Release 18.05

18 files changed, 406 insertions, 127 deletions

diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt
index 6bc88178f5..ecdff7f909 100644
--- a/tests/CMakeLists.txt
+++ b/tests/CMakeLists.txt
@@ -127,6 +127,12 @@ if(BUILD_TF_PARSER)
         MobileNetDatabase.hpp
         MobileNetDatabase.cpp)
     TfParserTest(TfInceptionV3-Armnn "${TfInceptionV3-Armnn_sources}")
+
+    set(TfResNext-Armnn_sources
+        TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp
+        ImageNetDatabase.hpp
+        ImageNetDatabase.cpp)
+    TfParserTest(TfResNext-Armnn "${TfResNext-Armnn_sources}")
 endif()
 
 if (BUILD_CAFFE_PARSER OR BUILD_TF_PARSER)
diff --git a/tests/CaffeAlexNet-Armnn/CaffeAlexNet-Armnn.cpp b/tests/CaffeAlexNet-Armnn/CaffeAlexNet-Armnn.cpp
index c50d8ea05f..dce4e08d05 100644
--- a/tests/CaffeAlexNet-Armnn/CaffeAlexNet-Armnn.cpp
+++ b/tests/CaffeAlexNet-Armnn/CaffeAlexNet-Armnn.cpp
@@ -8,7 +8,21 @@
 
 int main(int argc, char* argv[])
 {
-    return armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnCaffeParser::ICaffeParser>(
-        argc, argv, "bvlc_alexnet_1.caffemodel", true, "data", "prob", { 0 },
-        [](const char* dataDir) { return ImageNetDatabase(dataDir); });
+    int retVal = EXIT_FAILURE;
+    try
+    {
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnCaffeParser::ICaffeParser>(
+                     argc, argv, "bvlc_alexnet_1.caffemodel", true, "data", "prob", { 0 },
+                     [](const char* dataDir) { return ImageNetDatabase(dataDir); });
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: CaffeAlexNet-Armnn: An error has occurred when running the "
+                     "classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/CaffeCifar10AcrossChannels-Armnn/CaffeCifar10AcrossChannels-Armnn.cpp b/tests/CaffeCifar10AcrossChannels-Armnn/CaffeCifar10AcrossChannels-Armnn.cpp
index 9994bb5431..fbd3312f04 100644
--- a/tests/CaffeCifar10AcrossChannels-Armnn/CaffeCifar10AcrossChannels-Armnn.cpp
+++ b/tests/CaffeCifar10AcrossChannels-Armnn/CaffeCifar10AcrossChannels-Armnn.cpp
@@ -8,8 +8,22 @@
 
 int main(int argc, char* argv[])
 {
-    return armnn::test::ClassifierInferenceTestMain<Cifar10Database, armnnCaffeParser::ICaffeParser>(
-        argc, argv, "cifar10_full_iter_60000.caffemodel", true, "data", "prob",
-        { 0, 1, 2, 4, 7 },
-        [](const char* dataDir) { return Cifar10Database(dataDir); });
+    int retVal = EXIT_FAILURE;
+    try
+    {
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<Cifar10Database, armnnCaffeParser::ICaffeParser>(
+                    argc, argv, "cifar10_full_iter_60000.caffemodel", true, "data", "prob",
+                    { 0, 1, 2, 4, 7 },
+                    [](const char* dataDir) { return Cifar10Database(dataDir); });
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: CaffeCifar10AcrossChannels-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/CaffeInception_BN-Armnn/CaffeInception_BN-Armnn.cpp b/tests/CaffeInception_BN-Armnn/CaffeInception_BN-Armnn.cpp
index 557a3b00f4..a6581bea55 100644
--- a/tests/CaffeInception_BN-Armnn/CaffeInception_BN-Armnn.cpp
+++ b/tests/CaffeInception_BN-Armnn/CaffeInception_BN-Armnn.cpp
@@ -8,12 +8,28 @@
 
