[CPU] Statically analyzed issues. (#4636)

inference-engine/src/mkldnn_plugin/nodes/common/tensor_desc_creator.cpp

@@ -91,7 +91,7 @@ TensorDescCreator::makeFilteredRange(const CreatorsMap &map, unsigned int rank)
 
 std::pair<CreatorsMapFilterConstIterator, CreatorsMapFilterConstIterator>
 TensorDescCreator::makeFilteredRange(const CreatorsMap& map, unsigned rank, const std::vector<TensorDescCreatorTypes>& supportedTypes) {
-    size_t bitMask = 0ul;
+    unsigned bitMask = 0ul;
     for (auto& item : supportedTypes) {
         bitMask |= 1 << static_cast<unsigned>(item);
     }

inference-engine/src/mkldnn_plugin/nodes/cum_sum.cpp

@@ -205,7 +205,7 @@ private:
     void parallelItInit(size_t start, std::vector<size_t>& counters, const std::vector<size_t>& iterationRange) {
         auto itCounter = counters.rbegin();
         auto itWork = iterationRange.rbegin();
-        while (itCounter != counters.rend()) {
+        while (itCounter != counters.rend() && itWork != iterationRange.rend()) {
             *itCounter = start % *itWork;
             start /= *itWork;
             ++itCounter;
@@ -217,7 +217,7 @@ private:
         auto itCounter = counters.rbegin();
         auto itWork = iterationRange.rbegin();
 
-        while (itCounter != counters.rend()) {
+        while (itCounter != counters.rend() && itWork != iterationRange.rend()) {
             *itCounter = (*itCounter + 1) % *itWork;
             if (*itCounter != 0) {
                 break;

inference-engine/src/mkldnn_plugin/nodes/mkldnn_bin_conv_node.cpp

@@ -991,13 +991,17 @@ void MKLDNNBinaryConvolutionNode::initSupportedPrimitiveDescriptors() {
 }
 
 void MKLDNNBinaryConvolutionNode::createPrimitive() {
-    auto config = getSelectedPrimitiveDescriptor()->getConfig();
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU binary convolution with name '" << getName() << "' doesn't have primitive descriptors.";
+
+    auto config = selectedPrimitiveDescriptor->getConfig();
 
     auto srcDims = config.inConfs[0].desc.getDims();
     auto weiDims = config.inConfs[1].desc.getDims();
     auto dstDims = config.outConfs[0].desc.getDims();
 
-    auto implType = getSelectedPrimitiveDescriptor()->getImplementationType();
+    auto implType = selectedPrimitiveDescriptor->getImplementationType();
 
     jcp.ngroups = group;
     jcp.mb = srcDims[0];
@@ -1295,7 +1299,11 @@ void MKLDNNBinaryConvolutionNode::execute(mkldnn::stream strm) {
     auto weights = reinterpret_cast<const uint8_t*>(weightsMemory->GetPtr());
     auto dst = reinterpret_cast<uint8_t*>(dstMemory->GetPtr());
 
-    auto config = getSelectedPrimitiveDescriptor()->getConfig();
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU binary convolution with name '" << getName() << "' doesn't have primitive descriptors.";
+
+    auto config = selectedPrimitiveDescriptor->getConfig();
 
     auto srcBlockDesc = config.inConfs[0].desc.getBlockingDesc();
     std::vector<size_t> srcStride(srcBlockDesc.getStrides().size());
@@ -1315,7 +1323,7 @@ void MKLDNNBinaryConvolutionNode::execute(mkldnn::stream strm) {
         dstStride[dstBlockDesc.getOrder()[i]] = dstBlockDesc.getStrides()[i];
     }
 
-    auto implType = getSelectedPrimitiveDescriptor()->getImplementationType();
+    auto implType = selectedPrimitiveDescriptor->getImplementationType();
     if (implType != impl_desc_type::ref) {
         executeOptimized(src, weights, dst, srcStride, weightsStride, dstStride);
     } else {

inference-engine/src/mkldnn_plugin/nodes/mkldnn_def_conv_node.cpp

@@ -854,7 +854,10 @@ void MKLDNNDeformableConvolutionNode::initSupportedPrimitiveDescriptors() {
 }
 
 void MKLDNNDeformableConvolutionNode::createPrimitive() {
-    auto config = getSelectedPrimitiveDescriptor()->getConfig();
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU deformable convolution with name '" << getName() << "' doesn't have primitive descriptors.";
+    auto config = selectedPrimitiveDescriptor->getConfig();
 
     auto srcDims = config.inConfs[0].desc.getDims();
     auto weiDims = config.inConfs[2].desc.getDims();
@@ -1057,7 +1060,10 @@ void MKLDNNDeformableConvolutionNode::execute(mkldnn::stream strm) {
     const auto *weights = reinterpret_cast<const float *>(srcMemory2.GetPtr());
     float *dst = reinterpret_cast<float *>(dstMemory.GetPtr());
 
