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[CPU] Statically analyzed issues. (#4636)

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This commit is contained in:
Nikolay Shchegolev 2021-03-09 12:52:25 +03:00 committed by GitHub
parent 3e22f33224
commit 85e493ecb9
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GPG Key ID: 4AEE18F83AFDEB23
12 changed files with 67 additions and 33 deletions
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2
inference-engine/src/mkldnn_plugin/nodes/common/tensor_desc_creator.cpp
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@ -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);
}

4
inference-engine/src/mkldnn_plugin/nodes/cum_sum.cpp
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@ -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;

16
inference-engine/src/mkldnn_plugin/nodes/mkldnn_bin_conv_node.cpp
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@ -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 {

10
inference-engine/src/mkldnn_plugin/nodes/mkldnn_def_conv_node.cpp
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@ -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());

4
inference-engine/src/mkldnn_plugin/nodes/mkldnn_mvn_node.cpp
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@ -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);
});
}

5
inference-engine/src/mkldnn_plugin/nodes/mkldnn_pad_node.cpp
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@ -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),

10
inference-engine/src/mkldnn_plugin/nodes/mkldnn_pad_node.h
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@ -49,11 +49,11 @@ private:
InferenceEngine::SizeVector srcStrides;
InferenceEngine::SizeVector dstStrides;
InferenceEngine::SizeVector srcDimsForReflectOrSymmetric;
size_t nDimsForWork;
size_t workAmount;
size_t lastDstDim;
size_t shift;
uint8_t sizeData;
size_t nDimsForWork = 0lu;
size_t workAmount = 0lu;
size_t lastDstDim = 1lu;
size_t shift = 0lu;
uint8_t sizeData = 1;
} params;
template<typename T>

16
inference-engine/src/mkldnn_plugin/nodes/mkldnn_quantize_node.cpp
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@ -279,8 +279,8 @@ private:
Reg64 reg_output_scale = rbx;
Reg64 reg_output_shift = rdx;
bool do_rounding;
bool do_dequantization;
bool do_rounding = true;
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

14
inference-engine/src/mkldnn_plugin/nodes/mkldnn_roi_pooling_node.cpp
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@ -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.yoff = (size_t) ((bottom_y_index - top_y_index) * jpp.iw * jpp.c_block * sizeof(float));
arg.xoff = sizeof(float) * (right_x_index - left_x_index) * jpp.c_block;
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]];

5
inference-engine/src/mkldnn_plugin/nodes/mkldnn_split_node.cpp
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@ -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

10
inference-engine/src/mkldnn_plugin/nodes/non_max_suppression.cpp
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@ -433,11 +433,11 @@ private:
size_t num_boxes;
size_t num_classes;
size_t max_output_boxes_per_class;
float iou_threshold;
float score_threshold;
float soft_nms_sigma;
float scale;
size_t max_output_boxes_per_class = 0lu;
float iou_threshold = 0.0f;
float score_threshold = 0.0f;
float soft_nms_sigma = 0.0f;
float scale = 1.f;
std::vector<std::vector<size_t>> numFiltBox;
const std::string inType = "input", outType = "output";

4
inference-engine/src/mkldnn_plugin/nodes/region_yolo.cpp
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@ -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 dst_data_size;
unsigned src_data_size = 0;
unsigned dst_data_size = 0;
};
struct jit_uni_logistic_kernel {