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Fixed compilation with ninja + clang (#5469)

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This commit is contained in:
Ilya Lavrenov
2021-04-30 08:57:03 +03:00
committed by GitHub
parent c350f61a42
commit c52117a09f
7 changed files with 9 additions and 12 deletions
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4
inference-engine/src/gna_plugin/frontend/scale_factor_calc.hpp
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@@ -858,8 +858,8 @@ class ScaleFactorPerLayer<InferenceEngine::ConcatLayer*> {
auto minScaleFactor = quantParamsFirst->_dst_quant.GetScale();
for (auto it = inputLayers.begin(); it != inputLayers.end(); ++it) {
auto quantParams = InferenceEngine::getInjectedData<QuantizedLayerParams>(*it);
if (quantParams->_dst_quant.GetScale() < minScaleFactor &&
!fp32eq(quantParams->_dst_quant.GetScale(), 1.0f) ||
if ((quantParams->_dst_quant.GetScale() < minScaleFactor &&
!fp32eq(quantParams->_dst_quant.GetScale(), 1.0f)) ||
fp32eq(minScaleFactor, 1.0f)) {
minScaleFactor = quantParams->_dst_quant.GetScale();
sourceLayerIt = it;

1
inference-engine/src/gna_plugin/gna_graph_compiler.cpp
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@@ -43,6 +43,7 @@ using namespace GNAPluginNS;
#define CREATE(name) [](GNAGraphCompiler *p, CNNLayerPtr l) {p->name(l);}
const GNALimitations::Cnn2D::Validator GNAGraphCompiler::cnn2dValidator;
void GNAGraphCompiler::setGNAMemoryPtr(std::shared_ptr<GNAPluginNS::gna_memory_type> gnaMemPtr) {
this->gnamem = std::move(gnaMemPtr);

2
inference-engine/src/gna_plugin/gna_graph_compiler.hpp
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@@ -52,7 +52,7 @@ private:
static void assertConvolutionLayoutProper(const InferenceEngine::DataPtr&);
std::vector<uint8_t> static transposeMatrix(uint8_t* ptr_matrix, size_t element_size, uint32_t num_rows, uint32_t num_cols);
const GNALimitations::Cnn2D::Validator cnn2dValidator;
static const GNALimitations::Cnn2D::Validator cnn2dValidator;
public:
GNAPluginNS::backend::DnnComponents dnnComponents;

1
inference-engine/src/gna_plugin/gna_plugin.cpp
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@@ -1519,6 +1519,7 @@ InferenceEngine::IExecutableNetworkInternal::Ptr GNAPlugin::ImportNetwork(std::i
return gnaOperation.Type == Gna2OperationTypeConvolution ?
kDnnNonInterleavedOrientation : kDnnInterleavedOrientation;
};
(void)getOrientation;
#else
auto getOrientation = [](intel_nnet_layer_t & layer) {
return layer.nLayerKind == INTEL_CONVOLUTIONAL ?

2
inference-engine/tests/functional/plugin/gna/pass_tests/fq_activation.cpp
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@@ -59,7 +59,7 @@ public:
return result.str();
}
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo& info) const {
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo& info) const override {
return FuncTestUtils::createAndFillBlob(info.getTensorDesc(), inputDataMax - inputDataMin, inputDataMin, 1 / inputDataResolution);
}

9
inference-engine/tests/functional/plugin/gna/pass_tests/remove_permutations_NHWC_to_NCHW_pass.cpp
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@@ -158,10 +158,9 @@ class RemovePermutationsWithPoolAndActTest : public testing::WithParamInterface<
}
protected:
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo& info) const {
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo& info) const override {
InferenceEngine::Blob::Ptr blob = make_blob_with_precision(info.getTensorDesc());
blob->allocate();
auto precision = info.getPrecision();
auto* rawBlobDataPtr = blob->buffer().as<float*>();
std::vector<float> values = CommonTestUtils::generate_float_numbers(blob->size(), -0.2f, 0.2f);
@@ -250,10 +249,9 @@ class RemovePermutationsWithTwoConvTest : public testing::WithParamInterface<rem
}
protected:
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo& info) const {
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo& info) const override {
InferenceEngine::Blob::Ptr blob = make_blob_with_precision(info.getTensorDesc());
blob->allocate();
auto precision = info.getPrecision();
auto* rawBlobDataPtr = blob->buffer().as<float*>();
std::vector<float> values = CommonTestUtils::generate_float_numbers(blob->size(), 0.0f, 0.5f);
@@ -338,10 +336,9 @@ class RemovePermutationsWithEltwiseTest : public testing::WithParamInterface<rem
}
protected:
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo& info) const {
InferenceEngine::Blob::Ptr GenerateInput(const InferenceEngine::InputInfo& info) const override {
InferenceEngine::Blob::Ptr blob = make_blob_with_precision(info.getTensorDesc());
blob->allocate();
auto precision = info.getPrecision();
auto* rawBlobDataPtr = blob->buffer().as<float*>();
std::vector<float> values = CommonTestUtils::generate_float_numbers(blob->size(), -0.2f, 0.2f);

2
inference-engine/thirdparty/movidius/mvnc/CMakeLists.txt vendored
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@@ -35,8 +35,6 @@ endif()
if(NOT WIN32)
target_compile_options(${TARGET_NAME}
PRIVATE
-MMD
-MP
-Wformat
-Wformat-security
-Wall)