Address review comments

src/plugins/intel_cpu/src/nodes/bin_conv.cpp

@@ -1084,7 +1084,7 @@ void BinaryConvolution::initSupportedPrimitiveDescriptors() {
 void BinaryConvolution::createPrimitive() {
     auto selectedPrimitiveDescriptor = getSelectedPrimitiveDescriptor();
     if (!selectedPrimitiveDescriptor) {
-        THROW_CPU_NODE_ERR("CPU binary convolution with name '", getName(), "' doesn't have primitive descriptors.");
+        THROW_CPU_NODE_ERR("doesn't have primitive descriptors.");
     }
 
     auto srcDims = getParentEdgeAt(0)->getMemory().getStaticDims();

src/plugins/intel_cpu/src/nodes/conv.cpp

@@ -420,7 +420,7 @@ void Convolution::getSupportedDescriptors() {
         return;
     }
     if (!attrs.empty()) {
-        THROW_CPU_NODE_ERR("has not empty attrs vector");
+        THROW_CPU_NODE_ERR("has a non-empty attrs vector");
     }
 
     attrs.reserve(2);
@@ -1363,7 +1363,7 @@ void Convolution::prepareParams() {
 
     const NodeDesc* selected_pd = getSelectedPrimitiveDescriptor();
     if (selected_pd == nullptr) {
-        THROW_CPU_NODE_ERR("Preferable primitive descriptor is not set for node ", getName(), ".");
+        THROW_CPU_NODE_ERR("Preferable primitive descriptor is not set.");
     }
 
     DnnlMemoryDescCPtr inMemoryDesc = srcMemPtr->getDescWithType<DnnlMemoryDesc>();

src/plugins/intel_cpu/src/nodes/embedding_bag_packed.cpp

@@ -54,7 +54,7 @@ EmbeddingBagPacked::EmbeddingBagPacked(const std::shared_ptr<ov::Node>& op, cons
         }
     }
     if (getInputShapeAtPort(INDICES_IDX).getRank() != 2ul) {
-        THROW_CPU_NODE_ERR("layer has indices data with invalid rank.");
+        THROW_CPU_NODE_ERR("has indices data with invalid rank.");
     }
 }
 

src/plugins/intel_cpu/src/nodes/extract_image_patches.cpp

@@ -466,7 +466,7 @@ void ExtractImagePatches::execute(const dnnl::stream& strm) {
         const auto outStrides = getChildEdgeAt(0)->getMemory().getDescWithType<BlockedMemoryDesc>()->getStrides();
         execPtr->exec(src, dst, inStrides, outStrides);
     } else {
-        THROW_CPU_NODE_ERR("Can't execute extract image patches node. Primitive wasn't created");
+        THROW_CPU_NODE_ERR("Primitive wasn't created");
     }
 }
 

src/plugins/intel_cpu/src/nodes/grid_sample.cpp

@@ -41,7 +41,7 @@ GridSample::GridSample(const std::shared_ptr<ov::Node>& op, const GraphContext::
     : Node(op, context, NgraphShapeInferFactory(op)) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
 
     if (op->get_input_size() != 2 || op->get_output_size() != 1) {

src/plugins/intel_cpu/src/nodes/interpolate.cpp

@@ -2465,7 +2465,7 @@ void Interpolate::prepareParams() {
     std::vector<float> dataScales =
         getScales(getPaddedInputShape(srcDims, interpAttrs.padBegin, interpAttrs.padEnd), dstDims);
     if (!NCHWAsNHWC && (getOutputShapeAtPort(0).getRank() > 2 && (dataScales[0] != 1.f || dataScales[1] != 1.f))) {
-        THROW_CPU_NODE_ERR("Interpolate layer only supports resize on spatial dimensions(depth, height and width)");
+        THROW_CPU_NODE_ERR("only supports resize on spatial dimensions(depth, height and width)");
     }
 
     if (canUseAclExecutor) {
@@ -2724,7 +2724,7 @@ void Interpolate::execute(const dnnl::stream& strm) {
     } else if (aclExecPtr) {
         aclExecPtr->exec({srcMemPtr}, {dstMemPtr}, postOpsDataPtrs.data());
     } else {
-        THROW_CPU_NODE_ERR("Primitive didn't created");
+        THROW_CPU_NODE_ERR("Primitive wasn't created");
     }
 }
 

src/plugins/intel_cpu/src/nodes/inverse.cpp

@@ -19,7 +19,7 @@ Inverse::Inverse(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr&
     : Node(op, context, NgraphShapeInferFactory(op)) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
 
     auto inverse_op = as_type_ptr<op::v14::Inverse>(op);

src/plugins/intel_cpu/src/nodes/llm_mlp.cpp

@@ -504,7 +504,7 @@ LLMMLP::LLMMLP(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr& co
     std::string errorMessage;
     const auto& config = context->getConfig();
     if (!isSupportedOperation(op, errorMessage, config.fcDynamicQuantizationGroupSize)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
     const auto node_mlp = ov::as_type_ptr<const LLMMLPNode>(op);
     m_mlp_config = node_mlp->get_config();

src/plugins/intel_cpu/src/nodes/multinomial.cpp

@@ -18,7 +18,7 @@ Multinomial::Multinomial(const std::shared_ptr<ov::Node>& op, const GraphContext
     : Node(op, context, NgraphShapeInferFactory(op)) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
 
