[CPU] Implement TopK-11 to CPU plugin (#16522)

src/common/transformations/src/transformations/convert_precision.cpp

@@ -8,6 +8,7 @@
 #include <ngraph/runtime/reference/convert.hpp>
 #include <openvino/opsets/opset1.hpp>
 #include <openvino/opsets/opset10.hpp>
+#include <openvino/opsets/opset11.hpp>
 #include <openvino/opsets/opset3.hpp>
 #include <openvino/opsets/opset4.hpp>
 #include <openvino/opsets/opset5.hpp>
@@ -334,7 +335,9 @@ bool ov::pass::ConvertPrecision::run_on_model(const std::shared_ptr<ngraph::Func
         {opset9::MulticlassNms::get_type_info_static(), fuse_type_to_multiclass_nms},
         {opset9::GenerateProposals::get_type_info_static(), fuse_type_to_generate_proposals},
         {opset6::CTCGreedyDecoderSeqLen::get_type_info_static(), fuse_type_to_ctc_greedy_decoder_seq_len},
+        {opset1::TopK::get_type_info_static(), fuse_type_to_topk},
         {opset4::TopK::get_type_info_static(), fuse_type_to_topk},
+        {opset11::TopK::get_type_info_static(), fuse_type_to_topk},
         {opset8::MaxPool::get_type_info_static(), fuse_type_to_maxpool},
         {opset4::NonZero::get_type_info_static(), fuse_type_to_nonzero},
         {opset4::Bucketize::get_type_info_static(), fuse_type_to_bucketize},
@@ -653,7 +656,7 @@ bool fuse_type_to_generate_proposals(const std::shared_ptr<ngraph::Node>& node,
 }
 
 bool fuse_type_to_topk(const std::shared_ptr<ngraph::Node>& node, const precisions_map& precisions) {
-    if (auto topk = ov::as_type_ptr<opset4::TopK>(node)) {
+    if (auto topk = ov::as_type_ptr<ov::op::util::TopKBase>(node)) {
         return update_type(1, node, precisions, [&](const element::Type& to) {
             topk->set_index_element_type(to);
         });

src/plugins/intel_cpu/src/nodes/topk.cpp

@@ -270,12 +270,12 @@ private:
     inline void topk_loop() {
         if (jcp_.algorithm == TopKAlgorithm::topk_bubble_sort) {
             if (jcp_.layout == TopKLayoutType::topk_blocked && jcp_.topk_innermost) {
-                if (jcp_.top_k == 1) {
+                if (jcp_.top_k == 1 && !jcp_.stable) {
                     topk_bubble_horiz();
                 } else {
                     topk_bubble_BLK_on_channel_verti();
                 }
-            } else if (jcp_.topk_innermost && jcp_.top_k == 1) {
+            } else if (jcp_.topk_innermost && jcp_.top_k == 1 && !jcp_.stable) {
                 topk_bubble_horiz();
             } else {
                 topk_bubble_vector();
@@ -1788,30 +1788,32 @@ private:
     }
 };
 
-bool TopK::isSupportedOperation(const std::shared_ptr<const ngraph::Node>& op, std::string& errorMessage) noexcept {
+bool TopK::isSupportedOperation(const std::shared_ptr<const ov::Node>& op, std::string& errorMessage) noexcept {
     try {
-        const auto topKOp = ngraph::as_type_ptr<const ngraph::op::v1::TopK>(op);
+        if (!one_of(op->get_type_info(), ov::op::v1::TopK::get_type_info_static(),
-        if (!topKOp) {
+                                         ov::op::v3::TopK::get_type_info_static(),
-            errorMessage = "Node is not an instance of the TopK from the operations set v1 or v3";
+                                         ov::op::v11::TopK::get_type_info_static())) {
+            errorMessage = "Node is not an instance of the TopK from the operation sets v1, v3 or v11";
             return false;
         }
 
+        auto topKOp = ov::as_type_ptr<const ov::op::util::TopKBase>(op);
         if (!isDynamicNgraphNode(op)) {
-            auto topKConst = std::dynamic_pointer_cast<const ngraph::opset1::Constant>(topKOp->get_input_node_shared_ptr(TOPK_K));
+            auto topKConst = std::dynamic_pointer_cast<const ov::op::v0::Constant>(topKOp->get_input_node_shared_ptr(TOPK_K));
             if (!topKConst) {
                 errorMessage = "Second tensor is not constant in static shape mode";
                 return false;
             }
         }
 
