diff --git a/src/plugins/intel_cpu/src/nodes/conv.h b/src/plugins/intel_cpu/src/nodes/conv.h index 1e9d23467a2..6ec17425030 100644 --- a/src/plugins/intel_cpu/src/nodes/conv.h +++ b/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 diff --git a/src/plugins/intel_cpu/src/nodes/deconv.h b/src/plugins/intel_cpu/src/nodes/deconv.h index 7f4b3db5128..ea3024dfb12 100644 --- a/src/plugins/intel_cpu/src/nodes/deconv.h +++ b/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 OC; + size_t IC = 0; + size_t OC = 0; std::vector kernel; std::vector stride; std::vector 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 attr; void setPostOps(dnnl::primitive_attr &attr, const VectorDims &dims); diff --git a/src/plugins/intel_cpu/src/nodes/fullyconnected.h b/src/plugins/intel_cpu/src/nodes/fullyconnected.h index cc03ac281f5..e661154c640 100644 --- a/src/plugins/intel_cpu/src/nodes/fullyconnected.h +++ b/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; executorPtr execPtr = nullptr; bool useConv1x1 = false; - impl_desc_type implementationTypeIP; + impl_desc_type implementationTypeIP = impl_desc_type::unknown; MemoryDescPtr weightDescIP; dnnl::primitive_attr attr; diff --git a/src/plugins/intel_cpu/src/nodes/interpolate.h b/src/plugins/intel_cpu/src/nodes/interpolate.h index 7fa12c5e1ad..7582c7019dd 100644 --- a/src/plugins/intel_cpu/src/nodes/interpolate.h +++ b/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 axes; @@ -251,4 +251,4 @@ private: } // namespace node } // namespace intel_cpu -} // namespace ov \ No newline at end of file +} // namespace ov diff --git a/src/plugins/intel_cpu/src/nodes/kernels/x64/rdft_kernel.hpp b/src/plugins/intel_cpu/src/nodes/kernels/x64/rdft_kernel.hpp index 36f416d9003..38b0ea4952c 100644 --- a/src/plugins/intel_cpu/src/nodes/kernels/x64/rdft_kernel.hpp +++ b/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_); diff --git a/src/plugins/intel_cpu/src/nodes/mha.h b/src/plugins/intel_cpu/src/nodes/mha.h index 6faadff4d71..0b986112c41 100644 --- a/src/plugins/intel_cpu/src/nodes/mha.h +++ b/src/plugins/intel_cpu/src/nodes/mha.h @@ -142,12 +142,13 @@ protected: private: struct brgemmCtx { - size_t M, N, K, LDA, LDB, LDC; - dnnl_data_type_t dt_in0, dt_in1; + size_t M = 0, N = 0, K = 0, LDA = 0, LDB = 0, LDC = 0; + 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_comp; - float beta; + bool is_with_amx = false; + bool is_with_comp = false; + float beta = 0.0f; }; template @@ -190,18 +191,18 @@ private: VectorDims dimsMatMul1In1; VectorDims dimsMatMul1Out; - size_t batch0, batch1; - size_t M, M_blk, M_tail; - size_t K0, K0_blk, K0_tail, N0, N0_blk, N0_tail; - size_t K1, K1_blk, K1_tail, N1, N1_blk, N1_tail; + size_t batch0 = 0, batch1 = 0; + size_t M = 0, M_blk = 0, M_tail = 0; + size_t K0 = 0, K0_blk = 0, K0_tail = 0, N0 = 0, N0_blk = 0, N0_tail = 0; + size_t K1 = 0, K1_blk = 0, K1_tail = 0, N1 = 0, N1_blk = 0, N1_tail = 0; - size_t bufferMatMul0In0Size; - size_t bufferMatMul0In1Size; - size_t bufferMatMul0OutSize; - size_t bufferMatMul1In1Size; - size_t bufferMatMul1OutSize; - size_t bufferCompensation0Size; - size_t bufferCompensation1Size; + size_t bufferMatMul0In0Size = 0; + size_t bufferMatMul0In1Size = 0; + size_t bufferMatMul0OutSize = 0; + size_t bufferMatMul1In1Size = 0; + size_t bufferMatMul1OutSize = 0; + size_t bufferCompensation0Size = 0; + size_t bufferCompensation1Size = 0; size_t wsp_size_per_thread = 4 * 1024; std::vector bufferMatMul0In0; @@ -222,13 +223,13 @@ private: std::vector fqScales2; std::vector fqScales3; - size_t brg0VnniFactor; + size_t brg0VnniFactor = 0; brgemmCtx brgCtxs0[MHA_BRGEMM_KERNELS_NUM]; std::unique_ptr brgKernels0[MHA_BRGEMM_KERNELS_NUM]; std::unique_ptr brgCopyAKernel0; std::unique_ptr brgCopyBKernel0; - size_t brg1VnniFactor; + size_t brg1VnniFactor = 0; brgemmCtx brgCtxs1[MHA_BRGEMM_KERNELS_NUM]; std::unique_ptr brgKernels1[MHA_BRGEMM_KERNELS_NUM]; std::unique_ptr brgCopyBKernel1; diff --git a/src/plugins/intel_cpu/src/nodes/subgraph.h b/src/plugins/intel_cpu/src/nodes/subgraph.h index 4b1abef7b2a..f1afc1ea438 100644 --- a/src/plugins/intel_cpu/src/nodes/subgraph.h +++ b/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 diff --git a/src/plugins/intel_cpu/src/nodes/topk.h b/src/plugins/intel_cpu/src/nodes/topk.h index cb2d202012a..f737857073c 100644 --- a/src/plugins/intel_cpu/src/nodes/topk.h +++ b/src/plugins/intel_cpu/src/nodes/topk.h @@ -113,27 +113,27 @@ private: void preset_params(); void prepare_original_idx(); - bool topk_innermost; - bool jit_mode; - bool sort_index; - bool stable; - bool mode_max; - int axis; + bool topk_innermost = false; + bool jit_mode = false; + bool sort_index = false; + bool stable = false; + bool mode_max = false; + 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 blk_size; - size_t data_size; - size_t axis_dim; - int top_k; - int dim, before_num; - bool bubble_inplace; - bool preset_params_done; + size_t O = 0, A = 0, I = 0; + size_t blk_size = 0; + size_t data_size = 0; + size_t axis_dim = 0; + int top_k = 0; + int dim = 0, before_num = 0; + bool bubble_inplace = false; + bool preset_params_done = false; VectorDims src_dims, dst_dims; - TopKLayoutType layout; - TopKAlgorithm algorithm; + TopKLayoutType layout = TopKLayoutType::topk_ncsp; + TopKAlgorithm algorithm = TopKAlgorithm::topk_bubble_sort; std::vector vec_bitonic_idx; std::vector vec_bitonic_k_idx;