diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data.cpp index 36bd64dbb..c5da5603d 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data.cpp @@ -92,12 +92,17 @@ class ConvolutionBackpropDataExtendedLayerTest bool addBiases = false, const std::vector &filterWeights = {}, const std::vector &biasesWeights = {}) { - bool randomFilterWeights = filterWeights.empty(); auto shape = in.get_shape(); std::vector filterWeightsShape = {shape[1], numOutChannels}; filterWeightsShape.insert(filterWeightsShape.end(), filterSize.begin(), filterSize.end()); - auto filterWeightsNode = - ngraph::builder::makeConstant(type, filterWeightsShape, filterWeights, randomFilterWeights); + std::shared_ptr filterWeightsNode; + if (filterWeights.empty()) { + ov::Tensor random_tensor(type, filterWeightsShape); + ov::test::utils::fill_tensor_random(random_tensor); + filterWeightsNode = std::make_shared(random_tensor); + } else { + filterWeightsNode = std::make_shared(type, filterWeightsShape, filterWeights); + } return makeConvolutionBackpropData(in, filterWeightsNode, @@ -149,9 +154,9 @@ class ConvolutionBackpropDataExtendedLayerTest std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, padType, outputPad) = convBackpropDataParams; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); - auto params = ngraph::builder::makeParams(ngPrc, {inputShape}); - auto outputShapeNode = - ngraph::builder::makeConstant(ov::element::Type_t::i64, {outputShapeData.size()}, outputShapeData); + ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape(inputShape))}; + + auto outputShapeNode = std::make_shared(ov::element::Type_t::i64, ov::Shape{outputShapeData.size()}, outputShapeData); auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto convBackpropData = std::dynamic_pointer_cast( diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data_add.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data_add.cpp index 43b00ad26..bbf2e51b5 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data_add.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data_add.cpp @@ -90,13 +90,18 @@ class ConvolutionBackpropDataAddExtendedLayerTest bool addBiases = false, const std::vector &filterWeights = {}, const std::vector &biasesWeights = {}) { - bool randomFilterWeights = filterWeights.empty(); auto shape = in.get_shape(); std::vector filterWeightsShape = {shape[1], numOutChannels}; filterWeightsShape.insert(filterWeightsShape.end(), filterSize.begin(), filterSize.end()); - auto filterWeightsNode = - ngraph::builder::makeConstant(type, filterWeightsShape, filterWeights, randomFilterWeights); + std::shared_ptr filterWeightsNode; + if (filterWeights.empty()) { + ov::Tensor random_tensor(type, filterWeightsShape); + ov::test::utils::fill_tensor_random(random_tensor); + filterWeightsNode = std::make_shared(random_tensor); + } else { + filterWeightsNode = std::make_shared(type, filterWeightsShape, filterWeights); + } return makeConvolutionBackpropData(in, filterWeightsNode, output, @@ -147,9 +152,9 @@ class ConvolutionBackpropDataAddExtendedLayerTest std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, padType, outputPad) = convBackpropDataParams; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); - auto params = ngraph::builder::makeParams(ngPrc, {inputShape}); - auto outputShapeNode = - ngraph::builder::makeConstant(ov::element::Type_t::i64, {outputShapeData.size()}, outputShapeData); + ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape(inputShape))}; + + auto outputShapeNode = std::make_shared(ov::element::Type_t::i64, ov::Shape{outputShapeData.size()}, outputShapeData); auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto convBackpropData = std::dynamic_pointer_cast( @@ -163,8 +168,11 @@ class ConvolutionBackpropDataAddExtendedLayerTest dilation, padType, convOutChannels)); - auto addConstant = ngraph::builder::makeConstant(ngPrc, outputShapeData, outputShapeData, true); - auto