 int main(int argc, char* argv[])
 {
-    std::vector<ImageSet> imageSet =
+    int retVal = EXIT_FAILURE;
+    try
     {
-        {"shark.jpg", 3694}
-    };
-    return armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnCaffeParser::ICaffeParser>(
-        argc, argv, "Inception-BN-batchsize1.caffemodel", true,
-        "data", "softmax", { 0 },
-        [&imageSet](const char* dataDir) { return ImageNetDatabase(dataDir, 224, 224, imageSet); });
+        // Coverity fix: The following code may throw an exception of type std::length_error.
+        std::vector<ImageSet> imageSet =
+        {
+            {"shark.jpg", 3694}
+        };
+
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnCaffeParser::ICaffeParser>(
+                    argc, argv, "Inception-BN-batchsize1.caffemodel", true,
+                    "data", "softmax", { 0 },
+                    [&imageSet](const char* dataDir) { return ImageNetDatabase(dataDir, 224, 224, imageSet); });
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: CaffeInception_BN-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/CaffeMnist-Armnn/CaffeMnist-Armnn.cpp b/tests/CaffeMnist-Armnn/CaffeMnist-Armnn.cpp
index 5b8864d73d..ec14a5d7bc 100644
--- a/tests/CaffeMnist-Armnn/CaffeMnist-Armnn.cpp
+++ b/tests/CaffeMnist-Armnn/CaffeMnist-Armnn.cpp
@@ -8,8 +8,22 @@
 
 int main(int argc, char* argv[])
 {
-    return armnn::test::ClassifierInferenceTestMain<MnistDatabase, armnnCaffeParser::ICaffeParser>(
-        argc, argv, "lenet_iter_9000.caffemodel", true, "data", "prob",
-        { 0, 1, 5, 8, 9 },
-        [](const char* dataDir) { return MnistDatabase(dataDir); });
+    int retVal = EXIT_FAILURE;
+    try
+    {
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<MnistDatabase, armnnCaffeParser::ICaffeParser>(
+                    argc, argv, "lenet_iter_9000.caffemodel", true, "data", "prob",
+                    { 0, 1, 5, 8, 9 },
+                    [](const char* dataDir) { return MnistDatabase(dataDir); });
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: CaffeMnist-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/CaffeResNet-Armnn/CaffeResNet-Armnn.cpp b/tests/CaffeResNet-Armnn/CaffeResNet-Armnn.cpp
index ed304f8b0c..7cccb215a1 100644
--- a/tests/CaffeResNet-Armnn/CaffeResNet-Armnn.cpp
+++ b/tests/CaffeResNet-Armnn/CaffeResNet-Armnn.cpp
@@ -8,16 +8,32 @@
 
 int main(int argc, char* argv[])
 {
-    std::vector<ImageSet> imageSet =
+    int retVal = EXIT_FAILURE;
+    try
     {
-        {"ILSVRC2012_val_00000018.JPEG",  21 },
-        {"shark.jpg", 2}
-    };
+        // Coverity fix: The following code may throw an exception of type std::length_error.
+        std::vector<ImageSet> imageSet =
+        {
+            {"ILSVRC2012_val_00000018.JPEG",  21 },
+            {"shark.jpg", 2}
+        };
 