-    auto config = getSelectedPrimitiveDescriptor()->getConfig();
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU deformable convolution with name '" << getName() << "' doesn't have primitive descriptors.";
+    auto config = selectedPrimitiveDescriptor->getConfig();
 
     auto src_block_desc = config.inConfs[0].desc.getBlockingDesc();
     std::vector<size_t> src_strides(src_block_desc.getStrides().size());

inference-engine/src/mkldnn_plugin/nodes/mkldnn_mvn_node.cpp

@@ -942,7 +942,7 @@ void MKLDNNMVNNode::mvn_pln(const uint8_t* src_data, uint8_t* dst_data, const Si
                     arg.src_stride = src_stride_size;
                     arg.dst_stride = dst_stride_size;
                     arg.work_amount = static_cast<size_t>(C2 / blk_size);  // work amount for vector part
-                    arg.oc_off = static_cast<size_t>(c * sizeof(float));
+                    arg.oc_off = sizeof(float) * c;
                     (*mvn_kernel)(&arg);
                 });
             } else {
@@ -956,7 +956,7 @@ void MKLDNNMVNNode::mvn_pln(const uint8_t* src_data, uint8_t* dst_data, const Si
                     arg.src_stride = src_stride_size;
                     arg.dst_stride = dst_stride_size;
                     arg.work_amount = static_cast<size_t>(C2 / blk_size);
-                    arg.oc_off = static_cast<size_t>(c * sizeof(float));
+                    arg.oc_off = sizeof(float) * c;
                     (*mvn_kernel)(&arg);
                 });
             }

inference-engine/src/mkldnn_plugin/nodes/mkldnn_pad_node.cpp

@@ -252,7 +252,10 @@ void MKLDNNPadNode::padConstant() {
         return;
     }
 
-    InferenceEngine::Precision precision = this->getSelectedPrimitiveDescriptor()->getConfig().inConfs[0].desc.getPrecision();
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU Pad node with name '" << getName() << "' doesn't have primitive descriptors.";
+    InferenceEngine::Precision precision = selectedPrimitiveDescriptor->getConfig().inConfs[0].desc.getPrecision();
     OV_SWITCH(MKLDNNPlugin, PadConstantEmitter, this, precision,
               OV_CASE(InferenceEngine::Precision::FP32, float),
               OV_CASE(InferenceEngine::Precision::I32, int32_t),

inference-engine/src/mkldnn_plugin/nodes/mkldnn_pad_node.h

@@ -49,11 +49,11 @@ private:
         InferenceEngine::SizeVector srcStrides;
         InferenceEngine::SizeVector dstStrides;
         InferenceEngine::SizeVector srcDimsForReflectOrSymmetric;
-        size_t nDimsForWork;
+        size_t nDimsForWork = 0lu;
-        size_t workAmount;
+        size_t workAmount = 0lu;
-        size_t lastDstDim;
+        size_t lastDstDim = 1lu;
-        size_t shift;
+        size_t shift = 0lu;
-        uint8_t sizeData;
+        uint8_t sizeData = 1;
     } params;
 
     template<typename T>

inference-engine/src/mkldnn_plugin/nodes/mkldnn_quantize_node.cpp

@@ -279,8 +279,8 @@ private:
     Reg64 reg_output_scale = rbx;
     Reg64 reg_output_shift = rdx;
 
-    bool do_rounding;
+    bool do_rounding = true;
-    bool do_dequantization;
+    bool do_dequantization = true;
 
     inline void compute_planar() {
         int src_type_size = jqp_.src_prc.size();
@@ -1209,7 +1209,11 @@ void MKLDNNQuantizeNode::createPrimitive() {
 
     jqp.op_type = quantizeOpType;
 