add = ngraph::builder::makeEltwise(convBackpropData, addConstant, ngraph::helpers::EltwiseTypes::ADD); + + ov::Tensor random_tensor(ngPrc, outputShapeData); + ov::test::utils::fill_tensor_random(random_tensor); + auto addConstant = std::make_shared(random_tensor); + auto add = std::make_shared(convBackpropData, addConstant); ov::ResultVector results{std::make_shared(add)}; function = std::make_shared(results, params, "convolutionBackpropData"); } diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_biasadd_activation.hpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_biasadd_activation.hpp index 627628aca..957f70c78 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_biasadd_activation.hpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/convolution_biasadd_activation.hpp @@ -120,16 +120,15 @@ class BasicConvolutionBiasAddActivationLayerTest for (size_t i = 0; i < biasShape.size(); ++i) { if (i != channel_dim_index) biasShape[i] = 1; } - auto biasLayer = - ngraph::builder::makeInputLayer(ngNetPrc, ngraph::helpers::InputLayerType::CONSTANT, biasShape); + auto biasLayer = std::make_shared(ngNetPrc, biasShape); - auto biasAddLayer = ngraph::builder::makeEltwise(convLayer, biasLayer, ngraph::helpers::EltwiseTypes::ADD); + auto biasAddLayer = std::make_shared(convLayer, biasLayer); std::shared_ptr lastNode; if constexpr (HasAddNode) { auto addParam = std::make_shared(ngNetPrc, convLayer->get_output_shape(0)); params.push_back(addParam); - auto addLayer = ngraph::builder::makeEltwise(biasAddLayer, addParam, ngraph::helpers::EltwiseTypes::ADD); + auto addLayer = std::make_shared(biasAddLayer, addParam); lastNode = addLayer; } else { lastNode = biasAddLayer; @@ -164,7 +163,8 @@ class BasicConvolutionBiasAddActivationLayerTest } auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); - auto params = ngraph::builder::makeParams(ngPrc, {inputShape}); + ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape(inputShape))}; + auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector filter_weights; diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/cuda_eltwise.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/cuda_eltwise.cpp index a1d4d9d76..700a44977 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/cuda_eltwise.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/cuda_eltwise.cpp @@ -208,7 +208,7 @@ void CudaEltwiseLayerTest::SetUp() { init_input_shapes(shapes); - auto parameters = ngraph::builder::makeDynamicParams(netType, {inputDynamicShapes.front()}); + ov::ParameterVector parameters {std::make_shared(netType, inputDynamicShapes.front())}; ov::PartialShape shape_input_secondary; switch (opType) { @@ -229,8 +229,9 @@ void CudaEltwiseLayerTest::SetUp() { std::shared_ptr secondaryInput; if (secondaryInputType == ngraph::helpers::InputLayerType::PARAMETER) { - secondaryInput = ngraph::builder::makeDynamicParams(netType, {shape_input_secondary}).front(); - parameters.push_back(std::dynamic_pointer_cast(secondaryInput)); + auto input = std::make_shared(netType, shape_input_secondary); + secondaryInput = input; + parameters.push_back(input); } else { constexpr bool is_random = true; ov::Shape shape = inputDynamicShapes.back().get_max_shape(); @@ -246,15 +247,17 @@ void CudaEltwiseLayerTest::SetUp() { [](const auto& value) { return static_cast(static_cast(value)) == 0; }, 1); } - secondaryInput = ngraph::builder::makeConstant(netType, shape, data); + secondaryInput = std::make_shared(netType, shape, data); break; } case ngraph::helpers::EltwiseTypes::POWER: { - secondaryInput = ngraph::builder::makeConstant(netType, shape, {}, is_random, 3); + ov::Tensor random_tensor(netType, shape); + ov::test::utils::fill_tensor_random(random_tensor, 3, -3); + secondaryInput = std::make_shared(random_tensor); break; } default: { - secondaryInput = ngraph::builder::makeConstant(netType, shape, data); + secondaryInput = std::make_shared(netType, shape, data); } } } diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/fully_connected.