coverity Uninitialized scalar variable (#17182)

Signed-off-by: Hu Yuan2 <yuan2.hu@intel.com>

src/plugins/intel_cpu/src/nodes/conv.h

@@ -167,7 +167,7 @@ private:
     MemoryPtr legacyWeightsZeroPointsMemPtr;
     MemoryPtr legacyOutputCompensationMemPtr;
     MemoryPtr stockInputZeroPointsMemPtr;
-    dnnl::memory::data_type outputDataType;
+    dnnl::memory::data_type outputDataType = dnnl::memory::data_type::undef;
     InferenceEngine::Precision sumPrc = InferenceEngine::Precision::UNSPECIFIED;
 
     // TODO: migrate on convolution_auto algorithm for x64

src/plugins/intel_cpu/src/nodes/deconv.h

@@ -89,8 +89,8 @@ private:
     bool autoPad = false;
     bool externOutShape = false;
     size_t groupNum = 1;
-    size_t IC;
+    size_t IC = 0;
-    size_t OC;
+    size_t OC = 0;
     std::vector<ptrdiff_t> kernel;
     std::vector<ptrdiff_t> stride;
     std::vector<ptrdiff_t> dilation;
@@ -105,7 +105,7 @@ private:
 
     AttrPtr pAttr;
 
-    dnnl::memory::data_type outputDataType;
+    dnnl::memory::data_type outputDataType = dnnl::memory::data_type::undef;
 
     std::shared_ptr<dnnl::primitive_attr> attr;
     void setPostOps(dnnl::primitive_attr &attr, const VectorDims &dims);

src/plugins/intel_cpu/src/nodes/fullyconnected.h

@@ -78,12 +78,12 @@ private:
     static const size_t DATA_ID = 0;
     static const size_t WEIGHTS_ID = 1;
     static const size_t BIAS_ID = 2;
-    dnnl::memory::data_type outputDataType;
+    dnnl::memory::data_type outputDataType = dnnl::memory::data_type::undef;
 
     using executorPtr = std::shared_ptr<DnnlExecutor>;
     executorPtr execPtr = nullptr;
     bool useConv1x1 = false;
-    impl_desc_type implementationTypeIP;
+    impl_desc_type implementationTypeIP = impl_desc_type::unknown;
     MemoryDescPtr weightDescIP;
     dnnl::primitive_attr attr;
 

src/plugins/intel_cpu/src/nodes/interpolate.h

@@ -228,7 +228,7 @@ private:
     static size_t getSpatialDimsNum(const Dim rank);
 
     bool hasPad = false;
-    InterpolateShapeCalcMode shapeCalcMode;
+    InterpolateShapeCalcMode shapeCalcMode = InterpolateShapeCalcMode::sizes;
 
     bool isAxesSpecified = false;
     std::vector<int> axes;
@@ -251,4 +251,4 @@ private:
 
 }   // namespace node
 }   // namespace intel_cpu
-}   // namespace ov
+}   // namespace ov

src/plugins/intel_cpu/src/nodes/kernels/x64/rdft_kernel.hpp

@@ -35,7 +35,7 @@ struct jit_dft_args {
 struct jit_dft_kernel {
     jit_dft_kernel(bool is_inverse, enum dft_type type) : is_inverse_(is_inverse), kernel_type_(type) {}
 
-    void (*ker_)(const jit_dft_args*);
+    void (*ker_)(const jit_dft_args*) = nullptr;
 
     void operator()(const jit_dft_args* args) {
         assert(ker_);

src/plugins/intel_cpu/src/nodes/mha.h

@@ -142,12 +142,13 @@ protected:
 
 private:
     struct brgemmCtx {
-        size_t M, N, K, LDA, LDB, LDC;
+        size_t M = 0, N = 0, K = 0, LDA = 0, LDB = 0, LDC = 0;
-        dnnl_data_type_t dt_in0, dt_in1;
+        dnnl_data_type_t dt_in0 = dnnl_data_type_undef;
+        dnnl_data_type_t dt_in1 = dnnl_data_type_undef;
         char palette[64];
-        bool is_with_amx;
+        bool is_with_amx = false;
-        bool is_with_comp;
+        bool is_with_comp = false;
-        float beta;
+        float beta = 0.0f;
     };
 
     template <typename in1_type>
@@ -190,18 +191,18 @@ private:
     VectorDims dimsMatMul1In1;
     VectorDims dimsMatMul1Out;
 