-        if (topKOp->get_mode() != ngraph::op::TopKMode::MAX &&
+        if (topKOp->get_mode() != ov::op::TopKMode::MAX &&
-                topKOp->get_mode() != ngraph::op::TopKMode::MIN) {
+            topKOp->get_mode() != ov::op::TopKMode::MIN) {
             errorMessage = "Unsupported mode.";
             return false;
         }
-        if (!one_of(topKOp->get_sort_type(), ngraph::op::TopKSortType::NONE,
+        if (!one_of(topKOp->get_sort_type(), ov::op::TopKSortType::NONE,
-                                  ngraph::op::TopKSortType::SORT_VALUES,
+                                             ov::op::TopKSortType::SORT_VALUES,
-                                  ngraph::op::TopKSortType::SORT_INDICES)) {
+                                             ov::op::TopKSortType::SORT_INDICES)) {
             errorMessage = "Unsupported sort type.";
             return false;
         }
@@ -1821,13 +1823,13 @@ bool TopK::isSupportedOperation(const std::shared_ptr<const ngraph::Node>& op, s
     return true;
 }
 
-TopK::TopK(const std::shared_ptr<ngraph::Node>& op, const GraphContext::CPtr context)
+TopK::TopK(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr context)
         : Node(op, context, NgraphShapeInferFactory(op, PortMask(TOPK_K))) {
     std::string errorMessage;
     if (isSupportedOperation(op, errorMessage)) {
         errorPrefix = "TopK layer with name '" + getName() + "'";
 
-        auto topKOp = ngraph::as_type_ptr<ngraph::op::v1::TopK>(op);
+        auto topKOp = ov::as_type_ptr<const ov::op::util::TopKBase>(op);
 
         auto in_dims = topKOp->get_input_partial_shape(TOPK_DATA);
         auto out_dims = topKOp->get_output_partial_shape(TOPK_DATA);
@@ -1835,15 +1837,23 @@ TopK::TopK(const std::shared_ptr<ngraph::Node>& op, const GraphContext::CPtr con
         auto in_dims_size = in_dims.size();
 
         if (!isDynamicNgraphNode(op)) {
-            auto topKConst = std::dynamic_pointer_cast<const ngraph::opset1::Constant>(topKOp->get_input_node_shared_ptr(TOPK_K));
+            auto topKConst = std::dynamic_pointer_cast<const ov::op::v0::Constant>(topKOp->get_input_node_shared_ptr(TOPK_K));
             if (!topKConst) {
                 IE_THROW() << errorPrefix <<  "gets non-constant second tensor in static shape mode!";
             }
         }
 
         axis = topKOp->get_axis();
-        mode_max = topKOp->get_mode() == ngraph::op::TopKMode::MAX;
+        mode_max = topKOp->get_mode() == ov::op::TopKMode::MAX;
-        sort_index = topKOp->get_sort_type() == ngraph::op::TopKSortType::SORT_INDICES;
+        sort_index = topKOp->get_sort_type() == ov::op::TopKSortType::SORT_INDICES;
+
+        stable = false;
+        if (!sort_index) {
+            const auto topKOpV11 = ngraph::as_type_ptr<const ov::op::v11::TopK>(op);
+            if (topKOpV11) {
+                stable = topKOpV11->get_stable();
+            }
+        }
 
         top_k = 0;
         preset_params_done = false;
@@ -1959,7 +1969,10 @@ void TopK::preset_params() {
     }
 