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/fully_connected.cpp index bd74352d6..7915679b6 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/fully_connected.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/fully_connected.cpp @@ -3,7 +3,6 @@ // #include -#include #include #include "finite_comparer.hpp" @@ -83,21 +82,20 @@ class FullyConnectedLayerTest : public testing::WithParamInterface(ngPrc, ov::Shape{shapeRelatedParams.input1.first})}; - auto secondaryInput = - ngraph::builder::makeInputLayer(ngPrc, secondaryInputType, shapeRelatedParams.input2.first); + std::shared_ptr secondaryInput; if (secondaryInputType == ngraph::helpers::InputLayerType::PARAMETER) { - params.push_back(std::dynamic_pointer_cast(secondaryInput)); + secondaryInput = std::make_shared(ngPrc, ov::Shape(shapeRelatedParams.input2.first)); + params.push_back(std::static_pointer_cast(secondaryInput)); + } else { + secondaryInput = std::make_shared(ngPrc, shapeRelatedParams.input2.first); } - auto thirdInput = ngraph::builder::makeInputLayer( - ngPrc, ngraph::helpers::InputLayerType::CONSTANT, shapeRelatedParams.input3); + auto thirdInput = std::make_shared(ngPrc, shapeRelatedParams.input3); auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto MatMul = std::dynamic_pointer_cast(ngraph::builder::makeMatMul( - paramOuts[0], secondaryInput, shapeRelatedParams.input1.second, shapeRelatedParams.input2.second)); - auto Add = std::dynamic_pointer_cast( - ngraph::builder::makeEltwise(MatMul, thirdInput, ngraph::helpers::EltwiseTypes::ADD)); + auto MatMul = std::make_shared(paramOuts[0], secondaryInput, shapeRelatedParams.input1.second, shapeRelatedParams.input2.second); + auto Add = std::make_shared(MatMul, thirdInput); ov::ResultVector results{std::make_shared(Add)}; function = std::make_shared(results, params, "FullyConnected"); } @@ -189,33 +187,36 @@ class FullyConnectedLayer2MatMulTest : public testing::WithParamInterface(ngPrc, ov::Shape(shapeRelatedParams.matmul1_input1.first))); + params.push_back(std::make_shared(ngPrc, ov::Shape(shapeRelatedParams.matmul2_input1.first))); + + std::shared_ptr matmul0SecondaryInput; if (secondaryInputType == ngraph::helpers::InputLayerType::PARAMETER) { - params.push_back(std::dynamic_pointer_cast(matmul0SecondaryInput)); + matmul0SecondaryInput = std::make_shared(ngPrc, ov::Shape(shapeRelatedParams.matmul1_input2.first)); + params.push_back(std::static_pointer_cast(matmul0SecondaryInput)); + } else { + matmul0SecondaryInput = std::make_shared(ngPrc, shapeRelatedParams.matmul1_input2.first); } - auto matmul1SecondaryInput = - ngraph::builder::makeInputLayer(ngPrc, secondaryInputType, shapeRelatedParams.matmul2_input2.first); + + std::shared_ptr matmul1SecondaryInput; if (secondaryInputType == ngraph::helpers::InputLayerType::PARAMETER) { - params.push_back(std::dynamic_pointer_cast(matmul1SecondaryInput)); + matmul1SecondaryInput = std::make_shared(ngPrc, ov::Shape(shapeRelatedParams.matmul1_input2.first)); + params.push_back(std::static_pointer_cast(matmul1SecondaryInput)); + } else { + matmul1SecondaryInput = std::make_shared(ngPrc, shapeRelatedParams.matmul1_input2.first); } - auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto matMul0 = std::dynamic_pointer_cast( - ngraph::builder::makeMatMul(paramOuts[0], - matmul0SecondaryInput, - shapeRelatedParams.matmul1_input1.second, - shapeRelatedParams.matmul1_input2.second)); - auto matMul1 = std::dynamic_pointer_cast( - ngraph::builder::makeMatMul(paramOuts[1], - matmul1SecondaryInput, - shapeRelatedParams.matmul2_input1.second, - shapeRelatedParams.matmul2_input2.second)); - auto Add = std::dynamic_pointer_cast( - ngraph::builder::makeEltwise(matMul0, matMul1, ngraph::helpers::EltwiseTypes::ADD)); + auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); + auto