove when CNNNetwork will be supporting not-unique names
 std::string get_node_unique_name(std::unordered_set<std::string>& unique_names,
                                  const ngraph::Node* n) {
@@ -721,9 +723,6 @@ void ngfunction_2_irv10(pugi::xml_node& netXml,
         if (node->get_input_size() > 0) {
             pugi::xml_node input = layer.append_child("input");
             for (const auto & i : node->inputs()) {
-                NGRAPH_CHECK(i.get_partial_shape().is_static(),
-                             "Unsupported dynamic input shape in ", node);
-
                 // WA for LSTMCellv0, peephole input shall not be serialized
                 if (i.get_index() == 6 && dynamic_cast<opset1::LSTMCell *>(node)) {
                     port_id++;
@@ -734,10 +733,10 @@ void ngfunction_2_irv10(pugi::xml_node& netXml,
                 port.append_attribute("id").set_value(port_id++);
                 port.append_attribute("precision")
                         .set_value(get_precision_name(i.get_element_type()).c_str());
-                for (auto d : i.get_shape()) {
+                for (auto d : std::vector<Dimension>(i.get_partial_shape())) {
                     pugi::xml_node dim = port.append_child("dim");
                     dim.append_child(pugi::xml_node_type::node_pcdata)
-                        .set_value(std::to_string(d).c_str());
+                        .set_value(std::to_string(d.get_max_length()).c_str());
                 }
             }
 
@@ -765,10 +764,10 @@ void ngfunction_2_irv10(pugi::xml_node& netXml,
                 if (!names.empty()) {
                     port.append_attribute("names").set_value(names.c_str());
                 }
-                for (auto d : o.get_shape()) {
+                for (auto d : std::vector<Dimension>(o.get_partial_shape())) {
                     pugi::xml_node dim = port.append_child("dim");
                     dim.append_child(pugi::xml_node_type::node_pcdata)
-                        .set_value(std::to_string(d).c_str());
+                        .set_value(std::to_string(d.get_max_length()).c_str());
                 }
             }
             if (node_type_name == "TensorIterator" || node_type_name == "Loop") {

model-optimizer/extensions/front/user_data_repack.py

@@ -30,3 +30,10 @@ def find_and_replace_pattern(self, graph: Graph):
         inputs = list(packed_user_shapes.keys()) \
             if packed_user_shapes is not None and isinstance(packed_user_shapes, dict) else None
         graph.graph['inputs'] = inputs  # save user defined inputs for other extensions
+
+        print('---------- Inputs/outpus -----------')
+        print(packed_user_shapes)
+        print(packed_outputs)
+        print(freeze_placeholder)
+        print(inputs)
+        print('------------------------------------')