     if (isDynamicNode()) {
-        if ((layout == TopKLayoutType::topk_ncsp || layout == TopKLayoutType::topk_nspc) && topk_innermost) {
+        if (stable) {
+            algorithm = TopKAlgorithm::topk_bubble_sort;
+            bubble_inplace = false;
+        } else if ((layout == TopKLayoutType::topk_ncsp || layout == TopKLayoutType::topk_nspc) && topk_innermost) {
             algorithm = TopKAlgorithm::topk_heap_sort;
         } else {
             algorithm = TopKAlgorithm::topk_bubble_sort;
@@ -2006,8 +2019,11 @@ void TopK::prepareParams() {
         // [case 1]: if 2 * (top_k + 1) + 2 <= count_xmm, thus top_k is small enough that the vector registers are sufficient
         //           to keep all necessary data for sorting, no need to load and store frequently, use inplace bubble sort;
         //           (horizotal sorting cases not included)
-        // [case 2]: only when topk is imposed on innermost dimsension of planar(ncsp/nspc) layout, should heap sort be used;
+        // [case 2]: if stable sorting is required, bubble sort(topk_bubble_vector/topk_bubble_BLK_on_channel_verti) will be
-        // [case 3]: by default, use bitonic sort when alg_cost_bitonic < alg_cost_bubble, otherwise use bubble sort.
+        //           applied currently, because among the implemented sorting algorithms, these bubble sort implementations
+        //           are the only stable ones;
+        // [case 3]: only when topk is imposed on innermost dimsension of planar(ncsp/nspc) layout, should heap sort be used;
+        // [case 4]: by default, use bitonic sort when alg_cost_bitonic < alg_cost_bubble, otherwise use bubble sort.
         //           alg_cost_bitonic = (N / 4) * logN * (logN + 1)
         //           alg_cost_bubble = K * (K - 1) / 2 + (N - K) * K
         //           where, N = axis_dim, K = topk_k
@@ -2018,6 +2034,9 @@ void TopK::prepareParams() {
             if (top_k <= count_xmm / 2 - 2) {
                 algorithm = TopKAlgorithm::topk_bubble_sort;
                 bubble_inplace = topk_innermost && top_k == 1 ? false : true;
+            } else if (stable) {
+                algorithm = TopKAlgorithm::topk_bubble_sort;
+                bubble_inplace = false;
             } else if ((layout == TopKLayoutType::topk_ncsp || layout == TopKLayoutType::topk_nspc) && topk_innermost) {
                 algorithm = TopKAlgorithm::topk_heap_sort;
             } else {
@@ -2074,6 +2093,7 @@ void TopK::createPrimitive() {
         jcp.topk_innermost = topk_innermost;
         jcp.algorithm = algorithm;
         jcp.bubble_inplace = bubble_inplace;
+        jcp.stable = stable;
         jcp.sort_stride = static_cast<int>(I);
         jcp.work_amount = static_cast<int>(I);
         jcp.bitonic_idx_cnt = 0;
@@ -2207,7 +2227,9 @@ inline void TopK::prepare_original_idx() {
     bool shape_agnostic_alg = algorithm == TopKAlgorithm::topk_heap_sort ||
                              (algorithm == TopKAlgorithm::topk_bubble_sort && !bubble_inplace);
     if (shape_agnostic_alg) {
-        if (topk_innermost) {
+        bool use_idx_seq = stable ? topk_innermost && (layout == TopKLayoutType::topk_blocked || (top_k == 1 && !stable))
+                                  : topk_innermost;
+        if (use_idx_seq) {
             if (vec_idx_seq.empty()) {
                 vec_idx_seq.resize(axis_dim);
                 std::iota(vec_idx_seq.begin(), vec_idx_seq.end(), 0);

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

@@ -32,6 +32,7 @@ struct jit_topk_config_params {
     bool sort_index;         // sort by value or index. true: index; false: value
     bool topk_innermost;     // if topk sorting is applied on innermost dimension or other dimension
     bool bubble_inplace;     // all the elements in sorting is right in the register, no need to load and store for each comparison
+    bool stable;             // if require stable sorting
     TopKLayoutType layout;   // memory layout
     TopKAlgorithm algorithm; // topk sorting algorithm
     InferenceEngine::Precision precision; // precision
@@ -115,6 +116,7 @@ private:
     bool topk_innermost;
     bool jit_mode;
     bool sort_index;
+    bool stable;
     bool mode_max;
     int axis;
     static const size_t TOPK_DATA = 0;

src/plugins/intel_cpu/src/transformation_pipeline.cpp

@@ -71,6 +71,8 @@
 #include "transformations/op_conversions/softsign_decomposition.hpp"
 #include "transformations/op_conversions/softmax_decomposition.hpp"
 #include "transformations/op_conversions/unique_decomposition.hpp"
+#include "transformations/op_conversions/convert_topk3.hpp"
+#include "transformations/op_conversions/convert_topk11_downgrade.hpp"
 #include "transformations/opset_conversions/convert_opset2_to_opset1.hpp"
 #include "transformations/opset_conversions/convert_opset3_to_opset2.hpp"
 #include "transformations/smart_reshape/matmul_sr.hpp"
@@ -398,6 +400,8 @@ void Transformations::PreLpt(const std::vector<ov::element::Type>& defaultPrecis
     pass_config->disable<ov::pass::ConvertROIAlign9To3>();
     pass_config->disable<ov::pass::SoftSignDecomposition>();
     pass_config->disable<ov::pass::UniqueDecomposition>();
+    pass_config->disable<ov::pass::ConvertTopK3>();
+    pass_config->disable<ov::pass::ConvertTopK11ToTopK3>();
 