-    armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
-    return armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnCaffeParser::ICaffeParser>(
-        argc, argv, "ResNet_50_ilsvrc15_model.caffemodel", true,
-        "data", "prob", { 0, 1 },
-        [&imageSet](const char* dataDir) { return ImageNetDatabase(dataDir, 224, 224, imageSet); },
-        &inputTensorShape);
+        armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
+
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnCaffeParser::ICaffeParser>(
+                    argc, argv, "ResNet_50_ilsvrc15_model.caffemodel", true,
+                    "data", "prob", { 0, 1 },
+                    [&imageSet](const char* dataDir) { return ImageNetDatabase(dataDir, 224, 224, imageSet); },
+                    &inputTensorShape);
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: CaffeResNet-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/CaffeVGG-Armnn/CaffeVGG-Armnn.cpp b/tests/CaffeVGG-Armnn/CaffeVGG-Armnn.cpp
index e7fc55c7e7..b859042935 100644
--- a/tests/CaffeVGG-Armnn/CaffeVGG-Armnn.cpp
+++ b/tests/CaffeVGG-Armnn/CaffeVGG-Armnn.cpp
@@ -9,9 +9,23 @@
 int main(int argc, char* argv[])
 {
     armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
-    return armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnCaffeParser::ICaffeParser>(
-        argc, argv, "VGG_CNN_S.caffemodel", true,
-        "input", "prob", { 0 },
-        [](const char* dataDir) { return ImageNetDatabase(dataDir, 224, 224); },
-        &inputTensorShape);
+    int retVal = EXIT_FAILURE;
+    try
+    {
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnCaffeParser::ICaffeParser>(
+                    argc, argv, "VGG_CNN_S.caffemodel", true,
+                    "input", "prob", { 0 },
+                    [](const char* dataDir) { return ImageNetDatabase(dataDir, 224, 224); },
+                    &inputTensorShape);
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: CaffeVGG-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/CaffeYolo-Armnn/CaffeYolo-Armnn.cpp b/tests/CaffeYolo-Armnn/CaffeYolo-Armnn.cpp
index af60be95ec..ad79d49f0c 100644
--- a/tests/CaffeYolo-Armnn/CaffeYolo-Armnn.cpp
+++ b/tests/CaffeYolo-Armnn/CaffeYolo-Armnn.cpp
@@ -13,27 +13,42 @@ int main(int argc, char* argv[])
     using YoloInferenceModel = InferenceModel<armnnCaffeParser::ICaffeParser,
         float>;
 
-    return InferenceTestMain(argc, argv, { 0 },
-        [&inputTensorShape]()
-        {
-            return make_unique<YoloTestCaseProvider<YoloInferenceModel>>(
-                [&]
-                (typename YoloInferenceModel::CommandLineOptions modelOptions)
-                {
-                    if (!ValidateDirectory(modelOptions.m_ModelDir))
+    int retVal = EXIT_FAILURE;
+    try
+    {
+        // Coverity fix: InferenceTestMain() may throw uncaught exceptions.
+        retVal = InferenceTestMain(argc, argv, { 0 },
+            [&inputTensorShape]()
+            {
+                return make_unique<YoloTestCaseProvider<YoloInferenceModel>>(
+                    [&]
+                    (typename YoloInferenceModel::CommandLineOptions modelOptions)
                     {
-                        return std::unique_ptr<YoloInferenceModel>();
-                    }
+                        if (!ValidateDirectory(modelOptions.m_ModelDir))
+                        {
+                            return std::unique_ptr<YoloInferenceModel>();
+                        }
 
-                    typename YoloInferenceModel::Params modelParams;
-                    modelParams.m_ModelPath = modelOptions.m_ModelDir + "yolov1_tiny_voc2007_model.caffemodel";
-                    modelParams.m_InputBinding = "data";
-                    modelParams.m_OutputBinding = "fc12";
-                    modelParams.m_InputTensorShape = &inputTensorShape;
-                    modelParams.m_IsModelBinary = true;
-                    modelParams.m_ComputeDevice = modelOptions.m_ComputeDevice;
+                        typename YoloInferenceModel::Params modelParams;
+                        modelParams.m_ModelPath = modelOptions.m_ModelDir + "yolov1_tiny_voc2007_model.caffemodel";
+                        modelParams.m_InputBinding = "data";
+                        modelParams.m_OutputBinding = "fc12";
+                        modelParams.m_InputTensorShape = &inputTensorShape;
+                        modelParams.m_IsModelBinary = true;
+                        modelParams.m_ComputeDevice = modelOptions.m_ComputeDevice;
+                        modelParams.m_VisualizePostOptimizationModel = modelOptions.m_VisualizePostOptimizationModel;
 