-    size_t batch0, batch1;
+    size_t batch0 = 0, batch1 = 0;
-    size_t M, M_blk, M_tail;
+    size_t M = 0, M_blk = 0, M_tail = 0;
-    size_t K0, K0_blk, K0_tail, N0, N0_blk, N0_tail;
+    size_t K0 = 0, K0_blk = 0, K0_tail = 0, N0 = 0, N0_blk = 0, N0_tail = 0;
-    size_t K1, K1_blk, K1_tail, N1, N1_blk, N1_tail;
+    size_t K1 = 0, K1_blk = 0, K1_tail = 0, N1 = 0, N1_blk = 0, N1_tail = 0;
 
-    size_t bufferMatMul0In0Size;
+    size_t bufferMatMul0In0Size = 0;
-    size_t bufferMatMul0In1Size;
+    size_t bufferMatMul0In1Size = 0;
-    size_t bufferMatMul0OutSize;
+    size_t bufferMatMul0OutSize = 0;
-    size_t bufferMatMul1In1Size;
+    size_t bufferMatMul1In1Size = 0;
-    size_t bufferMatMul1OutSize;
+    size_t bufferMatMul1OutSize = 0;
-    size_t bufferCompensation0Size;
+    size_t bufferCompensation0Size = 0;
-    size_t bufferCompensation1Size;
+    size_t bufferCompensation1Size = 0;
     size_t wsp_size_per_thread = 4 * 1024;
 
     std::vector<uint8_t> bufferMatMul0In0;
@@ -222,13 +223,13 @@ private:
     std::vector<float> fqScales2;
     std::vector<float> fqScales3;
 
-    size_t brg0VnniFactor;
+    size_t brg0VnniFactor = 0;
     brgemmCtx brgCtxs0[MHA_BRGEMM_KERNELS_NUM];
     std::unique_ptr<dnnl::impl::cpu::x64::brgemm_kernel_t> brgKernels0[MHA_BRGEMM_KERNELS_NUM];
     std::unique_ptr<dnnl::impl::cpu::x64::matmul::jit_brgemm_matmul_copy_a_t> brgCopyAKernel0;
     std::unique_ptr<dnnl::impl::cpu::x64::matmul::jit_brgemm_matmul_copy_b_t> brgCopyBKernel0;
 
-    size_t brg1VnniFactor;
+    size_t brg1VnniFactor = 0;
     brgemmCtx brgCtxs1[MHA_BRGEMM_KERNELS_NUM];
     std::unique_ptr<dnnl::impl::cpu::x64::brgemm_kernel_t> brgKernels1[MHA_BRGEMM_KERNELS_NUM];
     std::unique_ptr<dnnl::impl::cpu::x64::matmul::jit_brgemm_matmul_copy_b_t> brgCopyBKernel1;

src/plugins/intel_cpu/src/nodes/subgraph.h

@@ -78,7 +78,7 @@ private:
 
     // Holds ISA version used is codeGeneration target
     dnnl::impl::cpu::x64::cpu_isa_t host_isa;
-    size_t isa_num_lanes; // number of elements that fit in vector size
+    size_t isa_num_lanes = 0; // number of elements that fit in vector size
 
     // Holds index of output used as in execution domain
     // it should be compatible with a schedule's work size

src/plugins/intel_cpu/src/nodes/topk.h

@@ -113,27 +113,27 @@ private:
     void preset_params();
     void prepare_original_idx();
 
-    bool topk_innermost;
+    bool topk_innermost = false;
-    bool jit_mode;
+    bool jit_mode = false;
-    bool sort_index;
+    bool sort_index = false;
-    bool stable;
+    bool stable = false;
-    bool mode_max;
+    bool mode_max = false;
-    int axis;
+    int axis = 0;
     static const size_t TOPK_DATA = 0;
     static const size_t TOPK_K = 1;
     static const size_t TOPK_INDEX = 1;
-    size_t O, A, I;
+    size_t O = 0, A = 0, I = 0;
-    size_t blk_size;
+    size_t blk_size = 0;
-    size_t data_size;
+    size_t data_size = 0;
-    size_t axis_dim;
+    size_t axis_dim = 0;
-    int top_k;
+    int top_k = 0;
-    int dim, before_num;
+    int dim = 0, before_num = 0;
-    bool bubble_inplace;
+    bool bubble_inplace = false;
-    bool preset_params_done;
+    bool preset_params_done = false;
 
     VectorDims src_dims, dst_dims;
-    TopKLayoutType layout;
+    TopKLayoutType layout = TopKLayoutType::topk_ncsp;
-    TopKAlgorithm algorithm;
+    TopKAlgorithm algorithm = TopKAlgorithm::topk_bubble_sort;
 
     std::vector<int> vec_bitonic_idx;
     std::vector<int> vec_bitonic_k_idx;