     pass_config->enable<ov::pass::NormalizeL2Decomposition>();
     pass_config->enable<ov::pass::ConvertInterpolate1ToInterpolate4>();

src/plugins/intel_cpu/tests/functional/single_layer_tests/topk.cpp

@@ -10,18 +10,20 @@
 using namespace InferenceEngine;
 using namespace CPUTestUtils;
 using namespace ov::test;
+using SortMode = ov::op::TopKMode;
+using SortType = ov::op::TopKSortType;
 
 namespace CPULayerTestsDefinitions {
 
 typedef std::tuple<
-        int64_t,                        // keepK
+        int64_t,                    // keepK
-        int64_t,                        // axis
+        int64_t,                    // axis
-        ngraph::opset4::TopK::Mode,     // mode
+        SortMode,                   // mode
-        ngraph::opset4::TopK::SortType, // sort
+        std::tuple<SortType, bool>, // sort and stable
-        ElementType,                    // Net precision
+        ElementType,                // Net precision
-        ElementType,                    // Input precision
+        ElementType,                // Input precision
-        ElementType,                    // Output precision
+        ElementType,                // Output precision
-        InputShape                      // inputShape
+        InputShape                  // inputShape
 > basicTopKParams;
 
 typedef std::tuple<
@@ -39,11 +41,13 @@ public:
         std::tie(basicParamsSet, cpuParams, additionalConfig) = obj.param;
 
         int64_t keepK, axis;
-        ngraph::opset4::TopK::Mode mode;
+        SortMode mode;
-        ngraph::opset4::TopK::SortType sort;
+        std::tuple<SortType, bool> sortTypeStable;
         ElementType netPrecision, inPrc, outPrc;
         InputShape inputShape;
-        std::tie(keepK, axis, mode, sort, netPrecision, inPrc, outPrc, inputShape) = basicParamsSet;
+        std::tie(keepK, axis, mode, sortTypeStable, netPrecision, inPrc, outPrc, inputShape) = basicParamsSet;
+        SortType sort = std::get<0>(sortTypeStable);
+        bool stable = std::get<1>(sortTypeStable);
 
         std::ostringstream result;
         bool staticShape = inputShape.first.rank() == 0;
@@ -52,6 +56,7 @@ public:
         result << "axis=" << axis << "_";
         result << "mode=" << mode << "_";
         result << "sort=" << sort << "_";
+        result << "stable=" << (stable ? "True" : "False") << "_";
         result << "netPRC=" << netPrecision << "_";
         result << "inPRC=" << inPrc << "_";
         result << "outPRC=" << outPrc << "_";
@@ -85,11 +90,13 @@ protected:
         std::tie(inFmts, outFmts, priority, selectedType) = cpuParams;
 
         int64_t keepK;
-        ngraph::opset4::TopK::Mode mode;
+        SortMode mode;
-        ngraph::opset4::TopK::SortType sort;
+        std::tuple<SortType, bool> sortTypeStable;
         ElementType inPrc, outPrc;
         InputShape inputShape;
-        std::tie(keepK, axis, mode, sort, netPrecision, inPrc, outPrc, inputShape) = basicParamsSet;
+        std::tie(keepK, axis, mode, sortTypeStable, netPrecision, inPrc, outPrc, inputShape) = basicParamsSet;
+        sort = std::get<0>(sortTypeStable);
+        stable = std::get<1>(sortTypeStable);
 
         if (additionalConfig[PluginConfigParams::KEY_ENFORCE_BF16] == PluginConfigParams::YES)
             inPrc = outPrc = netPrecision = ElementType::bf16;
@@ -112,33 +119,34 @@ protected:
         auto params = ngraph::builder::makeDynamicParams(netPrecision, {inputDynamicShapes[0]});
 