-                    return std::make_unique<YoloInferenceModel>(modelParams);
+                        return std::make_unique<YoloInferenceModel>(modelParams);
+                });
             });
-        });
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: CaffeYolo-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/ExecuteNetwork/ExecuteNetwork.cpp b/tests/ExecuteNetwork/ExecuteNetwork.cpp
index 04ab195816..74737e2718 100644
--- a/tests/ExecuteNetwork/ExecuteNetwork.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetwork.cpp
@@ -31,7 +31,16 @@ std::vector<T> ParseArrayImpl(std::istream& stream, TParseElementFunc parseEleme
     while (std::getline(stream, line))
     {
         std::vector<std::string> tokens;
-        boost::split(tokens, line, boost::algorithm::is_any_of("\t ,;:"), boost::token_compress_on);
+        try
+        {
+            // Coverity fix: boost::split() may throw an exception of type boost::bad_function_call.
+            boost::split(tokens, line, boost::algorithm::is_any_of("\t ,;:"), boost::token_compress_on);
+        }
+        catch (const std::exception& e)
+        {
+            BOOST_LOG_TRIVIAL(error) << "An error occurred when splitting tokens: " << e.what();
+            continue;
+        }
         for (const std::string& token : tokens)
         {
             if (!token.empty()) // See https://stackoverflow.com/questions/10437406/
@@ -219,7 +228,17 @@ int main(int argc, char* argv[])
     {
         std::stringstream ss(inputTensorShapeStr);
         std::vector<unsigned int> dims = ParseArray<unsigned int>(ss);
-        inputTensorShape = std::make_unique<armnn::TensorShape>(dims.size(), dims.data());
+
+        try
+        {
+            // Coverity fix: An exception of type armnn::InvalidArgumentException is thrown and never caught.
+            inputTensorShape = std::make_unique<armnn::TensorShape>(dims.size(), dims.data());
+        }
+        catch (const armnn::InvalidArgumentException& e)
+        {
+            BOOST_LOG_TRIVIAL(fatal) << "Cannot create tensor shape: " << e.what();
+            return 1;
+        }
     }
 
     // Forward to implementation based on the parser type
diff --git a/tests/InferenceModel.hpp b/tests/InferenceModel.hpp
index c390ccdc2f..f5f00378ca 100644
--- a/tests/InferenceModel.hpp
+++ b/tests/InferenceModel.hpp
@@ -3,15 +3,19 @@
 // See LICENSE file in the project root for full license information.
 //
 #pragma once
-
 #include "armnn/ArmNN.hpp"
+#include "HeapProfiling.hpp"
 
+#include <boost/exception/exception.hpp>
+#include <boost/exception/diagnostic_information.hpp>
 #include <boost/log/trivial.hpp>
 #include <boost/format.hpp>
 #include <boost/program_options.hpp>
+#include <boost/filesystem.hpp>
 
 #include <map>
 #include <string>
+#include <fstream>
 
 template<typename TContainer>
 inline armnn::InputTensors MakeInputTensors(const std::pair<armnn::LayerBindingId, armnn::TensorInfo>& input,
@@ -19,8 +23,16 @@ inline armnn::InputTensors MakeInputTensors(const std::pair<armnn::LayerBindingI
 {
     if (inputTensorData.size() != input.second.GetNumElements())
     {
-        throw armnn::Exception(boost::str(boost::format("Input tensor has incorrect size. Expected %1% elements "
-            "but got %2%.") % input.second.GetNumElements() % inputTensorData.size()));
+        try
+        {
+            throw armnn::Exception(boost::str(boost::format("Input tensor has incorrect size. Expected %1% elements "
+                "but got %2%.") % input.second.GetNumElements() % inputTensorData.size()));
+        } catch (const boost::exception& e)
+        {
+            // Coverity fix: it should not be possible to get here but boost::str and boost::format can both
+            // throw uncaught exceptions - convert them to armnn exceptions and rethrow
+            throw armnn::Exception(diagnostic_information(e));
+        }
     }
     return { { input.first, armnn::ConstTensor(input.second, inputTensorData.data()) } };
 }
@@ -46,6 +58,7 @@ public:
     {
         std::string m_ModelDir;
         armnn::Compute m_ComputeDevice;
+        bool m_VisualizePostOptimizationModel;
     };
 