-    if (getSelectedPrimitiveDescriptor()->getImplementationType() != impl_desc_type::ref) {
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU quantize node with name '" << getName() << "' doesn't have primitive descriptors.";
+
+    if (selectedPrimitiveDescriptor->getImplementationType() != impl_desc_type::ref) {
         if (mayiuse(cpu::x64::avx512_common)) {
             if (isBinarization())
                 quantize_kernel.reset(new jit_uni_binarization_kernel<cpu::x64::avx512_common>(jqp));
@@ -1523,7 +1527,11 @@ void MKLDNNQuantizeNode::executeQuantization() {
 }
 
 void MKLDNNQuantizeNode::execute(mkldnn::stream strm) {
-    if (getSelectedPrimitiveDescriptor()->getImplementationType() != impl_desc_type::ref) {
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU quantize node with name '" << getName() << "' doesn't have primitive descriptors.";
+
+    if (selectedPrimitiveDescriptor->getImplementationType() != impl_desc_type::ref) {
         if (jqp.op_type == QuantizeOpType::Binarization)
             executeBinarization();
         else

inference-engine/src/mkldnn_plugin/nodes/mkldnn_roi_pooling_node.cpp

@@ -332,7 +332,10 @@ void MKLDNNROIPoolingNode::initSupportedPrimitiveDescriptors() {
 }
 
 void MKLDNNROIPoolingNode::createPrimitive() {
-    auto config = getSelectedPrimitiveDescriptor()->getConfig();
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU ROI Pooling node with name '" << getName() << "' doesn't have primitive descriptors.";
+    auto config = selectedPrimitiveDescriptor->getConfig();
 
     const int simd_w = mayiuse(cpu::x64::avx512_common) ? 16 : 8;
     jpp.c_block = simd_w;
@@ -378,7 +381,10 @@ void MKLDNNROIPoolingNode::execute(mkldnn::stream strm) {
     const auto *src_roi = reinterpret_cast<const float *>(srcMemory1.GetPtr());
     float *dst = reinterpret_cast<float *>(dstMemory.GetPtr());
 
-    auto config = getSelectedPrimitiveDescriptor()->getConfig();
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU ROI Pooling node with name '" << getName() << "' doesn't have primitive descriptors.";
+    auto config = selectedPrimitiveDescriptor->getConfig();
 
     auto src_strides = config.inConfs[0].desc.getBlockingDesc().getStrides();
     auto dst_strides = config.outConfs[0].desc.getBlockingDesc().getStrides();
@@ -526,8 +532,8 @@ void MKLDNNROIPoolingNode::execute(mkldnn::stream strm) {
                         arg.xf = in_x - left_x_index;
                         arg.yf = in_y - top_y_index;
 
-                        arg.xoff = (size_t) ((right_x_index - left_x_index) * jpp.c_block * sizeof(float));
+                        arg.xoff = sizeof(float) * (right_x_index - left_x_index) * jpp.c_block;
-                        arg.yoff = (size_t) ((bottom_y_index - top_y_index) * jpp.iw * jpp.c_block * sizeof(float));
+                        arg.yoff = sizeof(float) * (bottom_y_index - top_y_index) * jpp.iw * jpp.c_block;
 
                         arg.src = &src_data[roi_batch_ind * src_strides[0] + cb * src_strides[1] +
                                             top_y_index * src_strides[2] + left_x_index * src_strides[3]];

inference-engine/src/mkldnn_plugin/nodes/mkldnn_split_node.cpp

@@ -458,7 +458,10 @@ void MKLDNNSplitNode::setDynamicBatchLim(int lim) {
 }
 
 void MKLDNNSplitNode::prepareOptimizedParams() {
-    const auto& inpTensorDesc = this->getSelectedPrimitiveDescriptor()->getConfig().inConfs[0].desc;
+    auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
+    if (!selectedPrimitiveDescriptor)
+        THROW_IE_EXCEPTION << "CPU Split node with name '" << getName() << "' doesn't have primitive descriptors.";
+    const auto& inpTensorDesc = selectedPrimitiveDescriptor->getConfig().inConfs[0].desc;
     const auto outputPortsCount = outDims.size();
 
     //find axis order position

inference-engine/src/mkldnn_plugin/nodes/non_max_suppression.cpp

@@ -433,11 +433,11 @@ private:
     size_t num_boxes;
     size_t num_classes;
 
-    size_t max_output_boxes_per_class;
+    size_t max_output_boxes_per_class = 0lu;
-    float iou_threshold;
+    float iou_threshold = 0.0f;
-    float score_threshold;
+    float score_threshold = 0.0f;
-    float soft_nms_sigma;
+    float soft_nms_sigma = 0.0f;
-    float scale;
+    float scale = 1.f;
 
     std::vector<std::vector<size_t>> numFiltBox;
     const std::string inType = "input", outType = "output";

inference-engine/src/mkldnn_plugin/nodes/region_yolo.cpp

@@ -40,8 +40,8 @@ struct jit_args_logistic {
 struct jit_logistic_config_params {
     InferenceEngine::Precision src_dt;
     InferenceEngine::Precision dst_dt;
-    unsigned src_data_size;
+    unsigned src_data_size = 0;
-    unsigned dst_data_size;
+    unsigned dst_data_size = 0;
 };
 
 struct jit_uni_logistic_kernel {