         // static shape need specific const k to test different sorting algorithms, dynamic shape tests random param k
-        std::shared_ptr<ngraph::opset4::TopK> topk;
+        std::shared_ptr<ov::op::v11::TopK> topk;
         if (staticShape) {
-            auto k = std::make_shared<ngraph::opset3::Constant>(ngraph::element::Type_t::i64, ngraph::Shape{}, &keepK);
+            auto k = std::make_shared<ov::op::v0::Constant>(ElementType::i64, ov::Shape{}, &keepK);
-            topk = std::dynamic_pointer_cast<ngraph::opset4::TopK>(
+            topk = std::dynamic_pointer_cast<ov::op::v11::TopK>(
-                    std::make_shared<ngraph::opset4::TopK>(params[0], k, axis, mode, sort));
+                    std::make_shared<ov::op::v11::TopK>(params[0], k, axis, mode, sort, ElementType::i32, stable));
         } else {
-            auto k = std::make_shared<ngraph::opset3::Parameter>(ngraph::element::Type_t::i64, inputDynamicShapes[1]);
+            auto k = std::make_shared<ov::op::v0::Parameter>(ElementType::i64, inputDynamicShapes[1]);
             params.push_back(k);
-            topk = std::dynamic_pointer_cast<ngraph::opset4::TopK>(
+            topk = std::dynamic_pointer_cast<ov::op::v11::TopK>(
-                    std::make_shared<ngraph::opset4::TopK>(params[0], k, axis, mode, sort));
+                    std::make_shared<ov::op::v11::TopK>(params[0], k, axis, mode, sort, ElementType::i32, stable));
         }
 
         topk->get_rt_info() = getCPUInfo();
 
         ngraph::ResultVector results;
         for (size_t i = 0; i < topk->get_output_size(); i++) {
-            results.push_back(std::make_shared<ngraph::opset4::Result>(topk->output(i)));
+            results.push_back(std::make_shared<ov::op::v0::Result>(topk->output(i)));
         }
 
         function = std::make_shared<ngraph::Function>(results, params, "TopK");
     }
 
-    void generate_inputs(const std::vector<ngraph::Shape>& targetInputStaticShapes) override {
+    void generate_inputs(const std::vector<ov::Shape>& targetInputStaticShapes) override {
         inputs.clear();
         const auto& funcInputs = function->inputs();
 
-        // Spec TopK_3.md allows to use unstable sorting, thus generate unreapeated input data to avoid a. and b.
+        // For unstable sorting, generate unrepeated input data to avoid a. and b. While for stable sorting,
+        // repeating values are explicitly set.
         // a. Skip comparing of index results, because an element in actual index tensor can be different with
         //    its counterpart in expected index tensor
         // b. If SortType is SORT_INDICES or NONE, the test program still needs to apply std::sort for all pairs
@@ -153,7 +161,11 @@ protected:
 
             // For int32, deliberately set big numbers which are not accurately representable in fp32
             int start = netPrecision == ElementType::i32 ? pow(2, 30) + 1 : - static_cast<int>(size / 2);
-            std::iota(data.begin(), data.end(), start);
+            size_t set_size = sort == SortType::SORT_VALUES && stable ? size / 2 : size;
+            std::iota(data.begin(), data.begin() + set_size, start);
+            if (sort == SortType::SORT_VALUES && stable) {
+                std::copy(data.begin(), data.begin() + set_size, data.begin() + set_size);
+            }
             std::mt19937 gen(0);
             std::shuffle(data.begin(), data.end(), gen);
 
@@ -178,7 +190,7 @@ protected:
             if (O * A * I != size)
                 FAIL() << "Incorrect blob shape " << shape;
 
-            auto *rawBlobDataPtr = static_cast<ngraph::bfloat16 *>(tensor.data());
+            auto *rawBlobDataPtr = static_cast<ov::bfloat16 *>(tensor.data());
             for (size_t o = 0; o < O; o++) {
                 for (size_t i = 0; i < I; i++) {
                     std::vector<int> data(A);
@@ -188,7 +200,7 @@ protected:
                     std::mt19937 gen(seed);
                     std::shuffle(data.begin(), data.end(), gen);
                     for (size_t a = 0; a < A; a++) {
-                        rawBlobDataPtr[o * A * I + a * I + i] = static_cast<ngraph::bfloat16>(data[a]);
+                        rawBlobDataPtr[o * A * I + a * I + i] = static_cast<ov::bfloat16>(data[a]);
                     }
                 }
             }
@@ -198,20 +210,28 @@ protected:
         inputs.insert({funcInputs[0].get_node_shared_ptr(), tensor});
 
         if (!staticShape) {
-            const auto& kPrecision = funcInputs[1].get_element_type();
+            generate_dynamic_k(funcInputs, targetInputStaticShapes);
-            const auto& kShape = targetInputStaticShapes[1];
-
-            const size_t startFrom = 1;
-            const size_t range = targetInputStaticShapes[0][axis];
-            const size_t seed = inferRequestNum++;
-            const auto kTensor = ov::test::utils::create_and_fill_tensor(kPrecision, kShape, range, startFrom, 1, seed);
-
-            inputs.insert({funcInputs[1].get_node_shared_ptr(), kTensor});
         }
     }
 