     static void AddCommandLineOptions(boost::program_options::options_description& desc, CommandLineOptions& options)
@@ -56,7 +69,11 @@ public:
             ("model-dir,m", po::value<std::string>(&options.m_ModelDir)->required(),
                 "Path to directory containing model files (.caffemodel/.prototxt)")
             ("compute,c", po::value<armnn::Compute>(&options.m_ComputeDevice)->default_value(armnn::Compute::CpuAcc),
-                "Which device to run layers on by default. Possible choices: CpuAcc, CpuRef, GpuAcc");
+                "Which device to run layers on by default. Possible choices: CpuAcc, CpuRef, GpuAcc")
+            ("visualize-optimized-model,v",
+                po::value<bool>(&options.m_VisualizePostOptimizationModel)->default_value(false),
+             "Produce a dot file useful for visualizing the graph post optimization."
+                "The file will have the same name as the model with the .dot extention.");
     }
 
     struct Params
@@ -67,11 +84,13 @@ public:
         const armnn::TensorShape* m_InputTensorShape;
         armnn::Compute m_ComputeDevice;
         bool m_IsModelBinary;
+        bool m_VisualizePostOptimizationModel;
 
         Params()
          : m_InputTensorShape(nullptr)
          , m_ComputeDevice(armnn::Compute::CpuRef)
          , m_IsModelBinary(true)
+         , m_VisualizePostOptimizationModel(false)
         {
         }
     };
@@ -92,19 +111,38 @@ public:
         }
         std::vector<std::string> requestedOutputs{ params.m_OutputBinding };
 
-        // Handle text and binary input differently by calling the corresponding parser function
-        armnn::INetworkPtr network = (params.m_IsModelBinary ?
-          parser->CreateNetworkFromBinaryFile(modelPath.c_str(), inputShapes, requestedOutputs) :
-          parser->CreateNetworkFromTextFile(modelPath.c_str(), inputShapes, requestedOutputs));
+        armnn::INetworkPtr network{nullptr, [](armnn::INetwork *){}};
+        {
+            ARMNN_SCOPED_HEAP_PROFILING("Parsing");
+            // Handle text and binary input differently by calling the corresponding parser function
+            network = (params.m_IsModelBinary ?
+                parser->CreateNetworkFromBinaryFile(modelPath.c_str(), inputShapes, requestedOutputs) :
+                parser->CreateNetworkFromTextFile(modelPath.c_str(), inputShapes, requestedOutputs));
+        }
 
         m_InputBindingInfo  = parser->GetNetworkInputBindingInfo(params.m_InputBinding);
         m_OutputBindingInfo = parser->GetNetworkOutputBindingInfo(params.m_OutputBinding);
 
-        armnn::IOptimizedNetworkPtr optNet =
-            armnn::Optimize(*network, m_Runtime->GetDeviceSpec());
+        armnn::IOptimizedNetworkPtr optNet{nullptr, [](armnn::IOptimizedNetwork *){}};
+        {
+            ARMNN_SCOPED_HEAP_PROFILING("Optimizing");
+            optNet = armnn::Optimize(*network, m_Runtime->GetDeviceSpec());
+        }
+
+        if (params.m_VisualizePostOptimizationModel)
+        {
+            boost::filesystem::path filename = params.m_ModelPath;
+            filename.replace_extension("dot");
+            std::fstream file(filename.c_str(),file.out);
+            optNet->SerializeToDot(file);
+        }
+
+        armnn::Status ret;
+        {
+            ARMNN_SCOPED_HEAP_PROFILING("LoadNetwork");
+            ret = m_Runtime->LoadNetwork(m_NetworkIdentifier, std::move(optNet));
+        }
 
-        // Load the network into the runtime.
-        armnn::Status ret = m_Runtime->LoadNetwork(m_NetworkIdentifier, std::move(optNet));
         if (ret == armnn::Status::Failure)
         {
             throw armnn::Exception("IRuntime::LoadNetwork failed");
diff --git a/tests/InferenceTest.cpp b/tests/InferenceTest.cpp
index 55616798e2..161481f2cd 100644
--- a/tests/InferenceTest.cpp
+++ b/tests/InferenceTest.cpp
@@ -154,7 +154,7 @@ bool InferenceTest(const InferenceTestOptions& params,
     }
 
     const unsigned int nbTotalToProcess = params.m_IterationCount > 0 ? params.m_IterationCount
-        : boost::numeric_cast<unsigned int>(defaultTestCaseIds.size());
+        : static_cast<unsigned int>(defaultTestCaseIds.size());
 
