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[GNA] Security fixes for 2021.2 (#3167)

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Elizaveta Lobanova 2020-11-17 19:26:17 +03:00 committed by GitHub
parent 6a1eb5a139
commit ed6113854a
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 8 additions and 3 deletions
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8
inference-engine/src/gna_plugin/optimizer/gna_pass_manager.cpp
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@ -391,7 +391,7 @@ void SubstituteSoftSignPass::run() {
// pattern matched - lets substitute // pattern matched - lets substitute
gnalog() << "SoftSign subgraph found consits of: \n" gnalog() << "SoftSign subgraph found consits of: \n"
<< "\t" << abs->name << "\n"; << "\t" << abs->name << "\n";
if (addition == nullptr) gnalog() << "\t" << addition->name << "\n"; if (addition != nullptr) gnalog() << "\t" << addition->name << "\n";
gnalog() << "\t" << mul->name << "\n" gnalog() << "\t" << mul->name << "\n"
<< std::endl; << std::endl;
@ -402,6 +402,7 @@ void SubstituteSoftSignPass::run() {
CNNLayerPtr activationLayer = CNNLayerPtr activationLayer =
std::make_shared<GenericLayer>(LayerParams({layerName, "SoftSign", Precision::FP32})); std::make_shared<GenericLayer>(LayerParams({layerName, "SoftSign", Precision::FP32}));
IE_ASSERT(activationLayer != nullptr);
auto activationLayerWithQuant = quantized ? auto activationLayerWithQuant = quantized ?
InferenceEngine::injectData<QuantizedLayerParams>(activationLayer) : InferenceEngine::injectData<QuantizedLayerParams>(activationLayer) :
activationLayer; activationLayer;
@ -483,6 +484,7 @@ void SubstitutePReluPass::run() {
// sum // sum
auto sum = getNext(negate); auto sum = getNext(negate);
IE_ASSERT(sum != nullptr);
if (!LayerInfo(sum).isEltwiseSum()) continue; if (!LayerInfo(sum).isEltwiseSum()) continue;
if (sum->insData.size() != 2 if (sum->insData.size() != 2
|| sum->insData[0].lock() == nullptr || sum->insData[0].lock() == nullptr
@ -922,6 +924,7 @@ void InsertConcatAligningFilterPass::run() {
if (!info.isConcat()) continue; if (!info.isConcat()) continue;
size_t offset = 0; size_t offset = 0;
auto concatLayer = info.as<ConcatLayer*>(); auto concatLayer = info.as<ConcatLayer*>();
IE_ASSERT(concatLayer != nullptr);
for (auto input_idx = 0; input_idx != concatLayer->insData.size(); input_idx++) { for (auto input_idx = 0; input_idx != concatLayer->insData.size(); input_idx++) {
auto getLayerByIndex = [&concatLayer](int idx) { auto getLayerByIndex = [&concatLayer](int idx) {
@ -1237,6 +1240,8 @@ void EltwiseSplitOverChannelsPass::run() {
continue; continue;
} }
auto masterEltwise = std::dynamic_pointer_cast<EltwiseLayer>(l); auto masterEltwise = std::dynamic_pointer_cast<EltwiseLayer>(l);
IE_ASSERT(masterEltwise != nullptr);
if (l->outData.size() != 1) { if (l->outData.size() != 1) {
THROW_GNA_LAYER_EXCEPTION(l) << "number of outputs expected to be 1"; THROW_GNA_LAYER_EXCEPTION(l) << "number of outputs expected to be 1";
} }
@ -1339,6 +1344,7 @@ void SubstituteScaleShiftBroadCastPass::run() {
} }
auto scaleShift = layerInfo.as<ScaleShiftLayer*>(); auto scaleShift = layerInfo.as<ScaleShiftLayer*>();
IE_ASSERT(scaleShift != nullptr);
auto insData = scaleShift->insData.front().lock(); auto insData = scaleShift->insData.front().lock();
if (!insData) { if (!insData) {

3
inference-engine/tests_deprecated/unit/engines/gna/matchers/pwl_matcher.hpp
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@ -74,8 +74,7 @@ class PWLMatcher : public ::testing::MatcherInterface<const gna_nnet_type_t*> {
}; };
DnnActivationType detectPwlType(gna_nnet_layer_t *layer) const { DnnActivationType detectPwlType(gna_nnet_layer_t *layer) const {
intel_dnn_component_t comp{};
intel_dnn_component_t comp;
comp.ptr_outputs = layer->pOutputs; comp.ptr_outputs = layer->pOutputs;
comp.num_columns_in = layer->nInputColumns; comp.num_columns_in = layer->nInputColumns;
comp.num_rows_in = layer->nInputRows; comp.num_rows_in = layer->nInputRows;