matMul0 = std::make_shared(paramOuts[0], + matmul0SecondaryInput, + shapeRelatedParams.matmul1_input1.second, + shapeRelatedParams.matmul1_input2.second); + auto matMul1 = std::make_shared(paramOuts[1], + matmul1SecondaryInput, + shapeRelatedParams.matmul2_input1.second, + shapeRelatedParams.matmul2_input2.second); + auto Add = std::make_shared(matMul0, matMul1); ov::ResultVector results{std::make_shared(Add)}; function = std::make_shared(results, params, "FullyConnected"); } diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp index 2168cde31..cdc62cc17 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp @@ -34,10 +34,9 @@ class CUDNNGRUCellTest : public UnsymmetricalComparer { int seed = SEED_FIRST; for (const auto& op : ops) { if (std::dynamic_pointer_cast(op)) { - const auto constant = ngraph::builder::makeConstant( - op->get_element_type(), op->get_shape(), std::vector{}, true, up_to, start_from, seed); - function->replace_node(op, constant); - ++seed; + ov::Tensor random_tensor(op->get_element_type(), op->get_shape()); + ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, seed++); + function->replace_node(op, std::make_shared(random_tensor)); } } diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp index 275b1967e..76cf66aca 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp @@ -27,9 +27,9 @@ class CUDNNGRUSequenceTest : public UnsymmetricalComparer { for (const auto& op : ops) { if (std::dynamic_pointer_cast(op)) { if (op->get_element_type() == ov::element::Type_t::f32) { - const auto constant = ngraph::builder::makeConstant( - op->get_element_type(), op->get_shape(), std::vector{}, true, up_to, start_from, seed++); - function->replace_node(op, constant); + ov::Tensor random_tensor(op->get_element_type(), op->get_shape()); + ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, seed++); + function->replace_node(op, std::make_shared(random_tensor)); } } } @@ -57,9 +57,9 @@ class LPCNetCUDNNGRUSequenceTest : public UnsymmetricalComparer for (const auto& op : ops) { if (std::dynamic_pointer_cast(op)) { if (op->get_element_type() == ov::element::Type_t::f32) { - const auto constant = ngraph::builder::makeConstant( - op->get_element_type(), op->get_shape(), std::vector{}, true, up_to, start_from, seed++); - function->replace_node(op, constant); + ov::Tensor random_tensor(op->get_element_type(), op->get_shape()); + ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, seed++); + function->replace_node(op, std::make_shared(random_tensor)); } } } @@ -100,7 +100,9 @@ class LPCNetCUDNNGRUSequenceTest : public UnsymmetricalComparer }; m_max_seq_len_ = seq_lengths; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); - auto params = ngraph::builder::makeParams(ngPrc, {inputShapes[0], inputShapes[1]}); + ov::ParameterVector params; + params.push_back(std::make_shared(ngPrc, ov::Shape(inputShapes[0]))); + params.push_back(std::make_shared(ngPrc, ov::Shape(inputShapes[1]))); ASSERT_EQ(InputLayerType::CONSTANT, WRBType); std::vector WRB = {inputShapes[3], inputShapes[4], inputShapes[5], inputShapes[2]}; diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_cell.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_cell.cpp index 22bff0b1f..7f9c66625 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_cell.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_cell.cpp @@ -37,8 +37,9 @@ class CUDNNLSTMCellTest : public LSTMCellTest { int seed = SEED_FIRST; for (const auto& op : ops) { if (std::dynamic_pointer_cast(op)) { - const auto constant = ngraph::builder::makeConstant( - op->get_element_type(), op->get_shape(), std::vector{}, true, up_to, start_from, seed); + ov::Tensor random_tensor(op->get_element_type(), op->get_shape()); + ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, seed); + auto constant = std::make_shared(random_tensor); function->replace_node(op, constant); ++seed; } diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp index a982302d0..4eede00e7 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp @@ -26,14 +26,9 @@ class CUDALSTMSequenceTest : public UnsymmetricalComparer { for (const auto& op : ops) { if (std::dynamic_pointer_cast(op)) { if (op->get_element_type() == ov::element::Type_t::f32) { - const auto constant = ngraph::builder::makeConstant(op->get_element_type(), - op->get_shape(), - std::vector{}, - true, - up_to, - start_from, - counter++); - function->replace_node(op, constant); + ov::Tensor random_tensor(op->get_element_type(), op->get_shape()); + ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, counter++); + function->replace_node(op, std::make_shared(random_tensor)); } } } diff --git a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/range.cpp b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/range.cpp index 623263b47..bac509966 100644 --- a/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/range.cpp +++ b/modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/range.cpp @@ -220,9 +220,9 @@ struct CudaRangeLayerTest : public testing::WithParamInterface, CUDA::Device device{}; const bool optimizeOption = false; NodeVector params; - params.push_back(builder::makeConstant(Type(start_type), std::vector(), {start})); - params.push_back(builder::makeConstant(Type(Type_t::f32), std::vector(), {stop})); - params.push_back(builder::makeConstant(Type(step_type), std::vector(), {step})); + params.push_back(std::make_shared(ov::element::Type(start_type), ov::Shape(), start)); + params.push_back(std::make_shared(ov::element::f32, ov::Shape(), stop)); + params.push_back(std::make_shared(ov::element::Type(step_type), ov::Shape(), step)); params[0]->set_friendly_name("start"); params[1]->set_friendly_name("stop"); params[2]->set_friendly_name("step"); diff --git a/modules/nvidia_plugin/tests/unit/test_networks.hpp b/modules/nvidia_plugin/tests/unit/test_networks.hpp index 667f7b8c5..5eb2e1b33 100644 --- a/modules/nvidia_plugin/tests/unit/test_networks.hpp +++ b/modules/nvidia_plugin/tests/unit/test_networks.hpp @@ -9,18 +9,16 @@ #include inline std::shared_ptr CreateMatMulTestNetwork() { - ngraph::helpers::InputLayerType secondaryInputType = ngraph::helpers::InputLayerType::CONSTANT; auto netPrecision = InferenceEngine::Precision::FP32; std::map additionalConfig; auto ngPrc = InferenceEngine::details::convertPrecision(netPrecision); - auto params = ngraph::builder::makeParams(ngPrc, {{3, 2, 10, 10}}); + ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape{3, 2, 10, 10})}; - auto secondaryInput = ngraph::builder::makeInputLayer(ngPrc, secondaryInputType, {3, 2, 10, 20}); + auto secondaryInput = std::make_shared(ngPrc, ov::Shape{3, 2, 10, 20}); auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto MatMul = std::dynamic_pointer_cast( - ngraph::builder::makeMatMul(paramOuts[0], secondaryInput, false, false)); + auto MatMul = std::make_shared(paramOuts[0], secondaryInput, false, false); ov::ResultVector results{std::make_shared(MatMul)}; return std::make_shared(results, params, "MatMul"); } @@ -63,14 +61,13 @@ class SuperDummyOp : public ov::op::Op { }; inline std::shared_ptr CreateSuperOperationTestNetwork() { - ngraph::helpers::InputLayerType secondaryInputType = ngraph::helpers::InputLayerType::CONSTANT; auto netPrecision = InferenceEngine::Precision::FP32; std::map additionalConfig; auto ngPrc = InferenceEngine::details::convertPrecision(netPrecision); - auto params = ngraph::builder::makeParams(ngPrc, {{3, 2, 10, 10}}); + ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape{3, 2, 10, 10})}; - auto secondaryInput = ngraph::builder::makeInputLayer(ngPrc, secondaryInputType, {3, 2, 10, 20}); + auto secondaryInput = std::make_shared(ngPrc, ov::Shape{3, 2, 10, 20}); auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto superOp = std::make_shared(paramOuts[0], secondaryInput);