     for (; nbProcessed < nbTotalToProcess; nbProcessed++)
     {
diff --git a/tests/InferenceTest.inl b/tests/InferenceTest.inl
index 83a99459e3..a36e231e76 100644
--- a/tests/InferenceTest.inl
+++ b/tests/InferenceTest.inl
@@ -307,6 +307,7 @@ int ClassifierInferenceTestMain(int argc, char* argv[], const char* modelFilenam
                     modelParams.m_InputTensorShape = inputTensorShape;
                     modelParams.m_IsModelBinary = isModelBinary;
                     modelParams.m_ComputeDevice = modelOptions.m_ComputeDevice;
+                    modelParams.m_VisualizePostOptimizationModel = modelOptions.m_VisualizePostOptimizationModel;
 
                     return std::make_unique<InferenceModel>(modelParams);
             });
diff --git a/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp b/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
index 3c75ed7f24..37138f4a78 100644
--- a/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
+++ b/tests/MultipleNetworksCifar10/MultipleNetworksCifar10.cpp
@@ -190,7 +190,17 @@ int main(int argc, char* argv[])
     }
     catch (armnn::Exception const& e)
     {
-        BOOST_LOG_TRIVIAL(fatal) <<"Armnn Error: "<< e.what();
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "Armnn Error: " << e.what() << std::endl;
         return 1;
     }
-}
\ No newline at end of file
+    catch (const std::exception& e)
+    {
+        // Coverity fix: various boost exceptions can be thrown by methods called by this test. 
+        std::cerr << "WARNING: MultipleNetworksCifar10: An error has occurred when running the "
+                     "multiple networks inference tests: " << e.what() << std::endl;
+        return 1;
+    }
+}
diff --git a/tests/TfCifar10-Armnn/TfCifar10-Armnn.cpp b/tests/TfCifar10-Armnn/TfCifar10-Armnn.cpp
index 0d9e16a4ba..cfe95095a9 100644
--- a/tests/TfCifar10-Armnn/TfCifar10-Armnn.cpp
+++ b/tests/TfCifar10-Armnn/TfCifar10-Armnn.cpp
@@ -9,9 +9,24 @@
 int main(int argc, char* argv[])
 {
     armnn::TensorShape inputTensorShape({ 1, 32, 32, 3 });
-    return armnn::test::ClassifierInferenceTestMain<Cifar10Database, armnnTfParser::ITfParser>(
-        argc, argv, "cifar10_tf.prototxt", false,
-        "data", "prob", { 0, 1, 2, 4, 7 },
-        [](const char* dataDir) { return Cifar10Database(dataDir, true); },
-        &inputTensorShape);
+
+    int retVal = EXIT_FAILURE;
+    try
+    {
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<Cifar10Database, armnnTfParser::ITfParser>(
+                     argc, argv, "cifar10_tf.prototxt", false,
+                     "data", "prob", { 0, 1, 2, 4, 7 },
+                     [](const char* dataDir) { return Cifar10Database(dataDir, true); },
+                     &inputTensorShape);
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: TfCifar10-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/TfInceptionV3-Armnn/TfInceptionV3-Armnn.cpp b/tests/TfInceptionV3-Armnn/TfInceptionV3-Armnn.cpp
index 94878ae4ce..441b07c9c9 100644
--- a/tests/TfInceptionV3-Armnn/TfInceptionV3-Armnn.cpp
+++ b/tests/TfInceptionV3-Armnn/TfInceptionV3-Armnn.cpp
@@ -8,16 +8,33 @@
 