+private:
+    void generate_dynamic_k(const std::vector<ov::Output<ov::Node>>& funcInputs,
+                            const std::vector<ov::Shape>& targetInputStaticShapes) {
+        const auto& kPrecision = funcInputs[1].get_element_type();
+        const auto& kShape = targetInputStaticShapes[1];
+
+        const size_t startFrom = 1;
+        const size_t range = targetInputStaticShapes[0][axis];
+        const size_t seed = inferRequestNum++;
+        const auto kTensor = ov::test::utils::create_and_fill_tensor(kPrecision, kShape, range, startFrom, 1, seed);
+
+        inputs.insert({funcInputs[1].get_node_shared_ptr(), kTensor});
+    }
+
 private:
     int64_t axis;
+    SortType sort;
+    bool stable;
     size_t inferRequestNum = 0;
     ElementType netPrecision;
     bool staticShape;
@@ -236,14 +256,15 @@ std::vector<std::map<std::string, std::string>> additionalConfig = {
 const std::vector<int64_t> axes = {0, 1, 2, 3};
 const std::vector<int64_t> k = {1, 5, 7, 18, 21};
 
-const std::vector<ngraph::opset4::TopK::Mode> modes = {
+const std::vector<SortMode> modes = {
-    ngraph::opset4::TopK::Mode::MIN,
+    SortMode::MIN,
-    ngraph::opset4::TopK::Mode::MAX
+    SortMode::MAX
 };
 
-const std::vector<ngraph::opset4::TopK::SortType> sortTypes = {
+const std::vector<std::tuple<SortType, bool>> sortTypeStable = {
-    ngraph::opset4::TopK::SortType::SORT_VALUES,
+    std::tuple<SortType, bool>{SortType::SORT_VALUES, false},
-    ngraph::opset4::TopK::SortType::SORT_INDICES,
+    std::tuple<SortType, bool>{SortType::SORT_VALUES, true},
+    std::tuple<SortType, bool>{SortType::SORT_INDICES, false}
 };
 