     auto multinomial_op = as_type_ptr<op::v13::Multinomial>(op);

src/plugins/intel_cpu/src/nodes/mvn.cpp

@@ -2319,7 +2319,7 @@ void MVN::execute(const dnnl::stream& strm) {
     } else if (aclExecPtr) {
         aclExecPtr->exec({srcMemPtr}, {dstMemPtr}, postOpsDataPtrs.data());
     } else {
-        THROW_CPU_NODE_ERR("Primitive didn't created");
+        THROW_CPU_NODE_ERR("Primitive wasn't created");
     }
 }
 

src/plugins/intel_cpu/src/nodes/ngram.cpp

@@ -109,7 +109,7 @@ void Ngram::execute(const dnnl::stream& strm) {
     } else if (idcesPrecision == ov::element::i64) {
         batchLenghts = computeBatchLenghts<std::int64_t>();
     } else {
-        THROW_CPU_NODE_ERR("Unsupported idces precision: ", idcesPrecision);
+        THROW_CPU_NODE_ERR("Unsupported indices precision: ", idcesPrecision);
     }
 
     /* The following procedure applied to each batch:

src/plugins/intel_cpu/src/nodes/paged_attn.cpp

@@ -56,7 +56,7 @@ PagedAttention::PagedAttention(const std::shared_ptr<ov::Node>& op, const GraphC
     : Node(op, context, InternalDynShapeInferFactory()) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
     // output score may have no child
     m_hasScore = !op->get_output_target_inputs(1).empty();

src/plugins/intel_cpu/src/nodes/pooling.cpp

@@ -507,7 +507,7 @@ void Pooling::prepareParams() {
         dnnlExecPtr = result.first;
 
         if (!dnnlExecPtr) {
-            THROW_CPU_NODE_ERR("Primitive descriptor was not found for node ", getName(), ".");
+            THROW_CPU_NODE_ERR("Primitive descriptor was not found.");
         }
 
         auto scratchpadMem = getScratchPadMem(dnnlExecPtr->getScratchPadDesc());

src/plugins/intel_cpu/src/nodes/qkv_proj.cpp

@@ -348,7 +348,7 @@ QKVProjection::QKVProjection(const std::shared_ptr<ov::Node>& op, const GraphCon
     }
 
     if (!isSupportedOperation(op, errorMessage, concurrency, config.fcDynamicQuantizationGroupSize)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
     const auto node = ov::as_type_ptr<const QKVProjectionNode>(op);
     m_config = node->get_config();

src/plugins/intel_cpu/src/nodes/random_uniform.cpp

@@ -41,7 +41,7 @@ RandomUniform::RandomUniform(const std::shared_ptr<ov::Node>& op, const GraphCon
     : Node(op, context, NgraphShapeInferFactory(op)) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
 
     // RandomUniform should generate new sequence each run even if all inputs are constants. So that method

src/plugins/intel_cpu/src/nodes/rdft.h

@@ -118,7 +118,6 @@ class RDFT : public Node {
     bool needShapeInfer() const override;
     bool needPrepareParams() const override;
 
-    std::string errorMsgPrefix;
     bool inverse;
     std::vector<int> axes;
     std::vector<int> signalSizes;

src/plugins/intel_cpu/src/nodes/rms_norm.cpp

@@ -122,7 +122,7 @@ RMSNorm::RMSNorm(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr&
     : Node(op, context, RMSNormShapeInferFactory(op)) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
     const auto rms = ov::as_type_ptr<const ov::op::internal::RMS>(op);
     m_eps = static_cast<float>(rms->get_epsilon());

src/plugins/intel_cpu/src/nodes/rope.cpp

@@ -25,7 +25,7 @@ RoPE::RoPE(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr& contex
     : Node(op, context, NgraphShapeInferFactory(op)) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
 
     const auto node = ov::as_type_ptr<const op::internal::RoPE>(op);

src/plugins/intel_cpu/src/nodes/scaled_attn.cpp

@@ -1084,7 +1084,7 @@ ScaledDotProductAttention::ScaledDotProductAttention(const std::shared_ptr<ov::N
     : Node(op, context, SDPAShapeInferFactory(op)) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
     const auto& cpuConfig = context->getConfig();
     const auto& keyCachePrecision = cpuConfig.keyCachePrecision;

src/plugins/intel_cpu/src/nodes/stft.cpp

@@ -33,7 +33,7 @@ STFT::STFT(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr& contex
     : Node(op, context, NgraphShapeInferFactory(op)) {
     std::string errorMessage;
     if (!isSupportedOperation(op, errorMessage)) {
-        THROW_CPU_NODE_ERR(errorMessage);
+        OPENVINO_THROW_NOT_IMPLEMENTED(errorMessage);
     }
 
     const auto stft_op = as_type_ptr<op::v15::STFT>(op);

src/plugins/intel_cpu/src/nodes/transpose.cpp

@@ -148,7 +148,7 @@ void Transpose::prepareParams() {
         auto srcDesc = dnnl::memory::desc(dstDesc.get_dims(), dstDesc.get_data_type(), memory::format_tag::acdb);
         auto result = getReorderPrim(context->getParamsCache(), getEngine(), srcDesc, dstDesc);
         if (!result) {
-            THROW_CPU_NODE_ERR("Reorder primitive descriptor was not found for Transpose node ", getName(), ".");
+            THROW_CPU_NODE_ERR("reorder primitive descriptor was not found.");
         }
         prim = result;