 int main(int argc, char* argv[])
 {
-    std::vector<ImageSet> imageSet =
+    int retVal = EXIT_FAILURE;
+    try
     {
-        { "Dog.jpg", 208 },
-        { "Cat.jpg", 283 },
-        { "shark.jpg", 3 },
-    };
-    armnn::TensorShape inputTensorShape({ 1, 299, 299, 3 });
-    return armnn::test::ClassifierInferenceTestMain<MobileNetDatabase, armnnTfParser::ITfParser>(
-        argc, argv, "inception_v3_2016_08_28_frozen_transformed.pb", true,
-        "input", "InceptionV3/Predictions/Reshape_1", { 0, 1, 2, },
-        [&imageSet](const char* dataDir) { return MobileNetDatabase(dataDir, 299, 299, imageSet); },
-        &inputTensorShape);
+        // Coverity fix: The following code may throw an exception of type std::length_error.
+        std::vector<ImageSet> imageSet =
+        {
+            { "Dog.jpg", 208 },
+            { "Cat.jpg", 283 },
+            { "shark.jpg", 3 },
+        };
+
+        armnn::TensorShape inputTensorShape({ 1, 299, 299, 3 });
+
+        // Coverity fix: InferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<MobileNetDatabase, armnnTfParser::ITfParser>(
+                    argc, argv, "inception_v3_2016_08_28_frozen_transformed.pb", true,
+                    "input", "InceptionV3/Predictions/Reshape_1", { 0, 1, 2, },
+                    [&imageSet](const char* dataDir) { return MobileNetDatabase(dataDir, 299, 299, imageSet); },
+                    &inputTensorShape);
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: TfInceptionV3-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/TfMnist-Armnn/TfMnist-Armnn.cpp b/tests/TfMnist-Armnn/TfMnist-Armnn.cpp
index 5625f4c055..bcc3f416cc 100644
--- a/tests/TfMnist-Armnn/TfMnist-Armnn.cpp
+++ b/tests/TfMnist-Armnn/TfMnist-Armnn.cpp
@@ -9,9 +9,24 @@
 int main(int argc, char* argv[])
 {
     armnn::TensorShape inputTensorShape({ 1, 784, 1, 1 });
-    return armnn::test::ClassifierInferenceTestMain<MnistDatabase, armnnTfParser::ITfParser>(
-        argc, argv, "simple_mnist_tf.prototxt", false,
-        "Placeholder", "Softmax", { 0, 1, 2, 3, 4 },
-        [](const char* dataDir) { return MnistDatabase(dataDir, true); },
-        &inputTensorShape);
+
+    int retVal = EXIT_FAILURE;
+    try
+    {
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<MnistDatabase, armnnTfParser::ITfParser>(
+                     argc, argv, "simple_mnist_tf.prototxt", false,
+                     "Placeholder", "Softmax", { 0, 1, 2, 3, 4 },
+                     [](const char* dataDir) { return MnistDatabase(dataDir, true); },
+                     &inputTensorShape);
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: TfMnist-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/TfMobileNet-Armnn/TfMobileNet-Armnn.cpp b/tests/TfMobileNet-Armnn/TfMobileNet-Armnn.cpp
index e1aebb6bb0..54759bf88a 100644
--- a/tests/TfMobileNet-Armnn/TfMobileNet-Armnn.cpp
+++ b/tests/TfMobileNet-Armnn/TfMobileNet-Armnn.cpp
@@ -8,43 +8,59 @@
 
