Add a mutex for shared Inference Engine plugins

modules/dnn/src/op_inf_engine.cpp

@@ -622,7 +622,11 @@ void InfEngineBackendNet::init(int targetId)
 
 #endif  // IE < R5
 
-static std::map<InferenceEngine::TargetDevice, InferenceEngine::InferenceEnginePluginPtr> sharedPlugins;
+static std::map<InferenceEngine::TargetDevice, InferenceEngine::InferenceEnginePluginPtr>& getSharedPlugins()
+{
+    static std::map<InferenceEngine::TargetDevice, InferenceEngine::InferenceEnginePluginPtr> sharedPlugins;
+    return sharedPlugins;
+}
 
 void InfEngineBackendNet::initPlugin(InferenceEngine::ICNNNetwork& net)
 {
@@ -630,6 +634,8 @@ void InfEngineBackendNet::initPlugin(InferenceEngine::ICNNNetwork& net)
 
     try
     {
+        AutoLock lock(getInitializationMutex());
+        auto& sharedPlugins = getSharedPlugins();
         auto pluginIt = sharedPlugins.find(targetDevice);
         if (pluginIt != sharedPlugins.end())
         {
@@ -797,7 +803,8 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
 void resetMyriadDevice()
 {
 #ifdef HAVE_INF_ENGINE
-    sharedPlugins.erase(InferenceEngine::TargetDevice::eMYRIAD);
+    AutoLock lock(getInitializationMutex());
+    getSharedPlugins().erase(InferenceEngine::TargetDevice::eMYRIAD);
 #endif  // HAVE_INF_ENGINE
 }
 

modules/dnn/test/test_layers.cpp

@@ -46,6 +46,10 @@
 #include <opencv2/dnn/all_layers.hpp>
 #include <opencv2/dnn/layer.details.hpp>  // CV_DNN_REGISTER_LAYER_CLASS
 
+#ifdef HAVE_INF_ENGINE
+#include <thread>
+#endif
+
 namespace opencv_test { namespace {
 
 template<typename TString>
@@ -970,6 +974,36 @@ TEST_P(Layer_Test_Convolution_DLDT, setInput_uint8)
     if (targetId != DNN_TARGET_MYRIAD)
         normAssert(outs[0], outs[1]);
 }
+
+TEST_P(Layer_Test_Convolution_DLDT, multithreading)
+{
+    Target targetId = GetParam();
+    std::string suffix = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? "_fp16" : "";
+    std::string xmlPath = _tf("layer_convolution" + suffix + ".xml");
+    std::string binPath = _tf("layer_convolution" + suffix + ".bin");
+    Net firstNet = readNet(xmlPath, binPath);
+    Net secondNet = readNet(xmlPath, binPath);
+    Mat inp = blobFromNPY(_tf("blob.npy"));
+
+    firstNet.setInput(inp);
+    secondNet.setInput(inp);
+    firstNet.setPreferableTarget(targetId);
+    secondNet.setPreferableTarget(targetId);
+
+    Mat out1, out2;
+    std::thread t1([&]{out1 = firstNet.forward();});
+    std::thread t2([&]{out2 = secondNet.forward();});
+
+    t1.join();
+    t2.join();
+
+    Mat ref = blobFromNPY(_tf("layer_convolution.npy"));
+    double l1 = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? 1.5e-3 : 1e-5;
+    double lInf = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? 1.8e-2 : 1e-4;
+    normAssert(out1, ref, "first thread", l1, lInf);
+    normAssert(out2, ref, "second thread", l1, lInf);
+}
+
 INSTANTIATE_TEST_CASE_P(/**/, Layer_Test_Convolution_DLDT,
     testing::ValuesIn(getAvailableTargets(DNN_BACKEND_INFERENCE_ENGINE)));