 std::vector<ov::test::InputShape> inputShapes = {
@@ -266,7 +287,7 @@ INSTANTIATE_TEST_CASE_P(smoke_TopK, TopKLayerCPUTest,
             ::testing::ValuesIn(k),
             ::testing::ValuesIn(axes),
             ::testing::ValuesIn(modes),
-            ::testing::ValuesIn(sortTypes),
+            ::testing::ValuesIn(sortTypeStable),
             ::testing::ValuesIn(netPrecisions),
             ::testing::Values(ElementType::undefined),
             ::testing::Values(ElementType::undefined),
@@ -281,7 +302,7 @@ INSTANTIATE_TEST_CASE_P(smoke_TopK_dynamic, TopKLayerCPUTest,
             ::testing::Values(1),
             ::testing::ValuesIn(axes),
             ::testing::ValuesIn(modes),
-            ::testing::ValuesIn(sortTypes),
+            ::testing::ValuesIn(sortTypeStable),
             ::testing::ValuesIn(netPrecisions),
             ::testing::Values(ElementType::undefined),
             ::testing::Values(ElementType::undefined),
@@ -306,7 +327,7 @@ INSTANTIATE_TEST_CASE_P(smoke_TopK_int32, TopKLayerCPUTest,
             ::testing::ValuesIn(k_int32),
             ::testing::ValuesIn(axes),
             ::testing::ValuesIn(modes),
-            ::testing::ValuesIn(sortTypes),
+            ::testing::ValuesIn(sortTypeStable),
             ::testing::Values(ElementType::i32),
             ::testing::Values(ElementType::undefined),
             ::testing::Values(ElementType::undefined),
@@ -321,7 +342,7 @@ INSTANTIATE_TEST_CASE_P(smoke_TopK_int32_dynamic, TopKLayerCPUTest,
             ::testing::Values(1),
             ::testing::ValuesIn(axes),
             ::testing::ValuesIn(modes),
-            ::testing::ValuesIn(sortTypes),
+            ::testing::ValuesIn(sortTypeStable),
             ::testing::Values(ElementType::i32),
             ::testing::Values(ElementType::undefined),
             ::testing::Values(ElementType::undefined),
@@ -344,7 +365,7 @@ INSTANTIATE_TEST_CASE_P(smoke_TopK_bubble_BLK_on_channel_horiz, TopKLayerCPUTest
             ::testing::Values(1),
             ::testing::Values(1),
             ::testing::ValuesIn(modes),
-            ::testing::ValuesIn(sortTypes),
+            ::testing::ValuesIn(sortTypeStable),
             ::testing::ValuesIn(netPrecisions),
             ::testing::Values(ElementType::undefined),
             ::testing::Values(ElementType::undefined),
@@ -359,7 +380,7 @@ INSTANTIATE_TEST_CASE_P(smoke_TopK_bubble_BLK_on_channel_horiz_dynamic, TopKLaye
             ::testing::Values(1),
             ::testing::Values(1),
             ::testing::ValuesIn(modes),
-            ::testing::ValuesIn(sortTypes),
+            ::testing::ValuesIn(sortTypeStable),
             ::testing::ValuesIn(netPrecisions),
             ::testing::Values(ElementType::undefined),
             ::testing::Values(ElementType::undefined),
@@ -381,8 +402,8 @@ INSTANTIATE_TEST_CASE_P(smoke_Top1, TopKLayerCPUTest,
         ::testing::Combine(
             ::testing::Values(1),
             ::testing::Values(3),
-            ::testing::Values(ngraph::opset4::TopK::Mode::MAX),
+            ::testing::Values(SortMode::MAX),
-            ::testing::Values(ngraph::opset4::TopK::SortType::SORT_INDICES),
+            ::testing::Values(std::tuple<SortType, bool>(SortType::SORT_INDICES, false)),
             ::testing::ValuesIn(netPrecisions),
             ::testing::Values(ElementType::undefined),
             ::testing::Values(ElementType::undefined),
@@ -396,8 +417,8 @@ INSTANTIATE_TEST_CASE_P(smoke_Top1_dynamic, TopKLayerCPUTest,
         ::testing::Combine(
             ::testing::Values(1),
             ::testing::Values(3),
-            ::testing::Values(ngraph::opset4::TopK::Mode::MAX),
+            ::testing::Values(SortMode::MAX),
-            ::testing::Values(ngraph::opset4::TopK::SortType::SORT_INDICES),
+            ::testing::Values(std::tuple<SortType, bool>(SortType::SORT_INDICES, false)),
             ::testing::ValuesIn(netPrecisions),
             ::testing::Values(ElementType::undefined),
             ::testing::Values(ElementType::undefined),

src/tests/functional/shared_test_classes/src/base/utils/compare_results.cpp

@@ -80,6 +80,7 @@ CompareMap getCompareMap() {
 #include "openvino/opsets/opset8_tbl.hpp"
 #include "openvino/opsets/opset9_tbl.hpp"
 #include "openvino/opsets/opset10_tbl.hpp"
+#include "openvino/opsets/opset11_tbl.hpp"
 
 #include "ov_ops/opset_private_tbl.hpp"
 #undef _OPENVINO_OP_REG

src/tests/functional/shared_test_classes/src/base/utils/generate_inputs.cpp

@@ -835,6 +835,7 @@ InputsMap getInputMap() {
 #include "openvino/opsets/opset8_tbl.hpp"
 #include "openvino/opsets/opset9_tbl.hpp"
 #include "openvino/opsets/opset10_tbl.hpp"
+#include "openvino/opsets/opset11_tbl.hpp"
 
 #include "ov_ops/opset_private_tbl.hpp"
 #undef _OPENVINO_OP_REG

src/tests/ngraph_helpers/ngraph_functions/include/ngraph_functions/builders.hpp

@@ -16,6 +16,8 @@
 #include <ngraph/opsets/opset7.hpp>
 #include <ngraph/opsets/opset8.hpp>
 #include <ngraph/opsets/opset9.hpp>
+#include <ngraph/opsets/opset10.hpp>
+#include <ngraph/opsets/opset11.hpp>
 
 #include "ngraph_functions/utils/data_utils.hpp"
 #include "openvino/core/partial_shape.hpp"