 int main(int argc, char* argv[])
 {
-    std::vector<ImageSet> imageSet =
+    int retVal = EXIT_FAILURE;
+    try
     {
-        {"Dog.jpg", 209},
-        // top five predictions in tensorflow:
-        // -----------------------------------
-        // 209:Labrador retriever 0.949995
-        // 160:Rhodesian ridgeback 0.0270182
-        // 208:golden retriever 0.0192866
-        // 853:tennis ball 0.000470382
-        // 239:Greater Swiss Mountain dog 0.000464451
-        {"Cat.jpg", 283},
-        // top five predictions in tensorflow:
-        // -----------------------------------
-        // 283:tiger cat 0.579016
-        // 286:Egyptian cat 0.319676
-        // 282:tabby, tabby cat 0.0873346
-        // 288:lynx, catamount 0.011163
-        // 289:leopard, Panthera pardus 0.000856755
-        {"shark.jpg", 3},
-        // top five predictions in tensorflow:
-        // -----------------------------------
-        // 3:great white shark, white shark, ... 0.996926
-        // 4:tiger shark, Galeocerdo cuvieri 0.00270528
-        // 149:killer whale, killer, orca, ... 0.000121848
-        // 395:sturgeon 7.78977e-05
-        // 5:hammerhead, hammerhead shark 6.44127e-055
-    };
+        // Coverity fix: The following code may throw an exception of type std::length_error.
+        std::vector<ImageSet> imageSet =
+        {
+            {"Dog.jpg", 209},
+            // top five predictions in tensorflow:
+            // -----------------------------------
+            // 209:Labrador retriever 0.949995
+            // 160:Rhodesian ridgeback 0.0270182
+            // 208:golden retriever 0.0192866
+            // 853:tennis ball 0.000470382
+            // 239:Greater Swiss Mountain dog 0.000464451
+            {"Cat.jpg", 283},
+            // top five predictions in tensorflow:
+            // -----------------------------------
+            // 283:tiger cat 0.579016
+            // 286:Egyptian cat 0.319676
+            // 282:tabby, tabby cat 0.0873346
+            // 288:lynx, catamount 0.011163
+            // 289:leopard, Panthera pardus 0.000856755
+            {"shark.jpg", 3},
+            // top five predictions in tensorflow:
+            // -----------------------------------
+            // 3:great white shark, white shark, ... 0.996926
+            // 4:tiger shark, Galeocerdo cuvieri 0.00270528
+            // 149:killer whale, killer, orca, ... 0.000121848
+            // 395:sturgeon 7.78977e-05
+            // 5:hammerhead, hammerhead shark 6.44127e-055
+        };
 
-    armnn::TensorShape inputTensorShape({ 1, 224, 224, 3  });
-    return armnn::test::ClassifierInferenceTestMain<MobileNetDatabase, armnnTfParser::ITfParser>(
-        argc, argv, "mobilenet_v1_1.0_224_fp32.pb", true, "input", "output", { 0, 1, 2 },
-        [&imageSet](const char* dataDir) {
-            return MobileNetDatabase(
-                dataDir,
-                224,
-                224,
-                imageSet);
-        },
-        &inputTensorShape);
+        armnn::TensorShape inputTensorShape({ 1, 224, 224, 3  });
+
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<MobileNetDatabase, armnnTfParser::ITfParser>(
+                     argc, argv, "mobilenet_v1_1.0_224_fp32.pb", true, "input", "output", { 0, 1, 2 },
+                     [&imageSet](const char* dataDir) {
+                         return MobileNetDatabase(
+                             dataDir,
+                             224,
+                             224,
+                             imageSet);
+                     },
+                     &inputTensorShape);
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: TfMobileNet-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
 }
diff --git a/tests/TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp b/tests/TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp
new file mode 100644
index 0000000000..1e1ede3e68
--- /dev/null
+++ b/tests/TfResNext_Quantized-Armnn/TfResNext_Quantized-Armnn.cpp
@@ -0,0 +1,39 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// See LICENSE file in the project root for full license information.
+//
+#include "../InferenceTest.hpp"
+#include "../ImageNetDatabase.hpp"
+#include "armnnTfParser/ITfParser.hpp"
+
+int main(int argc, char* argv[])
+{
+    int retVal = EXIT_FAILURE;
+    try
+    {
+        // Coverity fix: The following code may throw an exception of type std::length_error.
+        std::vector<ImageSet> imageSet =
+        {
+            {"ILSVRC2012_val_00000018.JPEG",  21 },
+            {"shark.jpg", 2}
+        };
+
+        armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
+
+        // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+        retVal = armnn::test::ClassifierInferenceTestMain<ImageNetDatabase, armnnTfParser::ITfParser>(
+                     argc, argv, "resnext_TF_quantized_for_armnn_team.pb", true,
+                     "inputs", "pool1", { 0, 1 },
+                     [&imageSet](const char* dataDir) { return ImageNetDatabase(dataDir, 224, 224, imageSet); },
+                     &inputTensorShape);
+    }
+    catch (const std::exception& e)
+    {
+        // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
+        // exception of type std::length_error.
+        // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
+        std::cerr << "WARNING: TfResNext_Quantized-Armnn: An error has occurred when running "
+                     "the classifier inference tests: " << e.what() << std::endl;
+    }
+    return retVal;
+}